In order to identify possible wear mechanisms for our alloys, we first sought to better understand the nature and role of the individual scratch. This was done by producing coupons in each alloy that could be scratched using a conical Rockwell C hardness tester with a diamond indenter under controlled loads. The samples were first ground plane-parallel on both sides and then polished on the side designated for testing, followed by scratching under both constant and increasing loads. A tape lift consisting of adhesive tape applied directly and uniformly to the scratch in order to embed and remove any spalled material allowed us to compare the susceptibility of the platinum and gold alloys to scoring damage. Tapes from the lift were subsequently examined with energy dispersive X-ray spectroscopy (EDX) to confirm composition of the metal chips as well as characterise the amount of chipping.

A key objective for our study is the simulation of typical human wear mechanisms as closely as possible. There are countless chemical environments and unique mechanical forces that jewellery items are subjected to during human wear, hence a standardised test that attempts to replicate such conditions can only be seen as an approximation of what actually happens in real-life conditions. Correlation with the anecdotal is therefore critical in terms of supporting experimental outcomes as representative of what may be experienced in the human population.

The wear testing performed consisted of three different tests. The first being an abrasion test that utilises a stone and sand media, the second a corrosion test in artificial human sweat and the third a polishing test employing a nutshell media. All media used were calibrated and laboratory grade. Cycles were done in sequence fashion with each of the first five cycles including abrasion, followed by corrosion, followed by polishing. Two subsequent cycles were performed that omitted abrasion and corrosion and only included polishing media. The total test duration amounted to 252.5 h.

Five cube-shaped and individually identified samples of each alloy were used for the testing as shown in Figure 2. Before and after each test in the sequence samples were weighed and characterised by optical microscopy and Vickers microhardness testing. Samples were cleaned in an ultrasonic bath with ethanol to assure any media that might be clinging to the surface was removed. The surfaces of select samples were also characterised by SEM.

The abrasion and polishing tests were based upon the European Industrial Standard DIN EN 12472. The apparatus consists of a motorised rotating drum (Figure 3) that is filled with either an abrasive blend of sand and stones (abrasion test) or nutshells (polishing test). According to the standard, the samples must be physically isolated from one another during testing in order to avoid mutual damage through sample-to-sample contact. Therefore, cubes were anchored along a nylon cord attached to both ends of the drum frame.

Fig. 3

The possible roles of corrosion and erosion corrosion, specifically in gold alloys that contain significant amounts of corrosion-prone base metal elements, were other areas we considered as possibly contributing to wear. The platinum alloys tested were pure platinum group metal (pgm) alloys that did not contain any base metals and are otherwise well-known for their high resistance to chemical corrosion. Therefore, while we did not expect this test to have any effect on pure pgm alloys we included them for the sake of completeness. The corrosion test was based upon the international standard ISO 3160-2. The test involves application of artificial human sweat to the test cubes followed by heating in a closed chamber at 40°C +/– 2°C for 24 h (Figure 4). This test was conducted for cycles one through five right after the abrasion test and prior to the polishing test. Table II gives the composition of the artificial sweat and Figure 4 shows the samples positioned in the chamber. Following the test, samples were cleaned in an ultrasonic bath of deionised water and documented by light optical microscopy.

Fig. 4

Tensile testing was performed in accordance with ISO 6892-1 and microhardness testing was done using a 100 g load (HV0.1) in accordance with DIN EN ISO 6507-1. Tensile properties for cast product were derived from the same casting processes as the test cubes and coupons with the exception of the gold-nickel alloys that were cast by the producer of these alloys. Details on tensile testing are described in (14).

Prior to testing, samples were documented by stereomicroscopy and light optical microscopy. Due to hand polishing the samples exhibit some deviation from the ideal shape as shown in the computer aided design (CAD) images. Selected samples were also documented to obtain details of the geometry, shape and surface condition (Figure 5). After the fourth and fifth cycles the surfaces of select samples were also investigated by SEM (Figure 6).

Fig. 5

Fig. 6

The cube dimensions were measured using a calibrated micrometre calliper. Mass was determined by an analytical balance with an accuracy of 10 μg. Density was determined with the same balance using the buoyancy method (Archimedes’ principle). The mass and volume losses were determined after the abrasion and polish tests and in order to compare the samples, mass loss was normalised with the sample surface area. Volume loss was calculated by dividing mass loss by density.

Vickers hardness of each sample was measured in the as-polished condition and after completion of each cycle (abrasion + corrosion + polish). One measurement was done on each side of the cubes with the exception of the side bearing the sample ID. Table III gives the average hardness value of each sample.

Through SEM analysis (Figures 7 and 8) we see the evidence that the depth of the scratch is impacted by the hardness of the alloy. As one might expect, the softer the alloy, the deeper the scratch and the more material is displaced. In the case of the soft alloy 950PtIr, the displaced material was concentrated at the edges and the tip of the scratch (Figure 8), which is typical for micro-ploughing. Local overload also resulted in cracking of the displaced material at the edge of the scratch that appears to be loosely connected. In comparison, the gold alloys showed not only cracking, but also significant chipping along the cracks. This was especially true for the 585AuNi, which has a stronger tendency for micro-cutting.

Fig. 7

Fig. 8

We noted that the alloys appeared to show different levels of porosity after polishing with the platinum alloys exhibiting low levels and the gold alloys exhibiting higher levels characterised as finely dispersed microshrinkage. From previous studies on the tensile properties of platinum alloys (13) it was established that the ductility values of elongation and reduction of area are significantly impacted by porosity levels. Therefore, increased chipping in the gold alloys may be not only a result of intrinsically lower ductility for these alloys, but also porosity-related decreases.

3.1.1 Tape Lift

Corrosion was qualitatively assessed by optical microscopy after each test. The presence of corrosion was most visible after the first cycle because the surface had less scratching from the wear tests than subsequent cycles. As expected for pure pgm alloys, both 950 platinum alloys (Table I) showed no visible changes following corrosion testing (Figure 10).

Fig. 10

The alloy that demonstrated the least amount of resistance to corrosion was the 585AuNi containing high amounts of nickel, copper and zinc (Figure 11). Following wear testing porosity was exposed to the surface, suggesting that corrosion was further promoted by microshrinkage pores that had been revealed. Such pores act as crevices where a concentration of corrodents is able to accelerate the corrosion process. This being the case, the casting quality level may be a contributor to reduced (or improved) wear resistance, particularly in alloys demonstrated to have low corrosion resistance such as the 585AuNi.

Fig. 11

The 750AuNi and both the 585AuPd and 750AuPd alloys did not exhibit visible corrosion after any of the five cycles. While higher corrosion resistance is expected with the greater noble metal content of these alloys, the potential effects of corrosion cannot be ruled out given their base metal content and the limited scope of our testing. Moreover, the corrosion testing performed was of a static nature, omitting the potential for an erosion corrosion dynamic that is likely present in human wear conditions. This topic is recommended for further testing to better understand the potential for effects on wear resistance in gold alloys.

The goal of this series of tests was quantitative determination of mass loss and volume loss through a combination of abrasion testing and polish testing. The total testing time can be segregated into abrasion time (sand + stone media) and polish time (nutshell media). Mass loss and volume loss were normalised with the surface area of the sample, allowing us to compare data from samples with a different geometry. The plotted values show the mass loss and volume loss per surface area of the sample. For simplicity, the terms ‘mass loss’ and ‘volume loss’ are used for normalised values in the text of this paper. Mass and volume loss were plotted against abrasion and polishing time and total wear time, respectively. The plots show the average loss of the five samples per alloy that were tested. This allowed for a segregation of data for the amount of wear measured in each of the different tests.

During the abrasion test portion of our assessment the mass and volume losses show a non-linear increase with increasing abrasion test time (Figure 12) in the beginning of the tests, which turns into a linear trend with increasing testing time. No remarkable difference between the alloys is observed and overall mass loss during abrasion testing is extremely small. The 585AuPd does show slightly higher wear compared to other alloys in this phase of the cycle, but mass loss was only 0.00216 g, or 0.08% of original mass.

Fig. 12

Volume loss was calculated by dividing mass loss by density. Due to the considerably different densities of the tested alloys three groups can be distinguished. The platinum alloys have a density of ca. 20 g cm⁻³; 750 gold alloys are at ca. 15 g cm⁻³; and 585 gold alloys are at 13–14 g cm⁻³. While mass loss is very similar for all alloys, the volume loss differs more due to these distinctly different density levels. The platinum alloys showed the lowest volume loss, followed by the 750 gold alloys and the 585 gold alloys. Total volume loss in the abrasion test was very low with a maximum value at only 0.0005 mm³, or 0.03% of the original volume.

For the polishing test the mass and volume loss rate (i.e., the mass and volume loss per unit of time) was comparable to the loss rate abrasion test. Mass loss was demonstrated to increase linearly with increasing polishing time. The platinum alloys again show the lowest mass loss with total mass loss after 244 h of combined testing at less than half that of the 750AuPd, which showed the highest mass loss in the group. The mass loss of the 585AuPd and the 585AuNi lies in between the two 750 gold alloys. The total mass loss after 244 h of testing was 0.013 g for the 950PtRu (lowest value) and 0.031 g for the 750AuPd (highest value). These are still very small amounts equal to 0.03% for the 950PtRu and 1.1% for the 750AuPd. However, when we consider volume losses these differences take on much greater significance. The volume loss of both 950 platinum alloys is a factor of three times lower compared to 750AuPd, and a factor of about two times lower compared to 585AuPd and both 750AuNi alloys.

Figure 13 shows the total mass and volume loss after all cycles of wear testing were completed. Since the absolute mass loss in the abrasive test was much lower than that in the polishing test, the abrasive test was omitted in the last two cycles of wear testing. The result in Figure 13 is very similar to that of Figure 14. Error bars indicate the results from the samples with the lowest and highest mass loss in one group of alloys, while the full symbols indicate the averaged mass loss of the five samples. The error bars confirm that the difference between the alloys remains significant. The mass loss curves demonstrate a linear trend that was fitted for select alloys. The slope indicates the mass loss per hour of wear, i.e., the rate of wear.

Fig. 13

Fig. 14

The assessment of surface quality focused on the rounding of corners and edges, which was qualitatively determined by stereo microscopy. Figure 5 demonstrates the samples with the lowest and highest volume loss, which are 950PtRu and 750AuPd respectively. Figures 5(a) and 5(c) were taken after completing the first two cycles of 10 h total wear testing. After 10 h very little difference can be detected in comparison with the as-polished condition of the samples. The mass loss after two cycles was only 0.0004 g, therefore this result is expected. Figures 5(b) and 5(d) demonstrate the sample surface after completing seven cycles. 950PtRu displays a very well-defined cube shape after the second cycle and only a very slight rounding of the corners following the seventh and final cycle. The absolute mass loss after the complete series of testing was 0.0131 g, or 0.3% for the 950PtRu.

All five of the 750AuPd samples displayed a less-defined cube shape in the as-polished condition as a result of hand polishing prior to testing. The surface also appears somewhat uneven (Figure 5). Nevertheless, a continuing deterioration of the cube geometry was demonstrated through testing. Following the second cycle edges and corners present with increased rounding, and this condition is even more pronounced after the seventh cycle, indicating mass loss had occurred during testing. Absolute mass loss for the 750AuPd after the completion of wear testing was 0.0307 g, or 1.1%.

The surface of select samples and conditions was captured by SEM imaging. Figure 6 depicts the samples with the lowest and highest volume loss after abrasion testing (Figures 6(a) and 6(c)) as well as subsequent corrosion and polish tests (Figures 6(b) and 6(d)). Following the abrasion test both sample surfaces are quite rough and exhibit deep dents and scratches. After the polish test both samples display a levelling of the topography of the sample. Notably, despite its lower hardness, (or perhaps because of it) 950PtRu exhibits a smoother surface finish compared to 750AuPd.

Tensile testing was performed to determine whether strength and ductility measures might play a role in mass loss. Table III shows the average results of tensile testing from four as-cast bars in each alloy. The hardness values are the average values that were measured on a set of five cube samples of each alloy.

We did not find any significant correlation with tensile properties or hardness and mass loss. As other studies showed before (2), it appears that high hardness is not an indicator for low mass or volume loss. However, the opposite also cannot be concluded. Rather, the situation appears to be more complex and depends upon the mechanism of mass loss during wear testing. The alloys exhibited very different hardness levels with one series of samples (585AuPd) showing a spread of more than 10%, indicating an inhomogeneous microstructure, due to porosity for example. Micropores were visible on the polished coupons of the 585 gold alloys (Figure 8).

It has been demonstrated in platinum alloys that the reduction of area value (ROA) is strongly reduced by microporosity (14). If this is the case, then the microstructure of the samples plays an important role on wear behaviour. Micropores along scratches will act as points of stress concentration and may cause the chips to break free. Increased levels of microporosity are likely to favour micro-chipping over micro-ploughing, suggesting increased mass loss due to metal chips. Further investigations will be necessary to prove such a hypothesis.

Industries face mounting challenges in the paradigm shift to a more circular economy. Research and development is increasingly focused on finding ways to turn waste into resources, recover energy and materials and make better use of resources extracted from the natural environment. At the same time industry and consumers seek to cause less harm in the form of pollution or CO₂ emissions. In this issue of the Johnson Matthey Technology Review, we look at current and future technologies that may be used by industries including energy, fuels, chemicals, pharmaceuticals and transport to create the products we need while meeting the United Nations (UN) 2030 goals for sustainable development (1): “development that meets the needs of the present without compromising the ability of future generations to meet their own needs” (2).

Continuing the theme from our previous issue (3), several articles present different approaches to future fuels and chemicals. These approaches include water electrolysis, utilisation of biomass and waste and CO₂ reduction.

Electrification will provide alternatives to fossil fuel use in many areas of industrial science and technology but some areas like long-haul aviation will likely continue to need liquid fuels. These fuels will be provided through one or more of the technologies being developed today. For example, a technology recently commercialised by Johnson Matthey and bp uses a Fischer-Tropsch process to create sustainable jet and diesel fuels from waste, biomass or existing CO₂ emissions. The challenges involved in achieving a commercially viable process at scale are explained.

The technoeconomics and life cycle assessment of producing sustainable commodity chemicals from waste biomass using aerobic fermentation at scale are explored in another Johnson Matthey collaboration, this time with the University of Nottingham and Northumbria University, UK. Rigorous process modelling has determined at what point the production of commodity chemicals from a lignin source will become commercially viable. The future of this promising technology looks bright, with the authors concluding that their platform has promise as a best-in-class technology for the production of a broad spectrum of renewable commodity chemicals.

Activated carbon can be produced and characterised from biomass waste for applications in environmental protection, clean energy and catalysis. The work is presented by Gebze Technical University, Turkey, in collaboration with Gasification Consultancy Ltd, UK. Waste biochar from the gasification of biomass is the feedstock, and removal of contaminants is key to its successful use.

Reducing CO₂ emissions from iron metallurgy will become increasingly important. The electrification of primary iron production in a carbon-free process is presented in a collaborative research article from National Technical University of Athens, Laboratory of Metallurgy and Mytilineos SA, Metallurgy Business Unit-Aluminium of Greece. The technology is demonstrated at an early stage with additional optimisation recommended by the authors. Catalytic hydrogenation of CO₂ to methane using power-to-gas combined with biomass gasification is another option to reduce the CO₂ emissions of the steel industry, presented by Montanuniversität Leoben, Johannes Kepler Universität Linz and K1-MET GmbH, Austria.

This journal has long championed sustainable technologies involving the precious metals. Metals are inherently recyclable and none more so than the platinum group metals (4). Today’s focus on electrification of transport and energy means that elements such as lithium, nickel, cobalt and manganese join their precious cousins as critical materials for the clean energy revolution. Clean and efficient extraction of these minerals from spent lithium-ion cathodes is an emerging area of study that will become increasingly important in the coming years when batteries begin to reach end-of-life. Recycling techniques need to be developed for the sustainable development of the lithium-ion batteries industry as discussed in this issue. Meanwhile life cycle assessment of the entire lithium-ion batteries production process from both primary ore and recycled material is provided in the output from an Innovate UK project involving Johnson Matthey and the Warwick Manufacturing Group, UK.

Energy efficiency will be a key enabler for a transition to a low carbon future. High technology industries like electronics, energy and medical applications require novel materials and processes. Cooling is a challenge, especially at the microscale. Nanofluids containing titania offer a potential solution and are investigated in this issue.

Conventional technologies will continue to be used alongside newer ones. To help define the next generation of emissions legislation to clean up the air in China, a portable emissions measurement system was used to investigate on-road tailpipe volatile organic compounds emissions in diesel trucks compliant with Euro III–V. The results with recommendations from the authors are presented in this issue.

It will become apparent from reading this issue that collaborations both within and between industry and academia are vital to progress. The research projects described here are just a selection. Many more advances can be expected in the coming years and decades as fruitful collaborations continue apace, with industry and academia working together to meet the challenges of the present and the future.

Growing environmental concerns have made it imperative to reduce global climate change and this has resulted in prolific development of various energy storage technologies for different applications ranging from portable electronic devices (PED) to electric vehicles (EVs) (1, 2). The most common chemical energy storage devices are batteries for applications requiring high energy density and electrochemical capacitors (ECs) for applications with high power density requirements (3–5). LICs which have the combined desirable properties of batteries (high energy density) and ECs (high power density) are increasingly being investigated as high-performance energy storage devices that have a significant role in the decarbonisation of the transport sector (6, 7).

While there are many promising negative electrode materials for LICs, the lithium titanium oxide (Li₄Ti₅O₁₂, LTO) based anode offers high stability towards charge-discharge cycles, faradaic efficiency and lower costs (8–10). As the envisaged use of the LTO based LIC is in hybrid and EVs to assist in decarbonising the transport sector, it becomes pertinent to conduct a LCA for the production of a LIC using primary ore minerals and make comparisons to a manufacturing process that relies on recycling end-of-life LIC. LCA is defined as a process to evaluate the environmental burdens associated with a product, process or activity by identifying and quantifying energy and materials used and wastes released to the environment (11). The assessment includes the entire life cycle of a product, process or activity, encompassing extracting and processing raw materials, manufacturing, transport and distribution, use, reuse, recycling and final disposal.

LCA facilitates informed decision making as comparative analysis of competing processes or products can be conducted based on environmental impact. At the early stages of R&D activities, LCA is an invaluable tool as it can inform process and material choices that support sustainability goals in addition to promoting innovation for designing products that are more amenable to recycling when they reach end-of-life (12–14). Increasingly, LCA is also being utilised to engage with stakeholders as an evolving green marketing tool through brand competitive differentiation on the basis of sustainability as well as regulatory compliance purposes (15–17). Besides the multifaceted benefits of LCA, its utilisation is not without limitations with uncertainties in inventory data, methodology and application of the weighting technique often being cited as major weaknesses of the approach (18, 19).

While the LCA methodology has been widely applied to energy storage systems this has mostly been for lithium-ion batteries (LIBs), with most studies having focussed on comparative analysis of LIBs to internal combustion engine (ICE) or sustainability of the different battery chemistries (20–22). There is a scarcity in the literature of LCA studies that have analysed production of energy storage devices using primary ore materials in comparison to manufacture of a similar product using recycled materials and specifically for LICs. This study objective is to take a comparative approach with the aim of utilising LCA to inform early phase R&D activities to improve the sustainability of the various process and reagents choices in the production of a LIC module.

The LCA study was conducted as part of the Advanced Lithium Ion Capacitors Electrodes (ALICE) project whose objective was to develop a 48 V LIC module for use in automotive, e-bus and materials handling equipment. The project consortium had industrial and academic partners for developing and scaling-up materials production including application of novel coating techniques to electrode structure to improve performance. The 48 V module built in the project was tested based on end user requirements and physics based numerical modelling applied at different stages of the project to interlink sophisticated layer structure characterisation results with cell performance.

2.1 Goal and Scope

2.2 Functional Unit and System Boundary

2.3 Methods and Databases

The elementary flows of material required to make the cells for a 48 V LIC module are based on pilot plant data. The recycled process data is based on a laboratory flowsheet that is simulated using a process model with appropriate scaling of model parameters from gram scale to a full-scale production plant. The main product and process stages for the primary (ore) and recycled materials manufacture of LIC are as follows: (a) anode powder material preparation; (b) anode preparation; (c) cathode preparation; (d) electrolyte preparation; (e) cell formation; and (f) recycling of LTO powder (recycled material process only).

The detailed breakdown of materials for the assemblies and product stages of the two LCA comparative projects is in Table I. The only difference between the two comparative studies is in the source of lithium carbonate and titania for making the anode LTO powder material. For the primary (ore) process, the information for the environmental footprint associated with lithium carbonate and titania is obtained from the ecoinvent 3.5 database based on ore extraction and salt formation environmental impact values. However, in the case of the LIC module made from recycled materials, lithium carbonate and titania are obtained from the recycling product stage and only have process environmental impact values associated with reagents and energy consumption demand to recycle the end-of-life LTO anodes.

The supplementary data which contains the flowcharts and inventory to produce a lithium ion capacitor module and the list of assumptions used in the study is located with the online version of this article.

3.1 LTO Powder Synthesis

3.2 Anode and Cathode Preparation

3.3 Electrolyte, Cell and Lithium-Ion Capacitor Module Formation

3.4 Modelling of LTO Recycling Process

While results for several environmental impact categories were available for analysis, for purposes of this study climate change (kilogram of CO₂ equivalent) and terrestrial acidification (kilogram of SO₂ equivalent) were analysed in greater detail for comparing the LIC module manufacture from primary ore materials against the recycled material process. The calculations are based on the ReCiPe Midpoint (H) with European Normalisation (24). The ReCiPe method was utilised because of its environmental relevance to the scope of the study, transparency and reproducibility. However, other methods which are also compatible with ISO standards could have been applied to the study.

Aluminium had the highest climate change and terrestrial acidification burdens to the extent of overshadowing contributions from other materials. To facilitate detailed analysis of environmental burdens of the other materials and processes, visual graphics of the results were plotted without the contribution from aluminium. Aluminium has established recycling processes but the decision if the quality of this recycled aluminium was of specifications sufficient for direct use in LIC manufacture was indeterminate and therefore the LCA credit process was not applied towards aluminium used. Figure 4 compares the climate change impact for making a 48 V LIC module using primary ore material and recycled LTO. Overall, utilising recycled LTO materials reduces the climate change impact by 12%. The order of decreasing climate change for the LIC module manufacture using primary (ore) materials is titania > lithium hexafluorophosphate > ethylene carbonate. For LIC module manufacture using recycled LTO, the order of decreasing climate change is lithium hexafluorophosphate > formic acid > ethylene carbonate. The highest contributor towards climate change for primary (ore) case is titania while for the recycled LTO it is the lithium hexafluorophosphate electrolyte. Lithium hexafluorophosphate and ethylene carbonate are both part of the electrolyte system and have significant contributions which are equal for LIC manufacture using either primary (ore) or recycled LTO materials. Therefore, significant reductions in climate change for LIC manufacture using recycled LTO can only be achieved by reducing the quantities of formic acid used. Table II shows the climate change impact over the various stages of manufacturing a 48 V LIC module. The anode preparation stage has the highest contribution towards climate change for the two comparative cases. However, using recycled LTO lowers the climate change impact by 21 kg_CO2eq compared to using primary (ore) during the anode preparation stage. The cathode preparation and cell formation stages have the same values as the two cases only differ in source of materials used the anode preparation stage.

Fig. 4

Comparative analysis of terrestrial acidification for producing a 48 V LIC module using primary (ore) and recycled LTO materials is shown in Figure 5. Usage of recycled LTO for the anode manufacture product stage results in 18% reduction in terrestrial acidification compared to using primary ore materials. The major contributors towards terrestrial acidification in decreasing order are lithium hexafluorophosphate > titania > ethylene carbonate for LIC module manufacture using primary (ore) materials. For LIC manufacture using recycled LTO, the major contributors towards terrestrial acidification in decreasing order are lithium hexafluorophosphate > formic acid > ethylene carbonate. Table III shows the terrestrial acidification associated with the various stages of manufacturing a 48 V LIC module for the two cases. The anode preparation stage has the highest contribution towards terrestrial acidification when the primary (ore) and recycled LTO material sources are compared. By utilising recycled LTO for the anode preparation process the terrestrial acidification impact is lowered by 0.21 kg_SO2eq compared to using primary (ore) materials.

Fig. 5

While there are environmental benefits from using recycled LTO, the existing recycling process flowsheet has a lot of optimisation opportunities especially regarding the quantities of formic acid used which have a significant contribution towards both climate and terrestrial acidification.

The application in early phase R&D activities is demonstrated in this section as applied to process development choices for the recycling stage. Before the hydrometallurgical treatment detailed in Section 3.4, the LTO has to be decoated (removed) from the aluminium foil to which it is bound. The widely used binder for coating the LTO and most active materials to current collectors is polyvinylidene fluoride (PVDF) because of its adhesive capabilities and electrochemical stability (25). The PVDF binder presents a challenge to the decoating process as it is only partially soluble in most common solvents. The common solvent for dissolving PVDF is NMP which is also used during the slurry coating process. However, NMP has high environmental and toxicity burdens which has resulted in stringent legislative restrictions of its usage (26).

To improve the sustainability metrics of the recycling process, several alternative solvents were investigated for their capabilities to remove the LTO from the aluminium foils. Acetone and polyethylene glycol (PEG) have similar properties to dipolar aprotic solvents like NMP and were identified as greener alternatives (27). Several other organic reagents such as acetic acid, formic acid, ethylene glycol and methanol were also screened as potential candidates for the process. Figure 6 shows images of LTO anodes after stirring in different reagents for 1 h at room temperature. From Figure 6, formic acid has higher technical performance compared to the other solvents as it removed all of the visible traces of carbon and LTO from the aluminium foil.

Fig. 6

The decision-making process considered the environmental footprint of these reagents in addition to their technical performance for removing the LTO from the aluminium foils. Figures 7(a) and 7(b) show the contribution towards climate change and terrestrial acidification respectively based on using 1 kg of these reagents. NMP has the highest environmental burden for climate change and terrestrial acidification, while methanol has the least environmental footprint. However, methanol efficiency in decoating LTO was low and therefore a trade-off of technical performance, environmental impact and costs resulted in formic acid as the alternative reagent choice for the decoating process stage. The bulk purchase price for these reagents is in Table IV.

Fig. 7

While several product and process research activities are focussing on novel binders that are less toxic and low costs compared to PVDF (29), the electrodes bound with PVDF that have already been manufactured will still require a more environmentally sustainable process to recover the active material at their end-of-life. The approach applied in this case study of early phase R&D process development activities demonstrated sustainable choices in alternate reagent selection in alignment to the triple bottom line approach (30). The choice of formic acid when compared to NMP results in intersection of people, planet and profit (3Ps) requirements of sustainability. For this case study, formic acid had reduced environmental impact, toxicity and meets the profit criteria through high decoating technical efficiency at lower costs compared to NMP.

The LCA methodology was applied to quantitatively determine the environmental burdens associated with manufacturing a 48 V LIC module. The prospective LCA compared the environmental impact of manufacturing a LIC module using primary ore materials versus LIC manufacture using recycled materials from end-of-life LICs. The anode preparation stage is associated with most of the environmental burden for manufacturing the LIC module for both processes due to the source of precursors used in production of the active LTO material. Utilisation of LTO precursors from recycled end-of-life LICs reduced both climate change and terrestrial acidification environmental impact categories for the LIC module manufacture. However, the sustainability metrics of the recycled process route of production could potentially be improved further by optimised application of formic acid which is used in the process stage for separating the LTO from the aluminium current collector foils.

The application of the LCA methodology in early phase R&D activities was demonstrated for the process development reagent choice case study. The LTO decoating reagent decision-making process considered the environmental footprint, technical performance and costs. The decision to utilise formic acid as a decoating agent was a sustainable choice which balanced environmental, economic and social performance. For the demonstrated case study, the choice of formic acid as decoating reagent reduced climate change and terrestrial acidification, lowered human toxicity values and met the profit criteria through high separation efficiency at lower costs.

In the 21st century, there is a need to deal with threats such as energy scarcity and environmental deterioration. The worldwide usage of fossil fuels accounted for 84.7% of global energy consumption in 2018, which is equivalent to 11.7436 billion tonnes of oil (1–2). Global CO₂ emissions, especially from fossil fuels, will continue to grow rapidly. It is crucial to explore green and renewable energy systems, such as wind, tidal and solar energy, and energy storage such as batteries, to replace fossil fuels. LIBs, with excellent energy storage properties, safety and stability, are among the most promising clean and sustainable energy storage equipment. LIBs are widely used in zero-emission vehicles (mainly electric vehicles (EVs), and plug‐in hybrid electric vehicles (PHEVs)), computers and electronic communication devices (3–6). The newly emerging model for super-performance LIBs, assembled with specific complex three-dimensional (3D), porous and polyhedral geometric structures in cathode and anode materials, is perfectly suited to the scale-up requirements for zero-emission vehicles (3–5). Increasing demand for new energy vehicles contributes to the expansion of the LIBs market. It has been estimated that the world’s production of LIBs would increase by 520% from 2016 to 2020 (7), and about 50 million electric buses will run on the road by the end of 2027 (8). Therefore the number of expired LIBs, as major electronic wastes, will inevitably increase. In China, the weight of retired LIBs was predicted to reach 500,000 tonnes by the end of 2020 (9), and that of the European Union to reach 13,828 tonnes in 2020 (10). Since harmful substances may damage the environment and the metals contained in spent LIBs are precious resources, the recovery of retired LIBs is bound to gain considerable social, economic and environmental benefit.

The cathodes of retired LIBs are rich in valuable nonferrous metals such as lithium, nickel, cobalt and manganese, which are secondary resources worth recycling. Considering potential immense profit, researchers have been working hard to develop various technologies to recycle the metals in spent LIBs. Current recycling technologies mainly include pyrometallurgy and hydrometallurgy. Although pyrometallurgical recovery processes have the advantages of a short process, high efficiency and easy industrial application, high energy consumption and generation of toxic gases still limit their development (11–14). In contrast, hydrometallurgical recovery processes have attracted extensive attention due to low energy consumption, environmental friendliness and high recovery efficiency (15–19).

Leaching valuable elements by chemical reagents is the core of the hydrometallurgical recovery strategy. After leaching, valuable metals in the leachate are extracted by chemical precipitation, solvent extraction and ion-exchange (20–25). The conventional hydrometallurgical process for waste electrodes recovery can be illustrated as follows: (a) acid-reductant leaching and selective chemical precipitation; (b) sulfuric roasting, acid leaching and selective chemical precipitation; (c) mechanochemical activation leaching and selective chemical precipitation, as shown in Table I (26–34). However, sulfuric roasting or mechanochemical activation before leaching may complicate the recovery process and decrease overall leaching rate. Based on the principle: waste substance + waste substance → rebirth resources, Li et al. (35) developed an in situ recovery model for graphite, Li₂CO₃ and cobalt by oxygen-free roasting with an anode graphite + wet magnetic separation process, without pretreating or adding any other chemical reagents. However, this technique is not suitable for recovering complex electrode materials. Prabaharan et al. (36) investigated an electrochemical leaching system: lead as anode + electrode scraps as cathode + H₂SO₄ as leachate, in which the leaching rate of manganese, copper and cobalt exceeded 96% through adjusting pH value. Although it can perfectly achieve integrated recovery of valuable metals, the high electricity consumption and recovery cost limit the use of this method. Surprisingly, Gomaa et al. (37, 38) explored a new multifunctional recovery method to recycle ultratrace Co²⁺ (~3.05 × 10^–8 M and 4.7 × 10^–8 M respectively) with visible selective ion extraction-separation-detection. It can extract almost 100% Co²⁺ from leachate in only 10–15 min and the used ion-extractors after activation can be regenerated and reused in repeated adsorption-desorption processes. Following desorption by HCl eluting reagent, the overall recovery rates of cobalt from waste LIBs or printed circuit boards (PCBs) are 98% and 95.7% respectively.

NCM batteries consist of more valuable metals that are worth recycling compared with traditional LiCoO₂ and LiFePO₄ batteries. However, few reports have been made to systematically clarify recovery techniques for waste NCM materials. In order to avoid loss of valuable resources and risk of secondary pollution, it is urgent to construct a sustainable recycling model for valuable metals in cathodes of spent LIBs. This review aims to describe progress in hydrometallurgical recycling of cathode materials from spent NCM batteries. The hydrometallurgical recovery strategy of waste LIBs can be classified into three steps: (a) pretreatment or separation of active substances; (b) leaching or extracting the valuable metals from the active substances with appropriate solvents; (c) separation of valuable metals by selective extraction from leachate by different methods to obtain the metals or metallic compounds. The conventional process flow for recycling NCM materials from waste LIBs by hydrometallurgy is shown in Figure 1. The advantages, disadvantages, existing problems and current status of each treatment method are analysed. Furthermore, advanced recovery technologies, DESs extraction and crystal repair direct-regeneration/recovery technology are illustrated. The challenges and prospects for metals recovery from ternary cathode materials of used LIBs by hydrometallurgy are described. By comparing the advantages and disadvantages of different methods, it is expected that this information will contribute to exploring economic, green, sustainable, high-efficiency leaching, separation and regeneration recovery systems for closed-circuit recycling of LIBs.

Fig. 1

The LIBs are mainly divided into five types depending on the composition of cathode materials: lithium iron phosphate (LiFePO₄), lithium cobalt oxide (LiCoO₂), lithium manganese oxide (LiMn₂O₄), lithium nickel oxide (LiNiO₂) and lithium NCM oxide (LiNi_x Co_y Mn_{1–x –y} O₂,0<x +y <1) (39–43). Of these, layered LiNi_x Co_y Mn_{1–x –y} O₂(NCM) materials are preferred because of their excellent cycle and rate performance. Currently, there are five types of NCM cathode materials that have been commercialised: NCM333 (LiNi_1/3Co_1/3Mn_1/3O₂), NCM424 (LiNi_0.4Co_0.2Mn_0.4O₂), NCM523 (LiNi_0.5Co_0.2Mn_0.3O₂), NCM622 (LiNi_0.6Co_0.2Mn_0.2O₂) and NCM811 (LiNi_0.8Co_0.1Mn_0.1O₂) (44). It is predicted that NCM batteries will account for nearly 41% of the world’s LIBs market in 2025 (42). The chemical characteristics and potential hazards of each component in ternary LIBs are summarised in Table II (45–48). NCM cathode materials are rich in lithium, nickel, cobalt, manganese and other strategic essential metals. The heavy metals in waste LIBs will pose a huge threat to human health and the environment (49). Furthermore, the scarcity and high cost of nonferrous metals such as cobalt make it imperative to recycle ternary cathode materials from retired LIBs. It is also reported that the global lithium resource reserves in 2018 are over 62 million tonnes, but China only accounts for 7%, about 4.5 million tonnes (50). As a core raw material for LIBs, the value of cobalt is as high as AUD$115,000 per tonne (51, 52). Efficient extraction of these valuable nonferrous metals from retired LIBs is of great significance for green and sustainable development of the batteries industry.

3.1 Recovery Process

3.2 Recovery Process of Hydrometallurgical Method

4.1 Regeneration of Nickel Cobalt Manganese from Leachate

Sustainable recovery and regeneration of NCM materials from leaching solution is the current main trend for recovery of exhausted LIBs. Common methods to synthesise cathode materials include chemical coprecipitation, high temperature solid phase, hydrothermal synthesis, sol-gel, microwave synthesis and electrostatic spinning method (95–100). The parameters of resynthesis methods to regenerate NCM cathode materials from leachate are summarised in Table VII (61, 101–107).

NCM cathode materials regenerated by a hydrometallurgical process hold superior crystal morphology and rate/cycle performance. Their electrochemical performance is comparable to that of commercial NCM materials (102, 104). The conventional hydrometallurgical regeneration process to prepare NCM materials is as follows: leaching liquid → coprecipitation → solid phase synthesis at high temperature, as shown in Figure 6. In the regeneration process, appropriate amounts of cobalt salts, manganese salts, nickel salts and lithium salts are added according to the stoichiometric composition of NCM materials.

Fig. 6

Regeneration flow of LiNi_1/3Co_1/3Mn_1/3O₂ cathode material from leaching liquid by coprecipitation

Li et al. (108) resynthesised NCM333 (R-NCM) materials from spent cathode materials leaching liquids by a one-step sol-gel method, and the related details and recycling mechanism are shown in Figures 7 and 8 (108). In the recovery system, H₂O₂ is used as reducing agent, and lactic acid plays the role of leaching agent in the leaching stage and chelating agent in the regeneration stage respectively. The mechanism of leaching stage can be shown using Equation (i):

(i)

Fig. 7

Resynthesis flow of LiNi_1/3Co_1/3Mn_1/3O₂ cathode material from leachate of spent LIBs by sol-gel method

Fig. 8

(a) Possible products and mechanism in the lactic acid leaching process; (b) XRD and SEM patterns of R-NCM and F-NCM samples; (c) electrochemical performances of R-NCM and F-NCM samples: charge/discharge profiles at 0.2 C; (d) cycling performances at 1 C; (e) rate performances at different currents and (f) Nyquist plots in the frequency range of 100 kHz to 0.01 Hz. Reprinted with permission from (108). Copyright (2017) American Chemical Society

Under optimal conditions (lactic acid = 1.5 M, s/d = 20 g l^–1, H₂O₂ = 0.5 vol%, temperature = 343 K, where s/d means solid/liquid (S/L) ratio) the leaching efficiency of the metals reached 98%. Electrochemical results proved that the R-NCM cathode material held excellent reversible discharge capacity of 138.2 mAh g^–1 while capacity retention reached 96% at 0.5 C after 100 cycles (105). Due to low charge-transfer resistance (R_ct) of R-NCM (58.78 Ω) compared with fresh NCM333 (F-NCM, R_ct = 70.02 Ω), which can provide higher lithium ion diffusion coefficient (D_Li⁺) and faster lithium-ion intercalation/deintercalation kinetic properties, the electrochemical performance, especially cycle capability, of R-NCM is self-evidently higher than that of F-NCM. It is indicated that the chelating agent lactic acid can efficiently recycle and resynthesise NCM materials by a sol-gel method with closed-loop recovery process.

4.2 Integrated High Value Utilisation of Electrode Scraps

4.3 Potential and Challenges of Mediate/Direct Regeneration Method

5.1 Extractive Methods Based on Deep Eutectic Solvents

Compared with traditional extractants, DESs have the advantages of being non-toxic, cheap, biodegradable and possessing extremely high dissolution and reduction capability for metal oxides (114, 115). However, there are few reports on recycling electronic waste using DESs. Tran et al. (116) first applied DESs to recycle cathode materials from waste LIBs. The adopted DESs were synthesised by choline chloride and ethylene glycol, and the possible synthesis reaction is shown in Equation (ii):

(ii)

The aluminium foil and binder PVDF were recovered respectively while valuable metals were extracted by DESs. The results showed that the leaching rate of cobalt in LiCoO₂ cathode material was as high as 99.4% at 180ºC, which was comparable to that of traditional leaching agents such as sulfuric acid (99.70%) (70) and formic acid (99.96%) (72). Cobalt in the DESs liquids can be recovered as Co₃O₄ by electrodeposition and calcination.

Wang et al. (117) developed a recycling process using DESs to detach active substances and aluminium foil of retired LIBs, as the recovery flow shown in Figure 10. The specific synthesis reaction of DESs is shown in Equation (iii):

(iii)

Fig. 10

The separation of cathode materials and aluminium foil from spent LIBs by using choline chloride-glycerol DESs

The DESs attacked the hydrogen atoms in PVDF molecular chain, forming unsaturated double bonds, which were further oxidised into hydroxyl and carbonyl to construct an unsaturated ketone structure on the molecular chain. Therefore, PVDF was forced to deactivate and dissolve, the active materials and aluminium foil were separated successfully. Hence, it can be indicated that DESs have great potential in regenerating cathode materials. High selectivity of valuable metals is the key to promote leaching performance of DESs in recycling spent LIBs.

5.2 Nickel Cobalt Manganese Particles Recovery

Despite high recovery rates of R-NCM from leaching solution, electrochemical performance is damaged to some extent due to inevitable contact with organic solvent during the treatment process. In the future, recovery technologies with low efficiency must be avoided. Sieber et al. (118) directly recovered NCM particles from used cathode scraps. The active material was detached from the aluminium foil by strong stirring in water to maintain the electrochemical performance and morphological characteristics of NCM particles. However, during the separation process, side reactions occurred when the NCM cathode contacted with water, resulting in a rapid increase in pH value and degradation of NCM particles followed by forming of Al(OH)₃ precipitate and LiAl(OH)₄. The main chemical reactions during separation stage are as follows (Equations (iv–vii)):

(iv)

(v)

(vi)

(vii)

Such side effects can be avoided by adjusting pH value with superior buffer solution, aiming to detach active materials from aluminium foil and hinder degradation of NMC particles. Under buffer solution control, the aluminium foil was successfully dissolved into solution while NCM particles were well-preserved.

The waste cathode materials in spent LIBs contain valuable metals, which can be recycled by a hydrometallurgical process which offers low energy consumption, environmentally friendly and excellent recovery efficiency. Based on the present analysis and summary of hydrometallurgical recycling processes, the following conclusions are drawn. The following flow is considered the most competitive process to recycle valuable metals from waste cathode materials at industrial scale: alkaline solution dissolution/calcination treatment → reductant (H₂O₂) → sulfuric acid leaching → coprecipitation → resynthesis at high temperature. The leaching capability of organic acid with reducibility is greater than that of inorganic acid leaching united with reductants. Bacterial leaching shows high selectivity for lithium, which can be selected to recycle high purity lithium-containing products. A combination of processes for recovering valuable metals may complement each other, which contributes to improve the quality of the recycled products. The DESs separation technology can achieve efficient overall recovery of valuable components from spent LIBs, which is conducive to sustainable development. The highly efficient direct-regeneration or direct-recovery of NCM materials will face huge challenges and potential. In the future, both will become research hotspots in the field of spent LIBs recovery.

In 2011 the European Commission presented “A Roadmap for Moving to a Competitive Low Carbon Economy in 2050” outlining the milestones, among them also the 83–87% CO₂ reduction of the industry sector (1, 2). Primary steel production via the blast furnace/basic oxygen furnace (BF/BOF) route or so-called integrated steel plant, is a predominant and well-established process, contributing 70.8% of the world’s 1807 million tonnes of crude steel production in 2018 (3). The reduction process of the iron ore to crude steel is linked to CO₂ emissions, resulting in 2016 for a total of 7% (160 million tonnes of CO_2eq) of EU-28’s greenhouse gas emissions (4). The energy efficiency potential of a modern integrated steel plant has already been exploited to a great extent through conventional process optimisations. It is, therefore, necessary to transfer steel production to climate-friendly processes through new and innovative approaches. Hydrogen-based direct reduction processes and electrolytic reduction methods are alternatives for the reduction of iron ore, but they require on the one hand huge amounts of renewable energy, for instance for green hydrogen production in water electrolysis, and cause on the other hand significant investment demand as the existing production infrastructure has to be replaced (5). Carbon capture and utilisation (CCU) processes are a second option which are near-term actionable, as they can be added to the existing infrastructure without a significant change in the steel production itself (6). The first step of a CCU process chain is the energy intensive separation of CO₂ from diluted exhaust or process gases. If these gases also contain carbon monoxide, as is the case in the steel industry (Table I), carbon monoxide is avoided of utilisation since the carbon capture processes selectively separate CO₂ (8). The separated CO₂ is then either biologically or catalytically converted to usable products (6).

The process gases in a steel plant, BFG, BOFG and COG, contain high shares of carbon monoxide and CO₂ (Table I). These low-calorific gases are currently utilised in an integrated steel plant as an energy carrier, i.e. in heating processes, and as fuel in the power plant. In Figure 1 the energy flows in an integrated steel plant are depicted. The main part of the BFG (white letter A in Figure 1) is directed to the enrichment process where it is mixed with BOFG (white letter B in Figure 1). The main share of the enriched gas fuels the power plant. COG (white letter C in Figure 1) is mainly used in internal processes and in the power plant as well. The power plant covers almost the total electricity demand of the steel mill. NG (white letter D in Figure 1) is used for heating in downstream processes, like in the hot strip mill, and in the power plant as well. The quantity of the process gases BFG, BOFG and COG covers up to 40% (9) of the steel plant’s energy demand, where the remaining part is provided by electrical energy and fossil fuels, like NG.

Fig. 1

The Sankey diagram of Figure 2 indicates the composition of the different byproduct gases and their internal use. It is obvious that a withdrawal of these low-calorific gases has to be compensated by the supply of other energy carriers, either synthetic natural gas (SNG) or external electricity, since the main part of the gases are used in the power plant downstream of the enrichment process. In the enrichment process, the byproduct gases are mixed and buffered in gasometers.

Fig. 2

However, due to their high carbon monoxide and CO₂ concentrations, the process gases may be conceived for further use as a carbon source for catalytic conversions. As summarised in the review from Frey et al. (10) the alternative utilisation of steel plant process gases for the production of ammonia, methanol or recovery of its derivatives has already been under examination since the early 1950s. The latest review from Uribe-Soto et al. (11) outlined three alternatives: (a) thermal use of the process gases (state-of-the-art); (b) recovery of the valuable compounds (hydrogen, methane and carbon monoxide) via different separation technologies; and (c) thermochemical synthesis to high-added value products (methanol, dimethyl ether, urea), with the focus on the latter. The consideration of their utilisation as a potential carbon source and coupling it with renewable energy within the context of power-to-X technology, has gained attention in the last years especially in Europe, resulting in various theoretical studies as well as research projects. The largest German steel producer, thyssenkrupp, is leading the “Carbon2Chem” project (12), where different scenarios for the synthesis of methanol (13, 14), ammonia or urea (15), as well as higher alcohols and polymers (16) from BFG, COG and BOFG are being investigated. In an ongoing research project the possibilities of converting BOFG and BFG into methanol and methane are explored under dynamic conditions (17, 18).

All studies referenced above utilise pure CO₂ which is separated in a first step from the process gases, and is subsequently converted with hydrogen in a catalytic synthesis. In this study, the catalytic conversion of BFG and BOFG to methane is investigated without a prior separation of CO₂. The process gases of the steel plant are only pre-cleaned upstream of the catalytic conversion by dust removal (i.e. by a venturi scrubber and a bag house filter) and separation of the sulfur compounds sulfur dioxide, carbonyl sulfide, mercaptans (i.e. in a series of two adsorbers in order to remove the catalyst poisons), see Figure 3. Consequently, the catalytic conversion is carried out with significant shares of nitrogen in the feed gas. Therefore, the following advantages arise:

Fig. 3

The aim of the present study is the assessment of different process chains for the direct utilisation of BFG and BOFG in catalytic methanation without a prior CO₂ separation. Since the conversion of CO₂ and carbon monoxide to methane requires renewable hydrogen, the hydrogen supply is ensured by a water electrolysis powered by renewable electricity (P2G plant) as well as by an additional biomass gasification plant (Figure 3). Therefore, a variety of possible implementation scenarios arise, and the following fundamental research questions have to be answered:

A withdrawal of process gases, particularly of the comparatively high calorific COG, would result in a shortage of internal energy supply in the integrated steel plant (Figure 1) which has to be substituted by NG or electric energy sourced externally. Therefore, in order to avoid significant changes of the existing steel production infrastructure, in this study COG was not considered, and BFG as well as BOFG are solely used as a carbon source for a potential utilisation process (Question 1(a)). Furthermore, it has been deliberately decided that the product gas from the methanation, nitrogen diluted SNG, substitute fossil NG currently used in the integrated steel plant, mainly for heating processes. Alternatively, it is used as reducing agent in the blast furnace, for example as substitute for pulverised coal injection (PCI). An injection into the NG grid is not possible since the required specifications are not met (Question 3). The technoeconomic and ecological questions (Questions 1(b), 2 and 4) have been treated by Rosenfeld et al. (19). Supporting laboratory experiments for biomass gasification have been published by Müller et al. (20). The focus of this study is on Questions 5 and 1(b).

Figure 3 provides an overview of the possible integration of a P2G plant (Figure 3(b)) as well as a dual fluidised biomass gasification plant (Figure 3(c)) into the integrated steel plant (Figure 3(a) in dashed lines). By integrating a P2G plant, renewable energy is used for the production of hydrogen by water electrolysis and subsequently for the catalytic methanation of the process gases BFG and BOFG. The combination with a dual fluidised biomass gasification (20–22) provides an additional biogenic hydrogen source. The biogenic CO₂ is vented to the atmosphere. Alternatively, it could be stored in a carbon capture and storage (CCS) process resulting in negative CO₂ emissions (bioenergy with carbon capture and storage (BECCS)) which is not further considered here (23). In addition, the oxygen from the water electrolysis has the potential for utilisation in steel production as well as in the biomass gasification process. The produced nitrogen diluted SNG is directly utilised in the steel plant as a substitute for NG in various processes, and PCI in the blast furnace.

To explore the integration potential, a number of different scenarios has been defined and three of them, supported by the experimental results at a laboratory catalytic methanation plant, will be presented in detail in the present work. The three chosen scenarios provide a good overview of the order of magnitude of the required renewable energy, as well as the resulting CO₂ reduction potential.

The scenarios with different integration variations were based on Austria’s biggest steel production sites. The integration of renewable energy by a P2G plant and a biomass gasification plant has been analysed by three extreme value scenarios and three constrained scenarios. The results are reported in (19). The three extreme value scenarios described a maximum utilisation of the process gases, either individually or in combination. The required hydrogen for the methanation was balanced, half from water electrolysis and half from biomass gasification. The constrained scenarios are realistic in the medium term. They are limited by the maximum plant size of the biomass gasification plant (100 MW_th), based on the current biomass fuel availability and already installed gasification capacity in Europe (21). The main cost influencing factor throughout all six scenarios is the energy supply cost, both for electricity and for biomass (19).

The aim of the aforementioned scenarios was the minimisation of, or complete substitution of, the integrated steel plant’s demand for fossil fuels like NG and PCI. The steel plant process gases (BFG and BOFG) were used as carbon source for the methanation. The three scenarios which are the basis for the considerations in this paper are:

For these three scenarios, the required amount of the renewable electricity, biomass as well as the withdrawal amount of the process gasses (BFG or BOFG) has been determined. The main evaluation criteria for all scenarios were set by the CO₂ reduction potential.

Dual fluidised bed gasification systems consist of two reactors, the gasification reactor (650°C) and the combustion reactor (900°C). In contrast to the conventional systems, the presented system uses the sorption enhanced reforming (SER) process. It allows selective transport of CO₂ between the gasification reactor and the combustion reactor, by the use of calcium oxide as bed material, resulting in a product gas with a high hydrogen (up to 75 vol%) and low CO₂ concentration. The hydrogen rich product gas of the biomass gasification substitute green hydrogen from the electrolysis, and thus reduces the demand of renewable electric power (22, 24). Additionally, when pure oxygen is used instead of air for the combustion (oxySER), an almost pure CO₂ stream can be obtained as an exhaust (flue) gas, suitable as biogenic CO₂ source (Table II). The data given in Table II are based on the gasification of wood chips. A thermal gasification power of 100 MW_th consumes 50,400 kg h^–1 wood chips from Austria as fuel, and produces 28,800 Nm³ h^–1 product gas with the composition according to Table II (21).

The experimental tests were performed at a laboratory test plant, which consists of three fixed-bed reactors (R1–R3) connected in series with the purpose of achieving a multi-stage fixed-bed methanation. A detailed description of the test plant can be found in Kirchbacher et al. (25) and Medved (26). The conversion of CO₂ and carbon monoxide was investigated for synthetic gas compositions of BFG and BOFG under different flow rates, variation of hydrogen surplus and presence of nitrogen, with the focus on achieving a complete CO_x conversion.

A commercial bulk catalyst with 20 wt% nickel load was used. The operating pressure was set to 4 bar, which coincided with the steel producer’s gas supply system. The reactor load was limited to gas hourly space velocity (GHSV) of 4000 h^–1 (GHSV = V̇_feedgas/V_catalyst) for the synthetic BFG and BOFG gas composition and added hydrogen. The temperature in the reactor was determined by multi-thermocouples (Figure 4).

Fig. 4

Seven measuring points in each reactor, five in the catalyst bed and one below and above the catalyst zone, gave an understanding of the axial temperature profile in the catalyst bed. The methanation gas composition for BFG and BOFG for the stoichiometric ratio with hydrogen according to Equations (i) and (ii) is listed in Table III.

(i)

(ii)

The experimental results obtained from the methanation of BFG and BOFG were used as support for the further analysis of the three selected scenarios. In the following, the experimental results and the scenarios are presented separately in the subsections.

5.1 Methanation

The methanation of process gases is a combination of CO₂ and carbon monoxide conversion according to Equations (i) and (ii).

A suitable parameter for the description of the stoichiometry is the ratio r_{H 2} of molar hydrogen flow and molar flows of CO and CO₂, respectively, in the feed gas given in the Equation (iii):

(iii)

r_{H 2} equals 1 for stoichiometric mixtures, r_{H 2} <1 for sub- and r_{H 2} >1 for over-stoichiometric mixtures, respectively.

Achieved CO_x conversion rates for each reactor (R1–R3), with variation of hydrogen surplus (r_{H 2} = 1; 1.02; 1.04; 1.05) with and without nitrogen for a synthetic BFG and BOFG feed gas compositions, can be seen in Figures 5 and 6. On the right y-axis, the mean reactor temperature represents the average of the measured catalyst bed temperatures, as well as the calculated heating values of the product gas in each reactor. For experiments without nitrogen in the feed gas, marked with -N₂, the H₂:CO_x ratio and the amount of the reactive gas in the experimental series remained the same, meaning that the GHSV was reduced to 3260–3280 h^–1 for BFG and 3680–3690 h^–1 for BOFG due to the absent inert gas flow.

Fig. 5

Methanation of BFG with and without nitrogen and hydrogen-surplus variation

Fig. 6

Methanation of BOFG with and without nitrogen and hydrogen-surplus variation

5.1.1 Methanation of Blast Furnace Gas

Complete CO_x conversions are achieved downstream of the third reactor with an over-stoichiometric ratio of 1.05, both with and without the nitrogen in the feed gas (Figure 5). The mean reactor temperatures are approximately 50°C lower with nitrogen present, which is a result of the additional heat capacity of the inert gas. Despite these lower temperatures, approximately 4% better conversions are reached in R1 for all ratios in the absence of nitrogen. The withdrawal of nitrogen from the feed gas resulted in lower GHSV, consequently prolonging the residence time in the reactor leading to slightly better CO_x conversions. The temperature decrease in R2 and R3 was expected, since the majority of the reactive gas converted in R1, resulting in lower release of the exothermic reaction heat. Therefore, nitrogen in the feed gas only has a significant influence on the heating value of the product gas. In the case of the product gas (R3) with nitrogen the heating values vary from 19.4–19.8 MJ m^–3 (r_{H 2} = 1.05–1), whereas without nitrogen the values almost double (36.0–37.9 MJ m^–3). Although with the higher hydrogen surplus better conversions are achieved, the unconverted hydrogen decreases the heating value of the product gas, due to its lower volumetric heating value compared to methane.

5.1.2 Methanation of Basic Oxygen Furnace Gas

As for BFG, similar test series were conducted for the methanation of BOFG. As shown in Figure 6, on account of lower nitrogen share in the feed gas (8.2%), no noticeable effect on the temperature and consequently conversion can be recognised. Furthermore, a complete CO_x conversion at 4% hydrogen surplus is achieved with or without nitrogen in the feed gas. When comparing the mean reactor temperatures and CO_x conversion in R1 of BOFG with the BFG test series, temperatures are 50–100°C higher and conversions 5–10% lower, respectively. This can be attributed to the higher carbon monoxide share in BOFG, resulting in higher reaction heat release. Therefore, the conversion in the first reactor (R1) is clearly thermodynamically limited. Since its lower share in BOFG compared to BFG, the influence of nitrogen on the heating value of the product gas is lower, and values vary from 27.2–28.8 MJ m^–3 (r_H2 = 1.05–1) with nitrogen and between 34.9–37.7 MJ m^–3 (r_H2 = 1.05–1) without nitrogen.

The product gas composition downstream of the methanation is given in Table IV. A complete conversion is achieved at 5% hydrogen surplus for BFG and at 4% hydrogen surplus for BOFG, where the unconverted hydrogen is a result of its over-stoichiometric addition.

Table IV

Product Gas Composition for the Methanation of BFG and BOFG

	Product gas molar fraction
	CH4	CO2	CO	N2	H2
BFG (rH2 = 1.05)	0.446	0	0	0.434	0.120
BOFG (rH2 = 1.04)	0.679	0	0	0.215	0.106

5.2 Results for the Selected Scenarios

In this study, three different scenarios for the implementation of a P2G plant and a biomass gasification in an integrated steel plant have been investigated. The aim was the quantification of the CO₂ emission reduction potential of steel production, avoiding significant modifications in the existing steel plant infrastructure. Furthermore, a carbon capture step shall be avoided as well, in order to improve the efficiency of the CCU process chain, resulting in a catalytic conversion of BFG and BOFG to methane in the presence of nitrogen.

Basic evaluation of the three chosen scenarios confirmed the possibility of CO₂ emission reductions between 0.81 and 4.6 million tonnes CO_2eq per year without considerable interference with existing steel production. The required plant sizes and the necessary fuel demand (renewable power and biomass, respectively) substantially exceed the current realistic possibilities of a P2G plant (electrolyser power 784–2877 MW_el) as well of a biomass gasification (100–3162 MW_th). Even for the scenarios realistic in the medium term, the amount of required renewable electricity beyond 700 MW_el cannot be provided in the foreseeable future. This underscores the need for new technologies for the production of CO₂-free hydrogen.

Experimental tests have shown that the methanation of BFG and BOFG is technically possible without separating the inert gas nitrogen, and thus saving the energy intensive carbon capture unit with the additional benefit of carbon monoxide utilisation contained in the process gases from the steel production. A complete conversion of CO_x was achieved with a 4–5% hydrogen surplus for both process gases, BFG and BOFG, with and without nitrogen, with three-stage methanation. The lower heating value enrichment of the unrefined BFG (up to 19.8 MJ m^–3) and BOFG (up to 28.8 MJ m^–3) via methanation without the necessity of nitrogen removal as lean product gas showed a utilisation potential in the integrated steel plant as a substitute for NG and PCI.

The first evaluation presented here provides a good overview on the order of magnitude of required renewable energy and biomass for the transition of the integrated steel plant towards renewable gas supply by adding a CCU process chain. Additionally, particularly for the utilisation of the product gases of catalytic methanation within the steel plant, intricate CO₂ separation is not required as has been shown by the experimental investigations.

TiO₂ nanoparticles were successfully synthesised by a simple sol-gel method (37) using Ti[OCH(CH₃)₂]_4, generally referred to as titanium tetra-isopropoxide (TTIP), as a precursor purchased from Sigma-Aldrich Company (USA) with purity of 97%. Titanium(IV) isopropoxide was dropped slowly into the mixed solution of distilled water and ethanol in the ratios of 1:4:1 (TTIP: water: ethanol). The solution was stirred continuously for 1 h at room temperature to obtain a white slurry. HNO₃ was used to adjust pH value in the range 2–3. The white slurry mixture was dried at 120°C for 3 h on a hot plate; the dried powder was sintered at 450°C for 3 h. Finally, we obtained the required TiO₂ nanoparticles. The flow chart of synthesis of TiO₂ nanoparticles is given in Figure 1.

Fig. 1

The synthesised sample of TiO₂ nanoparticles were analysed with XRD pattern using a SmartLab^® X-ray diffractometer (Rigaku Corporation, Japan) (with λ = 1.5406 Å CuK_α radiation) operating at 40 kV, 30 mA and at room temperature. The XRD patterns were used to determine the crystallite size, lattice parameter and phase identification. The structural and morphological analysis of TiO₂ nanoparticles were done by HR-TEM and the selected area electron diffraction (SAED) pattern using the model Tecnai^TM G² F30 field emission gun transmission electron microscope (FEI Company, USA) operating at 200 kV accelerating voltage with resolution point:0.17 Angstrom line:1.24 Å and magnification 1500 LM to 520 kx. Tescan MAIA3 field emission scanning electron microscope (Tescan, Czech Republic) operating at 12.0 kV and magnification 21.4 Kx was used for SEM-EDX analysis of the morphology and average particle size of the TiO₂ nanoparticles. The UV-vis absorption spectrum was recorded using Shimadzu UV-2330 spectrometer (Shimadzu Corporation, Japan) in the range 200–700 nm. The UV-vis spectrum was used to determine direct energy band gap of the TiO₂ nanoparticles.

TiO₂-ethylene glycol nanofluids were prepared at different concentrations, 0.2 wt%, 0.5 wt% and 1.0 wt% of TiO₂ nanoparticles. When TiO₂ nanoparticles are added to the ethylene glycol base fluid, the nanoparticles produce a sediment within a few minutes because they remain in clusters without being dispersed. For the uniform dispersion of nanoparticles in the base fluid, we used an ultrasonic homogeniser VC 505 (Sonics & Materials Inc, USA) working at 20–40 kHz, 500 W.

The crystal phases of the synthesised TiO₂ nanoparticles were determined by XRD patterns as shown in Figure 2. The obtained peaks in the diffraction pattern are identified with the JCPDS Card No. 88-1175. The interplanar spacing has been calculated using Equation (i):

(i)

where λ represents the wavelength of CuK_α (1.5406 Å) radiation, θ is the angle between incident beam and the reflection lattice planes and n = 1 is the order of the XRD spectra. The highest peak is observed at 2θ = 25.4° which was indicated to plane (101) and d spacing corresponding to this peak is 3.12 Å. The other peaks in XRD pattern are observed at 2θ = 27.6°, 37.9°, 48.2°, 54.1°, 55.1°, 62.8°, 69°, 70.4°, 75.1° and 82.8° correspond to the (110), (004), (200), (105), (211), (002), (116), (112), (215) and (312) planes of TiO₂ nanoparticles and d spacing are calculated as 2.83 Å, 2.43 Å, 1.88 Å, 1.69 Å, 1.66 Å, 1.47 Å, 1.35 Å, 1.33 Å, 1.26 Å and 1.16 Å, respectively. The intensity of the obtained peaks indicates the well-formed crystalline nature of the sample. The average crystallite size has been computed with Scherrer’s equation (Equation (ii)) (38):

(ii)

where β_hkl represents the full width at half maxima (FWHM) and K is the Scherrer constant. From this formula, the calculated average crystallite size of the given sample is approximately ~23 nm.

Fig. 2

The TEM image of a crystalline sample is shown in Figure 3(a). The average particle size of the TiO₂ nanoparticles ranged from 20–26 nm as shown in the histogram (Figure 3(b)). The SAED pattern in Figure 3(c) shows principally 10 rings which are ascribed to (101), (110), (103), (004), (111), (200), (105), (211), (002) and (116) planes, respectively. These planes are consistent with the XRD results. The d spacings are in agreement with the tetragonal structure of TiO₂ nanoparticles (JCPDS Card No. 88-1175). For the structural analysis TiO₂ nanoparticles were also examined by HR-TEM as shown in Figure 3(d). The crystalline nature of the nanoparticles is visible in the HR-TEM micrograph. The lattice spacing 0.31 nm and 0.28 nm corresponds to (101) and (110) planes respectively. The size and morphology of the TiO₂ nanoparticles were also determined using SEM. Figure 4 shows typical SEM images of TiO₂ nanoparticles. The SEM image shows random distribution of TiO₂ nanoparticles having sizes in the range 18–26 nm. In Figure 4, there is a soft agglomeration of the nanoparticles: isolated particles are connected to each other by attractive physical interactions like Van der Waals force. The agglomeration of nanoparticles in the base fluid probably affects the thermal conductivity performance of the nanofluids. Agglomeration of nanoparticles affects the Brownian motion of the nanoparticles resulting in a decrease in thermal performance of the nanofluids. To remove agglomerations of nanoparticles in the base fluid, a sonication process has been used to break the intermolecular interactions. The EDX spectrum (Figure 5) of the TiO₂ nanoparticles provides information about the constituent components of our sample, which contains titanium and oxygen. The high intensity peaks for titanium and oxygen justifies that the sample contains mainly TiO₂.

Fig. 3

Fig. 4

Fig. 5

The UV-vis absorption spectrum at room temperature of TiO₂ nanoparticles has been recorded in the wavelength range 200–700 nm and is shown in Figure 6(a). It is obvious from the UV-vis absorption spectrum that the peak observed at 315 nm represents a blue shift compared with its bulk counterpart. This indicates that the particle size of the TiO₂ nanoparticles has been reduced (38–40). The optical absorption of the TiO₂ nanoparticles is analysed by Equation (iii):

(iii)

where E_g represents the optical band gap of nanoparticles, B is a constant, α is the optical absorption coefficient of the nanoparticles. The exponent m depends on the nature of the transition, m = 1/2, 2, 3/2, 3 for allowed direct, allowed indirect, forbidden direct and forbidden indirect transitions respectively. Figure 6(b) shows the Tauc plot of TiO₂ nanoparticles, a satisfactory fit is obtained for (αhν)² vs. hν indicating the presence of a direct band gap. The optical energy gap of the TiO₂ nanoparticles has been determined as 3.28 eV by extrapolating the linear portion of this plot at (αhν)² = 0.

Fig. 6

The thermal conductivity of the nanofluids was measured by using a Hot Disk TPS-500 S thermal constant analyser. The Hot Disk TPS-500 S is the newest transient plane source (TPS) thermal constants analyser. The TPS technique has been used to determine the thermal conductivity of a nanofluid. The temperature dependent thermal conductivity of the TiO₂-ethylene glycol nanofluids is plotted in Figure 7(a) at 0.2 wt%, 0.5 wt% and 1.0 wt%. The results show that the thermal conductivity of TiO₂-ethylene glycol nanofluids increases with concentration of TiO₂ nanoparticles. The thermal conductivity exhibits a slow increase for 0.2 wt% nanofluids while it shows relatively fast increase for 0.5 wt% and 1.0 wt% nanofluid in the temperature range 20–80°C. At 20°C, the value of thermal conductivity of pure ethylene glycol is 0.285 W mK⁻¹ and it has been increased to 0.314 W mK⁻¹ for 1.0 wt% concentration of TiO₂ nanoparticles in ethylene glycol base fluid. The expression of TCE is given by Equation (iv) (41):

(iv)

where TC_nf and TC_bf are the thermal conductivity of nanofluid and base fluid respectively.

Fig. 7

A number of investigators have developed models for determining the thermal conductivity of nanofluids containing spherical particles. They only consider the effect of volume fraction of the particles. However the thermal conductivity of nanofluids depends on various factors such as size, shape, volume fraction of the suspended particles as well as temperature of suspensions. A few models also propose that the TCE is due to the ordered layering of liquid molecules near the solid particles (42, 43).

In addition to describing the TCE in nanofluids, we consider the effect of three possible mechanisms for heat transfer in nanofluids: (a) translational Brownian motion, (b) the existence of an interparticle potential and (c) convection in the liquid due to the Brownian movement. In the low temperature region, the mean free path due to the collision of nanoparticles increases and leads to TCE due to Brownian particle (K_Brownian) as given as Equation (v):

(v)

where ϕ is the volume fraction, C_N is the heat capacity per unit volume of the nanoparticles, l is the mean free path and V_N is root mean square velocity of the particles.

This model explains the individual effect of temperature on the TCE in nanofluids with the help of Brownian motion but does not consider the effect of surface functionality and particle loading of nanoparticles. To overcome the shortcomings of this model, Prasher et al. (44) presents an order-of-magnitude justification to show a local convection effect caused by the Brownian movement of the nanoparticles. Based on the Brownian motion induced convection effect from multiple nanoparticles, the model of Prasher et al. for the TCE ratio of a nanofluid is given in Equation (vi):

(vi)

where K is the thermal conductivity of nanofluids, K_f is the thermal conductivity of fluids, A and m are the best fit constants, and should be same for different experimental data for a particular fluid. R_e and P_r are Reynolds and Prandtl numbers respectively (Equation (vii)):

(vii)

where d_N is the particle diameter, R_b is the interfacial resistance (Equation (viii)):

(viii)

The Reynolds number (R_e) is based on the root-mean-square velocity (ν_N) of a Brownian particle defined as Equation (ix) (45, 46):

(ix)

where ρ_N is the density of the particles, k_b is the Boltzmann constant and T is the temperature in Kelvin scale.

Figure 7(b) shows the variation of the TCE with temperature ranging from 20–80°C. It is clear from Figure 7(b) that the enhancement in thermal conductivity of TiO₂-ethylene glycol nanofluids is achieved with increasing concentrations of nanoparticles and temperatures. At 20°C, we observed 3.3% to 6.5% and 11.2% TCE on 0.2 wt%, 0.5 wt% and 1.0 wt%, and at 80°C, the TCE becomes 9.9%, 18.3% and 23.8% for 0.2 wt%, 0.5 wt% and 1.0 wt% respectively for TiO₂-ethylene glycol nanofluids. This enhancement is due to better uniformity and stability of suspensions. It has been found that ultrasonication increases the stability and uniformity of the nanofluids. The achieved values of TCE are higher than any of the results reported previously for TiO₂-ethylene glycol or TiO₂-water based nanofluids (13, 14, 30, 31) at such small concentrations. In preparation of the nanofluids, we used very small amounts of nanoparticles, so the fluidic properties of the liquid are almost unaffected, allowing for the easy flow of liquids and better transfer of heat. As the temperature increases, the TCE in the TiO₂-ethylene glycol nanofluids may be attributed to Brownian motion of nanoparticles. It is obvious from Equation (ix) that the root-mean-square velocity (ν_N) of a Brownian particle depends upon particle diameter. If the particle diameter is small, root-mean-square velocity of a Brownian particle is large. Since the synthesised nanoparticles are small in diameter (approximately 22 nm) this results in the increase of Brownian motion, causing convection which in turn increases the thermal conductivity of the nanofluids. The high TCEs are probably due to the small size of nanoparticles because as the particle size decreases, the surface-to-volume ratio of particles increases, which can lead to enhanced thermal conductivity of nanofluids.

The ultrasonic velocity in nanofluids was measured using an ultrasonic interferometer (model nanofluid-10X, Mittal Enterprises, India) at 3 MHz frequency in temperature range 20–80°C. The measured ultrasonic velocity in ethylene glycol matrix and three nanofluids samples containing 0.2 wt%, 0.5 wt% and 1.0 wt% of TiO₂ in temperature range 20–80°C are shown in Figure 8. It is obvious from Figure 8 that the ultrasonic velocity in the nanofluids increases with the temperature. The plot also indicates that the ultrasonic velocity in the nanofluids is larger than that of pure ethylene glycol matrix (1410 m s⁻¹) at 20°C and the velocity increases with the particle concentration (1430 m s⁻¹) for 1.0 wt% loading at the same temperature of 20°C.

Fig. 8

If we consider (ρ_m,ρ_s) and (k_m,k_s) are the density and the compressibility of fluid and suspended particles respectively, B and ϕ are the bulk modulus and the particle volume fraction; then the effective density (ρ_eff) and compressibility (k_eff) of the suspension becomes as Equation (x) (47–49):

(x)

The ultrasonic velocity (V) in a medium is given by Equation (xi):

(xi)

where B, ρ and k represent the bulk modulus, density and compressibility of the medium respectively. λ and μ are the material dependent quantities known as Lamé moduli or Lamé coefficients. The compressibility and density of a fluid medium are changed by the dispersion of nanoparticles and are the function of the particle volume fraction. From Equation (x), it is clear that the evaluation of the effective bulk modulus and compressibility of the suspension is performed with calculation of effective Lamé moduli, which depends on particle volume fraction of suspended particles.

It is obvious from Equations (x) and (xi) that the bulk modulus and change in density of the nanoparticles suspension as a function of volume fraction causes an enhancement in the ultrasonic velocity. An increase in the wave velocity with increase in the particle concentration of given nanofluids indicates that there is positive change in the bulk modulus and density of the nanofluids. It may be predicted that the comparative change in the density with respect to bulk modulus is small. As the particle concentration in nanofluids increases, the compressibility of the given matrix decreases. A strong cohesive interaction occurs among the molecules after dispersion of TiO₂ nanoparticles in the ethylene glycol matrix. Thus for the TiO₂ nanofluids, the ultrasonic velocities are larger in comparison to the ethylene glycol matrix and increase with the nanoparticle concentration.

In the low frequency region, the velocity in nanofluids is independent of particle size (49, 50). Here all the nanofluids have been prepared with nanoparticles fabricated at low evaporation rate and velocity of the ultrasonic wave is measured at different temperatures and low frequency (3 MHz). Thus it was concluded that the temperature dependent velocity at low frequency in the nanofluids depends only on the particle concentration. At low frequency, the ultrasonic velocity in a nanofluid is a quadratic function of temperature (Equation (xii) (51):

(xii)

where V₀ is the ultrasonic velocity at 0°C, V₁ and V₂ are the absolute temperature coefficients of velocity and T is the temperature difference between experimental and initial temperature (0°C). The first and second terms in Equation (xii) are in good agreement for a simple liquid system, but the third nonlinear term is caused by non-linear change in bulk modulus and density of the nanofluid system with temperature.

The acoustic particle sizer APS-100 (Matec Applied Sciences, USA) was used to examine the PSD in the nanofluids. The APS-100 works on Epstein and Carhart theory (52) and is mainly based on the ultrasonic spectroscopic method. The APS-100 computes the sound attenuation (dB) per unit length (cm) over the 1–100 MHz frequency range in particle-liquid suspensions with high precision. This attenuation spectrum can be converted to PSD data. According to Epstein and Carhart theory (52), the attenuation of the ultrasonic wave in a nanofluid can be understood with the understanding of the thermal wave length (; K_S, ρ_S and C_S: thermal conductivity, density and specific heat of the dispersed particle: ω ; frequency of the wave) and the viscous wave length (; η: viscosity of the matrix). When the viscous wave length is comparable to particle radius (r), the viscous loss is a prominent cause behind the ultrasonic attenuation; while the viscous drag, scattering and thermal losses are effective when the thermal wave length λ_T ≈ r. The expressions for the ordinary viscous dissipation (α_V), the viscous drag loss (α_VD) (47, 50) of the sound waves are given as Equation (xiii) and Equation (xiv):

(xiii)

(xiv)

where η_d and η_V represent the dynamic and the volume viscosities of the nanofluid, k̅ is the wave number, . Biwa (53) calculated the change in the ultrasonic attenuation with respect to volume fraction caused by scattering at microscale in low frequency limit. The expression to compute the ultrasonic attenuation is given as Equation (xv) (53):

(xv)

where γ^sca represents the scattering cross-section which depends on the frequency of the ultrasonic wave, particle size, bulk modulus and density of the base/carrier fluid and suspended particles. The thermal attenuation is caused by temperature variation produced by propagation of the sound waves in different components of suspension. The thermal loss mainly depends on the frequency and particle size. The particle size has been obtained by APS-100 in range of 19 nm to 24 nm as visualised in Figure 9. It has been confirmed from Figures 3(a) and 9 that the PSD obtained by APS-100 is in good agreement with that obtained by the TEM micrograph. Ultrasonic spectroscopy is sensitive to particles with radius between about 10 nm to 1000 mm. The maximum particle concentration which can be analysed varies between about 1 wt% to 50 wt% depending on the nature of the system. On the other hand, the technique is unsuitable for analysing dilute suspensions i.e., particle concentrations below about 1 wt%. In the present study (Figure 9) the weight percentage of TiO₂ is 1 wt%. Systems with different weight percentages of TiO₂ show the same PSD because nanoparticles are dispersed in base fluid with the same technique and the same ultrasonication time.

Fig. 9

Taking into account that more than 99.4% of the diesel vehicles currently in China are compliant with Euro III–V, three typical LDDTs compliant with Euro III, Euro IV and Euro V, respectively, were selected from the market and their specifications are provided in Table I. These trucks have similar dimensions and powers, and their biggest difference is their aftertreatment technology. To eliminate the impact of fuel quality, all the diesel fuel used in the study was from a specified filling station, conforming to the China VI standard.

The test route was designed to simulate the real driving conditions of most diesel trucks in Zhengzhou, Henan province. The total length of the test route was approximately 68 km, including 14 km of urban roads, 18 km of connection roads and 36 km of highway. VOCs were sampled only when the trucks travelled on the urban and highway roads and cold start emissions of VOCs were not included during the whole test. Table II shows the driving condition parameters during each road type. The average speeds on urban and highway roads were 18.1–20.8 km h⁻¹ and 72.8–76.5 km h⁻¹, respectively. Driving conditions on urban roads are more aggressive than those on highway roads. The average accelerations on urban and highway roads were 0.22–0.26 m s⁻² and 0.10–0.13 m s⁻², respectively. During the measurement, the trucks were not in service and the load of each truck was approximately 500 kg during the experiment, containing the PEMS equipment, four batteries, two testers and one driver.

Under real driving conditions, some gaseous emissions may transform to secondary fine particles when the exhaust is cooled or diluted with the ambient atmosphere. Thus, VOC emissions might be overestimated if sampled directly from the vehicle exhaust because the temperature is very high. Therefore, a combined PEMS (Sensors Inc, USA) was employed to sample the exhaust VOC emissions. The schematic diagram of the emission testing and sampling system is shown in Figure 1.

Fig. 1

The microproportional sample system (MPS), a partial flow dilution system, was used to dilute and cool the exhaust from tailpipe. After the MPS, the gas temperature decreased from about 120ºC to about 40ºC. Two 3.2 L SUMMA^® canisters (Entech Instruments Inc, USA) were used to sample the VOCs during each test trip, one for the urban roads and the other for the highway roads. VOC emissions during the connection roads section were not sampled because the actual running speed could not meet the requirement due to unexpected road repairing. The sampling flow rate was controlled by a passive restrict valve at 0.1 L min⁻¹. Teflon^TM tubes were used to connect the canister and PEMS system to minimise the adsorption of VOCs. A laptop was used to control the system and collect data from the test module. It should be noted that these trucks were driven by their owners throughout the test to ensure these trucks were running under ordinary working conditions and each vehicle was tested twice to enhance the reliability of the results.

Analysis of the VOCs was carried out following the United States Environmental Protection Agency (US EPA) TO-15 method by a gas chromatography-mass selective detector (GC-MSD) (22). Samples collected in the SUMMA^® canister were preconcentrated using an 8900DS preconcentrator (Nutech Instruments Inc, USA) with three cold traps and a canister autosampler (Nutech Instruments Inc, USA, mode 3600DS). The moisture, CO₂ and methane would be removed through the traps. Then the concentration of the individual VOCs in the samples was determined by a GC-MSD system (7890A GC with a 5975 MSD, Agilent Technologies Inc, USA). Separation of the VOCs was achieved through a capillary column (60 mm × 0.25 mm internal diameter, 1.4 μm film thickness, DB-624 column, Agilent Technologies Inc). During sampling and analysis, strict quality assurance and quality control procedures were conducted to assure the data quality (22). The detection limits of the target non-methane hydrocarbons ranged from 7 parts per trillion by volume (pptv) to 141 pptv and the accuracy of the measurements was about 1–10%. Detailed description of the analysis procedures can be found in our previous study (23).

A total of 102 VOC species were identified and quantified, including 29 alkanes, 35 halocarbons, 17 aromatics, nine alkenes, five carbonyls and seven other compounds, which are presented in Table III. Due to the detection limitation of GC-MSD used in this study, some species (ethane, ethylene, propylene, acetylene, formaldehyde) were not detected and included.

EF per kilometre of a certain pollutant was calculated with the corresponding concentration, total exhaust volume and running distance during the test process. Prior to calculation, the results of the VOC measurements were time-aggregated. The total exhaust volumes in various driving conditions were the integration of the instantaneous exhaust flow rates, and the same for the total running distance. The EF of compound i was calculated as Equations (i)–(iii):

(i)

(ii)

(iii)

where V (m³) is the total exhaust volume of the sampling process; V_ins (m³ s⁻¹) is the instantaneous exhaust flow rate; DR_ins is the instantaneous dilution ratio of MPS; S (km) is the distance that the test vehicle travelled during the sample period; S_j is the travel distance at j second, which is equal to the value of instantaneous speed at time j recorded by the global positioning system (m s⁻¹); EF_i (mg km⁻¹) is the EF of compound i; C_i (parts per billion by volume) is the concentration of compound i; M_i (g mol⁻¹) is the molar mass of compound i; and V_m (l mol⁻¹) is the molar volume of compound i. The volumes and concentration data were all normalised to the standard ambient temperature and pressure condition (273.15 K, 101.33 kPa). The total EFs of the VOCs in a certain driving mode were summed by the individual VOC EFs in the driving mode.

The OFP refers to the amount of ozone generated by VOCs per unit mass (mg O₃ mg⁻¹ VOCs), which can reflect the ozone formation capacity of VOC species. In most cases, ratios of VOCs to NOx from the diluted exhaust were much higher than 20 in this study, which illustrated VOCs had the greater effect on the ozone formation (24). Therefore, the MIR scenarios developed by Cater (25) was applicable to evaluate the OFP of VOC species here. The OFP of a certain VOC is calculated according to Equation (iv) (26, 27):

(iv)

where OFP_i (mg O₃ km⁻¹) is the ozone formation of compound i; and MIR_i (mg O₃ mg⁻¹ VOCs) is the maximum incremental reactive of compound i obtained from Cater (25, 28). The total OFPs of a certain driving mode were summed by the individual VOC OFPs of the driving mode.

Figure 2 presents the EFs of regulated gaseous pollutants of three LDDTs compliant with different standards. Obviously, NOx, CO and HC emissions from LDDT-3 (Euro V) were the lowest and those from LDDT-1 (Euro III) were the highest, except for CO. In general, updated emission standards had a great effect on the reduction of regulated gaseous emissions. This is mainly because the three trucks adopted different aftertreatment technologies to meet different emission standards (29). For example, both selective catalytic reduction (SCR) and diesel oxidation catalyst (DOC) were utilised by LDDT-3 to be compliant with Euro V standards. SCR was often used to purify the NOx emissions and the DOC device could oxidise the CO and HC emissions efficiently (30–32). It is not difficult to understand why LDDT-1 produced the worst emissions because there is no aftertreatment requirement for Euro III trucks in most of China.

Fig. 2

As shown in Figure 2, NOx, CO and HC emissions under urban conditions were significantly higher than those under highway conditions. To be specific, NOx, CO and HC emissions under urban conditions were 1.3–1.8 times, 1.4–2.2 times and 2.5–4.1 times those under highway conditions. This phenomenon could be explained by the fact that the combustion quality in the engine was associated with the operation speed and frequent acceleration and deceleration (18, 33, 34). During this experiment, no traffic signals were encountered on the highway and the average speed was up to 73.8 km h⁻¹. However, there were 26 traffic signals on the urban roads and the average speed was only 19.4 km h⁻¹. In this operating condition, the combustion was insufficient and the temperature of aftertreatments might not be high enough for proper function, which caused the emissions to deteriorate.

Average weight percentage of individual VOC species of the entire trip was calculated based on the test trucks. On the whole, alkanes were the dominant group, accounting for 65.5 ± 10.3% of the total VOCs, followed by aromatics, carbonyls and alkenes, taking up 19.6 ± 5.0%, 5.4 ± 1.9% and 4.4 ± 1.8%, respectively. Additionally, though 35 halocarbons were quantified, they only took up 3.6 ± 1.5% of the VOCs. Thus, the following discussions on the VOCs are mainly focused on alkanes, aromatics, alkenes and carbonyls.

Weight percentages of the top 15 VOC species from the exhaust are presented in Table IV. These species accounted for approximately 83.4% of the total VOCs. Dodecane, n-undecane, naphthalene, n-decane and acetone were the major species, and their total weight percentages were over 80.1%. These results are partially consistent with the results obtained by Wang et al. (14), who indicated that n-decane, n-undecane and n-dodecane were the most abundant species. However, a study by Yao et al. (20) showed that carbonyls were the top group, which could account for 42.7–69.2% of the total VOCs. The difference was mainly attributed to the different VOC species quantified between the two studies. For example, Yao et al. (20) reported formaldehyde and acetaldehyde took up 47.9% and 21.0% of carbonyls, while these two species were not detected in this study.

The mean EFs and weight percentages for each VOC group for the entire trip of the three test trucks are plotted in Figure 3. The total VOC EFs of LDDT-1 (Euro III), LDDT-2 (Euro IV) and LDDT-3 (Euro V) were 186.9 ± 34.9 mg km⁻¹, 106.5 ± 26.2 mg km⁻¹ and 61.1 ± 16.9 mg km⁻¹, respectively. In other words, the VOC emissions decreased significantly as the standards tightened gradually from Euro III to Euro V. Most of the other species also showed a decreasing trend. Especially, dodecane and n-undecane presented the most significant decline, from 85.2 ± 3.7 mg km⁻¹ and 38.6 ± 11.7 mg km⁻¹ for Euro III to 16.7 ± 2.8 mg km⁻¹ and 9.7 ± 3.0 mg km⁻¹ for Euro V, respectively. The trend was partially consistent with that found by Zhang et al. (10), though the VOC EFs were a little higher than those in this work. This might be mainly attributed to the fact that Zhang et al. (10) employed tunnel measurement, which included evaporative emissions.

Fig. 3

Most VOC groups presented similar variation trends as the emission standards changed, especially for the dominant groups. For example, both alkane and aromatic emissions decreased noticeably as the standards varied from Euro III to Euro V. The progress in engine technology and application of aftertreatment devices played a major role in the subtraction of VOCs emissions. Additionally, there were no significant differences between emissions of carbonyls, alkenes and halocarbons from LDDT-1 (Euro III) and LDDT-2 (Euro IV), but they were much higher than those of LDDT-3 (Euro V). No coherent order was observed for other emissions among these diesel trucks, possibly because the absolute values of these species were too small to quantify accurately. On the whole, implementing stringent emissions standards could reduce most of the VOC species effectively in the freight transportation sector.

Figure 3 indicates that alkanes were the dominant group in tailpipe VOCs emissions from the test LDDTs, accounting for 57.2–80.0%, followed by aromatics (12.5–22.9%), carbonyls (3.1–7.7%) and alkenes (2.2–6.5%). This result was consistent with that observed by Wang et al. (14) (carbonyls < aromatics < alkanes) but inconsistent with that by Yao et al. (20) (alkenes < aromatics < alkanes < carbonyls). Discrepancy of the quantified VOC species was the main cause of the inconsistency. It can also be found that the proportion of alkanes decreased significantly, from 80.01% for LDDT-1 to 57.15% and 60.41% for LDDT-2 and LDDT-3, respectively. Additionally, LDDT-2 and LDDT-3 had similar VOC group distributions, while the aromatics weight percentage of LDDT-2 was significantly related to that of LDDT-3. This is probably due to the different aftertreatment used in LDDT-2 and LDDT-3 (as shown in Table III). Jung et al. (35) also observed that heavy-duty trucks equipped with DPF emitted higher quantities of aromatics compared with those with SCR.

Figure 4 shows the EFs of the top 15 VOC species from the exhaust of LDDTs. The EF of dodecane for LDDT-3 (Euro V) was 51.0% and for LDDT‐2 (Euro IV) it was only 19.6% relative to LDDT‐1 (Euro III). For several other species, LDDT-3 had the lowest EFs, while the EFs of LDDT-2 and LDDT-1 were comparable or even higher, such as naphthalene, acetone, 2-propenal. A hypothesis is that much higher temperatures and more oxidising conditions during the DPF regeneration process favour carbonyl formation (36). However, there is no direct evidence that DPF regeneration occurred. Additionally, there were several individual species whose emissions were not affected by the emission standards. Overall, most of the top 15 VOC species presented a decreasing trend as the emission standards tightened.

Fig. 4

Figure 5 shows several VOC group emissions from the exhaust of LDDTs under urban and highway driving conditions, respectively. It can be seen that VOC emissions on highway roads were much lower than those on urban roads. EFs of each VOC group decreased significantly, especially for alkanes and aromatics. Specifically, EFs of alkanes under highway conditions were only 20.4–46.2% of those under urban conditions, which was mainly attributed to the sharp decline of the most abundant alkane species, such as dodecane, n-undecane and n- ecane. For aromatics, the significant reduction of the EFs during highway driving could be attributed to the sharp reductions of naphthalene, 1,2,3-trimethylbenzene and 1,2,4-trimethylbenzene. Lower average speed and more acceleration and declaration were found during the urban road episodes, causing more incomplete combustion on non-highway road driving, resulting in higher VOCs emissions than on highways (37). Caplain et al. (38) also reported that tailpipe emissions in urban driving cycles were approximately four times those in motorway driving cycles. In addition, the reduction degrees of VOC EFs (urban vs. highway) for LDDT-3 were highest while those for LDDT-2 were lowest. This discrepancy is mainly due to the different aftertreatment devices used. For instance, optimum conditions of a DOC + SCR system used for LDDT-3 could be maintained under highway conditions because of the high exhaust temperature, resulting in more efficient reduction.

Fig. 5

A breakdown of the C1–C12 VOCs for different driving conditions of the tested trucks is presented in Figure 6. There was no obviously consistent trend in the carbon number distribution of the VOC species between highway and urban road conditions except for C3 and C11, which showed a decreasing trend when driven on the highway compared to urban roads. This phenomenon illustrated that driving conditions had a weak correlation with carbon number distribution. On the whole, the carbon number of the VOCs was concentrated in C3–C4 and C10–C12, showing a distinct ‘double peak’ phenomenon. Lu et al. (39) summarised several previous studies and reached a similar conclusion. VOCs are expected to be a mixture of unburned and partially burned fuel species (40). Propane and acetone are the dominant species in C3–C4 group, and this portion of the VOCs is likely generated as a result of the high efficiency of the diesel engine. For the C10–C12 group, these species are considered to be components of diesel fuel. Durbin et al. (41) reported the C1–C3 species contributed most to non-methane organic gases (NMOG) and ethene, ethyne, acetaldehyde and formaldehyde made the largest contribution. The differences may be attributed to the VOCs species detected between these two studies.

Fig. 6

According to the EFs of each VOC species, OFPs based on the travelled distance were calculated and the results are plotted in Figure 7. As expected, the magnitude of OFP based on emission rate presented a decreasing trend. To be specific, LDDT‐1 and LDDT-2 had the higher OFPs, approximately 239.6 ± 57.3 mg O₃ km⁻¹ and 227.7 ± 69.2 mg O₃ km⁻¹, respectively, and that for LDDT-3 was 124.8 ± 47.6 mg O₃ km⁻¹. The OFP values in this work were lower but comparable to those for diesel trucks in some studies (20, 37, 42). The lower OFP values in this study were mainly because DOC and SCR dramatically reduced VOCs emission. Additionally, engine technologies, driving cycles and fuel quality were also important factors.

Fig. 7

The chemical structure of OFPs was different from the trend of VOCs emissions based on distance travelled, shown in Figure 3. Aromatics were the primary contributor to OFP, accounting for 49.3–57.6% of the OFPs. It was noteworthy that although alkenes accounted for only approximately 5.0% of the VOC emissions, the OFP contribution of alkenes (13.4–22.3%) was comparable with that of alkanes (13.7–27.9%), which was attributed to the higher MIR scales of alkenes related to alkanes. Similar conclusions have been reached in previous studies. Therefore, priority measures should be taken to reduce the VOCs with high MIR values, such as aromatics and alkenes, to control the formation of ozone originated from diesel exhaust.

The top 20 VOC species ranked by their OFP are given in Figure 8. The contribution of these substances accounted for approximately 90.0% of the total measured OFPs. Naphthalene, 1-butene, dodecane, 1,2,3-trimethylbenzene, 2-propenal, 1,2,4-trimethylbenzene and 3-ethyltoluene were the dominant species in the photochemical ozone formation process, and their OFP values were over 10 mg O₃ km⁻¹. Among the top 20 species, 11 belonged to the aromatic group and four were alkenes, which accounted for a lower mass percentage but higher MIR values. This indicates that substances present in small amounts but with high MIR values should not be ignored.

Fig. 8

Global energy demands are increasing and so too is the need for more renewable and sustainable sources of energy to help transition us to a post-fossil-fuel-powered world. The European Union (EU) has recently increased its renewable energy target to 32% for 2030 (1), with many countries planning to ban internal combustion engine powered cars by 2040 or sooner. However, the transportation industry is one of the most challenging sectors to adapt to using low-carbon fuels. Transportation modes such as aircraft, heavy-duty and marine vehicles demand high power and energy capacity that are currently unmet by renewable technologies. In the interim, we need clean, sustainable methods, continuous improvement and new innovations in renewable fuels to meet EU and other similar worldwide targets.

Johnson Matthey and bp have been collaborating for the past two decades (2, 3) to develop an efficient reactor system and catalyst for the FT process. This offers a cost-effective method of converting any carbon source into high-quality liquid hydrocarbon fuels.

Today the world consumes more than 55 million barrels (bbl) day^–1 of transportation fuels (4), the vast majority of which originates from crude oil. In addition to being a finite resource, each barrel of crude-oil-derived fuel typically contributes about 475 kg of CO₂ into the atmosphere over its life cycle (based on a 2010 European average) (5). At the same time, hundreds of millions of tonnes of municipal solid waste (MSW) are incinerated or sent to landfill each year, while similar quantities of woody biomass decompose to CO₂ and methane (a more potent greenhouse gas than CO₂) (6). Industrial processes release more than 8 billion tonnes of direct CO₂ emissions (7), and flaring of natural gas releases a further 275 million tonnes of CO₂ equivalent per year (8).

These wastes and emissions are rich in carbon which can be extracted through gasification, reforming or capture of CO₂ (which can then be converted to synthesis gas (syngas) via reverse water gas shift). Converting this carbon to useful syngas rather than allowing it to be emitted to the atmosphere as CO₂ creates an opportunity to significantly reduce fuel life-cycle emissions and its impact on global warming. The carbon intensity of the resulting fuel can typically be reduced by more than 70% (relative to conventional fuel), with reductions of more than 100% possible as grid electricity becomes increasingly renewable and CO₂ sequestration is added to the technology mix.

Gasification of biomass is not new technology. However, it has typically been used to produce syngas for the generation of electricity, rather than chemical synthesis. Effective FT synthesis requires a specific ratio of hydrogen and carbon monoxide, and the catalyst used for this reaction is particularly susceptible to poisoning by impurities that may be present. Gasification of waste introduces the potential for a wide range of contaminants that need to be removed.

The range of potential poisons, and the low levels necessary to ensure continued high-level performance for the FT synthesis catalyst, make syngas purification a critical step of the process. Effective removal of these impurities also ensures that FT products are ultra-clean and high purity (9).

As a world leader in purification and pre- and post-treatment of syngas gas for downstream applications, Johnson Matthey has a range of solutions to condition the syngas (irrespective of its original source) ready for conversion into sustainable fuel.

The FT process was originally developed by Franz Fischer and Hans Tropsch in 1925. It is a way of converting any carbon source into liquid hydrocarbon via syngas, effectively creating synthetic fuel (see Equation (i)).

(i)

Syngas can be generated from various carbon sources, including coal, natural gas, MSW and biomass. The process mainly produces linear, long-chain paraffins that require further upgrading to produce liquid fuels, such as diesel and kerosene. The upgrading step comprises catalytic hydrocracking to both isomerise and crack the long-chain paraffins into smaller-chain paraffins with the correct properties for fuel applications. The various stages in the process are shown in Figure 1. In the quest for sustainable fuel solutions, FT-derived synthetic fuels provide a cleaner way to power cars, heavy-duty vehicles and aeroplanes. The latest developments in FT technology mean that the production of fuel from sustainable carbon sources is now closer to being commercially viable at all industrial scales.

Fig. 1

Catalysts are required for the FT process to increase the rate of reaction and make the process industrially viable. There are broadly two options for FT synthesis, using cobalt or iron catalysts (10, 11). While cobalt is more expensive than iron, it mainly produces normal paraffins. Iron catalysed FT synthesis also incorporates the water-gas shift reaction for CO₂ products and makes a mixture of olefins and paraffins.

The most commonly used catalyst is cobalt, due to its high activity, selectivity to liquid hydrocarbons and stability. Commercial synthesis of hydrocarbons occurs at moderate temperatures of 200–240ºC and pressures of 20–40 bara. During the process, hydrogen and carbon monoxide are converted into long-chain paraffins or waxes over the supported catalyst (see Figure 1). Pore diffusion and mass-transfer effects therefore play a key role in FT catalyst performance due to the need for hydrogen and carbon monoxide to move into and along the catalyst pores against the movement of product molecules going the other way.

The FT synthesis reactions are all highly exothermic, making efficient removal of heat essential for any reactor design. There are a number of benefits of using conventional fixed-bed tubular reactors (12, 13) which is why Johnson Matthey and bp have favoured this design. They are a proven technology with many manufacturers able to fabricate reactors at large scale. They work by holding the catalyst in place via a static bed, which has the advantage of preventing catalyst loss, which could lead to product contamination as can occur in slurry reactors. The reactors have a modular design, which makes increasing capacity as simple as adding tubes; however, conventional fixed-bed tubular reactors are limited by the need to balance tube diameter and catalyst pellet size to achieve effective temperature control without excessive pressure drop. These reactors generally contain tens of thousands of tubes of around 25 mm diameter, resulting in high construction costs with catalyst pellets in the range of 1–2 mm diameter, which reduces catalyst productivity and selectivity to hydrocarbon liquids.

An alternative synthesis route is through slurry reactors. This type of reactor is more efficient at heat removal and uses catalyst powder of the order of tens of microns diameter to minimise pore diffusion resistance. However, slurry reactors can suffer from catalyst attrition, which leads to catalyst loss and product purity issues, and are also less straightforward to scale up compared to fixed-bed alternatives.

Since 1996, Johnson Matthey and bp have been collaborating to bring FT synthesis to the industrial scale. The first major joint venture in 2002 was to build the Nikiski demonstration plant in Alaska, USA (Figure 2), based on the first generation (Gen1) FT catalyst contained within conventional tubular reactor technology (14). The Nikiski plant produced a nominal 300 bbl day^–1 of synthetic crude product from pipeline natural-gas feedstock; and by the time it was decommissioned in 2009, the plant had exceeded all its performance goals related to catalyst productivity, hydrocarbon selectivity, carbon monoxide conversion, methane selectivity and catalyst lifetime. A single charge of catalyst ran for just over 7000 h enabling Johnson Matthey to predict an expected three-year lifetime without any regeneration.

Fig. 2

The integrated plant combined three processes for testing FT technology: a novel compact reformer for syngas generation; a fixed-bed FT reactor; and mild hydrocracking of FT waxes to produce synthetic crude. The original fixed-bed tubular reactor technology was developed as a method of monetising stranded natural gas in remote locations. However, it was only competitive at large scale, above 30,000 bbl day^–1 (~3850 metric tonnes per day (mtpd)), in areas with low natural gas prices and high oil prices.

More recent interest in FT technology is in small-scale applications to produce renewable fuel from MSW or cellulosic biomass. This involved developing technology that lowered costs whilst improving efficiency. In 2009, Johnson Matthey designed a novel catalyst carrier device to fit inside a tubular reactor that allows for the use of smaller catalyst particles. At the same time, bp developed an improved second generation (Gen2) catalyst formulation (15). Both organisations then worked to combine both the new catalyst and the novel catalyst carrier device, which produced a step change in commercial FT performance (see Figure 3). The CANS^TM catalyst carrier technology received global recognition, winning both the Research Project Award and the Oil and Gas Award at the Institution of Chemical Engineers (IChemE) Global Awards in 2017, and the Rushlight Clean Energy Award and Rushlight Bioenergy Award in January 2020. These accolades demonstrate how advanced FT technology will dramatically impact the chemical engineering industry, with many real-world applications.

Fig. 3

The novel catalyst carrier reactor design (16) combines the advantages of the fixed-bed tubular reactors and the slurry-phase systems. Its modular design enables low-risk scale-up and simple operation, while the smaller catalyst particles offer high productivity and selectivity. The stacked catalyst carriers have a unique design that aids their ability to perform FT synthesis as shown in Figure 4.

Fig. 4

A reactor tube contains 60–80 of the CANS^TM catalyst carriers and effectively creates a series of mini adiabatic radial-flow reactors with interbed cooling. Radial flow through each CANS^TM catalyst carrier means that, although the reactor tubes are 10–15 m long, the effective catalyst bed thickness is only around 15% of the overall tube length. This enables the use of sub-millimetre catalyst particles, which improves selectivity and activity whilst limiting the reactor pressure drop to that of a conventional fixed-bed tubular reactor. Wide-diameter tubes of 75–100 mm are used in the novel reactor, which has the effect of reducing the heat-transfer surface per unit volume of catalyst. However, this is compensated by a larger temperature difference at the wall, where reactants are hottest (as opposed to the centre of the tube in conventional fixed-bed tubular reactors). Combining this structure with a high gas velocity through the narrow annulus between the CANS^TM catalyst carrier body and tube wall results in excellent heat transfer. By separating heat removal from the catalyst bed, good control of the reaction temperature is also achieved without the risk of quenching the reaction. The advanced reactor technology also enables operation with >50% inerts in the reacting gas, allowing a single-stage FT reactor to be used in a recycle loop to maximise overall conversion of carbon monoxide to >90% (Figure 5).

Fig. 5

Compared to conventional fixed-bed tubular reactors, the new CANS^TM catalyst carrier and optimised catalyst reduces the number of reactor tubes by 95%, significantly simplifying the design and fabrication of the reactor, resulting in a reduction of capital expenditure costs of around 50% for the FT unit. There is also a three-fold increase in production for the same size reactor as the catalyst performance is closer to that of a powder, with excellent heat and mass transfer to, from and within catalyst particles. The increased productivity at least halves the catalyst volumes usually required for the same production rate. Additionally, containing the catalyst inside the CANS^TM catalyst carrier removes the requirement to filter the catalyst from the wax product. Instead the catalyst is easily replaced by removing the entire catalyst carrier, meaning there is no interaction with the hazardous cobalt catalyst material. Fundamentally, this makes FT applications possible at both small and large scales, with around 6000 bbl day^–1 (770 mtpd) achievable in a single reactor of around 900 tonnes. For areas with tighter transport restrictions, 2000 bbl day^–1 can be delivered in a single reactor of around 4 m diameter and 250 tonnes in weight.

One of the main challenges to overcome was proving that the concept worked at commercial scale, and so Johnson Matthey has invested in extensive testing to develop the engineering science necessary to implement the novel reactor concept. This involved building customised rigs to validate heat-transfer performance, hydraulics and accurately measure reaction kinetics on high-throughput microreactors. Significant engineering effort has been required to develop models capable of accurately predicting the performance of commercial-scale reactors. The initial proof of concept work was carried out using CANS^TM catalyst carriers manufactured by an experienced prototyper.

FT catalysis is strongly influenced by cobalt crystallite size, support properties and catalyst treatments. Selection of the cobalt crystallite size is critical to obtaining the required performance. Larger cobalt crystallites result in a less active catalyst due to the lower surface area to volume ratio, and thereby require higher temperatures to achieve a target conversion. Alternatively, if cobalt crystallites become too small the chemistry favours chain termination (methane formation) over chain growth (C–C coupling). While the desirable cobalt crystallite (17, 18) size is in the narrow range of 8 nm to 10 nm for FT synthesis, the activity of a good catalyst can be significantly reduced by suboptimal treatments, such as the reduction stage of the cobalt oxide to the active metallic phase. Cobalt-based FT catalysts are normally made by impregnating the support with a cobalt salt, calcination to give cobalt oxide and subsequent reduction under hydrogen in the plant to give the active cobalt metal phase. The catalyst reduction process is defined in Equation (ii), which highlights the significant levels of water that are produced throughout the catalyst bed, and this in turn can sinter, reoxidise or damage the catalyst significantly if not fully catered for under process conditions. Catalyst bed profile effects are also significant as the bottom sections of the bed are exposed to the water produced at the top of the bed, while higher pressures required commercially also lead to higher water partial pressures in the catalyst pores.

(ii)

bp originally developed the Gen2 catalyst formulation as a drop-in for conventional fixed-bed tubular reactors and this formulation has been adapted to the CANS^TM technology by Johnson Matthey to produce sub-millimetre size catalyst particles at scale. Developing the new formulation to achieve improved activity, selectivity and stability, while optimising the catalyst activation has required thousands of hours of testing at laboratory scale in high throughput and pilot plant test units. This has been supported by a state-of-the-art FT unit, with exceptional online analytics for all products up to C18 and analytical capabilities such as in situ X-ray diffraction and temperature programmed reductions which enable catalyst evaluation under process conditions (19, 20).

While the hydrocarbons and oxygenates that were identified are known compounds formed during the low temperature, cobalt catalysed, FT process the combination of the multiple analysis techniques used has allowed a level of detail to be gained on the FT product composition that is seldom reported (9). Typically, the long-chain 1-alcohols and carboxylic acids were found to be present at levels of one tenth and one thousandth that of hydrocarbons of equivalent carbon chain length respectively. Additionally, hydrogen-1 nuclear magnetic resonance (¹H-NMR) and carbon-13 nuclear magnetic resonance (¹³C-NMR) analyses were used to quantify the average class compounds concentration of 1-olefin, cis- and trans-2-olefins, 1-alcohol and aldehyde as appropriate for the technique used. The 1-olefin:n-paraffin ratio in the hydrocarbon liquid and wax products was found to decrease significantly with increasing carbon chain length in both phases and much more so than those of the 2-olefin or 1-alcohol.

Catalyst activity and selectivity is only part of the process however, with stability, robustness to process events and life duration also playing a vital role in a commercial catalyst. Johnson Matthey Davy and bp built on their extensive experiences of the Gen1 catalyst in the Nikiski demonstration plant to optimise this further for the Gen2 catalyst. This included several catalyst life tests which operated for many thousands of hours at steady FT process conditions. This included the catalyst formulation used in CANS^TM catalyst carriers operating with exceptional performance over an 18,000 h life test. The gradual drop in catalyst activity over this period was compensated by an increase in operating temperature within the reasonable limits of a commercial reactor. Despite frequent shutdowns and other challenges associated with laboratory-scale operation, the catalyst was still showing good activity and selectivity at the end of this test. This is a result of the process having been designed to be robust and operate in chemically stable conditions.

The CANS^TM catalyst carrier concept has been successfully demonstrated at commercial scale on a pilot plant at Johnson Matthey’s research and development (R&D) facilities in Stockton-on-Tees, UK. It is not practical to test a full-length commercial reactor tube at these facilities, due to limitations on gas supply and product storage capacity, so a creative approach was required. Flexible design of the pilot plant enabled testing of multiple commercial-size CANS^TM catalyst carriers in a much shorter tube; by recycling gas, liquid products and produced water to simulate the full range of conditions and flowrates present in a commercial reactor tube. This, coupled with raising steam in the reactor cooling jacket, has enabled full demonstration of the catalyst, CANS^TM catalyst carriers, hydraulics and heat transfer at commercial conditions, flows and tube diameters.

Over 20,000 h of testing under commercial flowsheet conditions has demonstrated the performance of the CANS^TM catalyst carrier and the Gen2 catalyst with a confirmed product slate and stable catalyst life. A C5+ selectivity of around 90% and C5+ productivities in excess of 300 g l^–1 h^–1 have been demonstrated on the pilot plant. The crude FT product consists of a wax stream which is liquid at reaction conditions and solid at ambient temperature and a light hydrocarbon condensate stream which is liquid at ambient temperature. Figure 6 shows both these products are high quality, clean and catalyst-free.

Fig. 6

The International Energy Agency, France, has measured the share of global energy-related CO₂ emissions from transport at 23%, with aviation contributing 2–3% of worldwide anthropogenic CO₂ emissions (21). There is great potential for this figure to be reduced by using synthetic fuels from sustainable feedstocks, and this makes fuels produced via the FT process an attractive alternative to current aviation fuels. Synthetic fuels also burn cleaner, due to the absence of sulfur and aromatics, while also producing fewer particulates (22). As a result, FT fuels lead to increased combustion and turbine life, while the enhanced thermal stability reduces deposits on engine components and fuel lines. This results in a dual advantage for the aviation industry, in terms of both improved fuel economy and less maintenance of aviation equipment.

The scale of the market is substantial, with air transportation alone expected to consume at least 500 million tonnes per year (11 million bbl day^–1) of fuel by 2050 (23). Practical limitations on the supply of waste feedstocks or local, low-cost renewable power for hydrogen production typically limit the scale of each project to less than 5000 bbl day^–1. With tens of thousands of filled CANS^TM catalyst carriers required for each project, the ability to consistently and efficiently produce both the CANS^TM catalyst carriers and the FT catalyst which they contain is crucial for successful commercial deployment of the technology.

To address this, Johnson Matthey has collaborated closely with a company skilled in delivering sustainable engineered solutions for vehicle exhaust after treatment systems, to develop a mechanical design for the CANS^TM catalyst carriers that is economical to make, can be easily filled with catalyst and meets the functional specifications developed by Johnson Matthey. This has been confirmed by testing of commercial prototypes.

A production line has been constructed and commissioned for mass manufacture and catalyst filling of the CANS^TM catalyst carriers, and the first charge has now been produced for the first commercial project. The production line is fully automated to allow the safe filling of the cobalt-containing catalyst and contains state of the art equipment and in-line quality control to assure the CANS^TM catalyst carriers meet the required functional specifications. The functional specifications were established during the development of the CANS^TM catalyst carriers from concept to prototype with testing performed on in-house built rigs at Johnson Matthey in Teesside, UK. Identifying these upfront allowed Johnson Matthey and the manufacturer to work together to ensure the resulting production line would safely, efficiently and consistently produce high-quality units.

A collaborative team of engineers from Johnson Matthey and the manufacturer worked closely during initial commissioning of the line to work through the various challenges associated with scale-up to mass manufacture of a novel process. This knowledge will be invaluable as further improvements and optimisations are implemented.

In order to achieve high-quality performance, challenging activity and selectivity targets were set for the FT catalyst. Scale-up of the chosen formulation took place at Billingham in the UK. Catalyst preparation was initially at laboratory scale with short-term and long-term testing of development samples conducted using both micro-reactors and CANS^TM catalyst carriers, facilitating accurate modelling of the performance of a full-scale FT reactor.

As scale-up continued, preparation of the FT catalyst moved into the Manufacturing Science Centre (MSC) where appropriate technologies were identified for each of the steps involved in catalyst production. The technical risk of scale-up was minimised by using down-scaled versions of full-scale production equipment.

A fully developed catalyst manufacturing process was transferred from the MSC to a dedicated production asset located at Clitheroe in the UK (Figure 7). Careful attention was paid to the specification of the raw materials used. To ensure a proper understanding of the impact of trace impurities on long term FT catalyst performance, a series of experiments were conducted in which the FT catalyst was doped with different FT poisons.

Fig. 7

Every production batch of FT catalyst has been tested against an agreed quality assurance specification. Conforming product was loaded into CANS^TM catalyst carriers as it was manufactured, thus minimising the overall production timeline.

The Johnson Matthey Davy/bp FT technology incorporating CANS^TM catalyst carriers offers benefits to both small- and large-scale operations with good economics, opening up the prospect of exciting future applications.

Fulcrum BioEnergy, USA, is the first to licence the Johnson Matthey Davy/bp FT technology in its Sierra BioFuels Plant, located near Reno, Nevada (Figure 8). The Sierra plant will be the first in the USA to produce a renewable low-carbon transportation fuel from MSW or household garbage. The plant will first sort the waste to recover recyclables and remove material not suitable for processing, so is not in competition with recycling processes. The remaining material will be processed into a feedstock before being fed into a gasification system to produce a syngas. This is then converted into hydrocarbons by the FT technology for the production of renewable fuels. The Sierra plant construction is approaching completion and when operational will convert approximately 175,000 tonnes of MSW into approximately 42 million litres of renewable FT product each year.

Fig. 8

Multiple projects are being developed in the USA and Europe, which can make a significant contribution to meeting the demand for renewable transportation fuels in the next decade.

In order to meet greenhouse gas emissions reduction targets, especially for aviation (24), production of sustainable fuels will have to substantially increase. There are a range of sustainable fuels potentially available, but limitations on sustainable feedstocks and viable technology routes mean that diesel and jet fuel production via FT synthesis will need to form a key part of this industry. Producing fuels via FT synthesis is not new. However, cost of production was always a barrier, with existing large-scale producers of FT fuels unable to economically scale down to match the size of the waste facilities that feed them. The CANS^TM technology addresses this problem, offering an economic and efficient solution at the scales required by the industry.

The proposed solvent plant is co-located with a Kraft paper and pulp mill in China with throughput as defined in Table I. Figure 1 outlines the Kraft process, which conventionally directs weak black liquor to multi-effect evaporators, producing strong black liquor which is combusted in a Tomlinson boiler to produce steam (4). This steam makes the mill self-sufficient in steam and electrical energy. Importantly, the cooking chemicals (NaOH and Na₂S) are recovered and recycled to the pulping process.

Fig. 1

As previously mentioned, investments in heat integration have freed up a portion of the weak black liquor coproduct for alternative uses. This study explores the opportunity of utilising this excess coproduct, taken as 25% of total production, for isopropanol and acetone production through aerobic fermentation in an integrated solvent plant as outlined in Figure 1.

Given black liquor has no economic value as a product, it is costed at its utility value. This is calculated based on its conventional use for renewable electricity generation, requiring capital investment in increased steam turbine capacity. The foregone net present value (NPV) associated with this conventional use is used as the utility value for the black liquor feedstock.

In the proposed solvent plant (Figure 1), weak liquor undergoes SCWG to carbon dioxide and hydrogen. A challenge, however, is the efficient recovery of the cooking chemicals from the SCWG reactor and their recycle to the pulp mill digestor. Loss of these salts would result in a significant cost to the pulp mill. Under supercritical conditions, the properties of water change from polar to apolar, where the solubility of inorganic salts is very low (31). Cao et al. described the precipitation of alkali sodium salts in SCWG, reporting a neutral pH for the reactor effluent, suggesting that under supercritical conditions the salts largely precipitate from the solution (32). However, this precipitation can cause issues with plugging and fouling within the reactor (33). In this study the salts are removed prior to entering the SCWG reactor, in a manner similar to supercritical water desalination (34, 35) and modelled for SCWG of black liquor (33).

The solvent plant’s mass and energy balance was informed by experimental data from continuous gas fermentation (28), and rigorous process simulation using Aspen HYSYS v11. The lignin content in black liquor was modelled as guaiacol, a model compound for lignin (36), as principal feed to the solvent plant. The weak black liquor is further diluted prior to entering the SCWG reactor, as lower biomass concentrations promote superior thermal cracking and yields greater hydrogen and carbon dioxide owed to the increased water concentration favouring the forward water-gas shift reaction (37).

The simplified flow diagram (Figure 1) outlines the six plant sections of the solvent plant, whilst Figure 2 presents a detailed process flow diagram and operating conditions for upstream and downstream processing. The unit operations included in each of the six plant sections are summarised in Table II. Table III summarises the scale-up of the experimental gas fermentation data for the process simulation, which recognises the oxygen mass transfer limitations associated with the safety requirement to maintain non-flammable operating conditions. The heat integration between the low temperature exothermic gas fermentation and the high temperature endothermic SCWG is facilitated using a heat pump with isopentane as the working fluid (28).

Fig. 2

Isopropanol and acetone are produced in both the aqueous and vapour phase of the bioreactors. The solvents in the vapour phase are recovered via gas absorption through mass integration using internal process streams, i.e. the isopropanol product was utilised to recover acetone, and water to recover isopropanol. For the isopropanol in the aqueous phase, azeotropic distillation is required due to the homogeneous minimum boiling point azeotrope formed between isopropanol and water (38). Conventionally, this azeotrope is broken using an entrainer, historically benzene (39). However, owed to its carcinogenic properties, alternative entrainers such as cyclohexane have been adopted (40). An alternative azeotropic separation technique is pressure swing distillation, taking advantage of the composition differences in the azeotrope at different pressures (41). In this work, pressure swing distillation was employed with the coproduct acetone acting as an unconventional entrainer. Further detail of the separation train is presented in Figure 2.

A U-loop bioreactor, similar to the one used by Peterson et al., is used in this work (42). The benefit of a U-loop bioreactor is that high mass transfer coefficients can be achieved without the need for mechanical agitation, leading to greater oxygen transfer rate and a reduced power requirement compared to conventional stirred tank reactors (42). The oxygen mass transfer coefficient calculation associated with the solvent plant’s mass balance is presented in Table S1 in the Supplementary Information (available with the online version of this article), falling at the lower end of the range of mass transfer coefficients reported by Peterson et al. (42). Details of the experimental gas fermentation data is presented in Table III; a more detailed explanation of the experimental procedure can be found in Bommareddy et al. (28).

Significant heat integration makes the solvent plant self-sufficient in electricity and both low and medium pressure steam. Furthermore, process water recovered from distillation and the steam condensate is recycled to reduce the water make-up burden.

The process flow diagram for conventional renewable electricity generation, used to value the black liquor, is presented in Figure 3. An additional steam turbine is required to produce the renewable electricity for sale, relying upon the existing multi-effect evaporators, air compression and Tomlinson boiler. Superheated steam at 9000 KPa and 480ºC is used in the steam turbine (44). The medium pressure steam exiting the turbine is used in the multi-effect evaporators to concentrate the excess black liquor to 75% and to preheat the auxiliary air supplied to the Tomlinson boiler. Similarly, the associated electricity demand for the air compressor and pump is provided by the electricity generated. Resultantly, through conventional renewable electricity generation, the excess black liquor produces 138 GWh year^–1 for sale to the grid.

Fig. 3

The mass and energy balance associated with the rigorous process simulation informs the capital cost, fixed operating cost and variable operating cost estimation. For the capital cost estimation, major equipment purchase costs were estimated using the models from Seider et al. (45), with the exception of the turbo-expander (46). Three different methods are used to calculate the FCI, owed to differences in the estimation methods. These three methods are designated as: the NREL method outlined in the 2011 NREL report (27), the Towler and Sinnott (TS) method taken from Chemical Engineering Design (47) and the Hand method detailed in Sustainable Design Through Process Integration (48). The calculation basis of the three methods is presented in Table IV.

For all three methods, the calculated equipment purchase costs are multiplied by an installation factor to obtain the inside battery limit (ISBL) installed costs. Both the NREL and Hand methods use installation factors dependant on the equipment type, whereas the TS method uses a universal multiplier. All installed equipment costs were adjusted to 2019 costs using the Chemical Engineering Plant Cost Index of 607.5 (49). A location factor of 0.51 was used for China (using indigenous materials), based on the 2003 location factor of 0.61 (47), updated to 2019 via the Chinese Yuan to US dollar exchange rate.

Three methods were used to calculate the fixed operating costs as summarised in Table V. As before, the NREL method (27) and the TS method (47) were employed. However, as the Hand method is solely for FCI, the third was the taken from Coulson and Richardson Volume 6 (50). Variable operating costs were estimated based on the costs detailed in Table VI, subject to annual inflation as outlined in Table VII.

Time series analysis was used to forecast the long-term average price of isopropanol and acetone. Takens’ theorem was used as the basis for this analysis (53). Takens’ theorem states that for a deterministic system, the underlying state variables that created the time series are embedded within the data. Using this theorem a deterministic, dynamic system can be reconstructed based on the observed time series. Forecast models constructed using the embedded state variables assume that the market drivers underpinning the trajectory of the state variables in phase space remain largely unchanged. An embedding dimension of 10 was used to reconstruct the isopropanol and acetone price models from monthly average price data obtained from the Intratec database (54). In this work, a radial basis function neural network (RBFNN) containing eight neurons was used as a model to predict the future commodity prices. The network was trained as a one step ahead predictor by minimising the mean square error of the difference between the actual and predicted prices. Once trained, the network was evaluated (tested) in free run mode, where successive predicted prices (outputs) become inputs to the RBFNN. The confidence limits corresponding to the trained RBFNN were calculated as a reliability measure of the prediction as per the work undertaken by Leonard, Kramer and Ungar (55). The benefit of using an RBFNN is that the resultant forecast price is an impartial product of the dataset’s underlying state variables.

The long-term average price for renewable electricity sales was taken as US$0.109 kWh^–1 as per the biomass subsidy in China (56). This is used to inform the renewable electricity project to value the black liquor and for the excess electricity generated by the solvent plant.

The cost models from Section 2.3 and the product price forecast models from Section 2.4 inform the investment analyses. The black liquor is costed at its utility value, calculated as the foregone NPV from generating renewable electricity. Resultantly, the NPV for the solvent plant is calculated by subtracting the NPV of renewable electricity generation. The investment analysis parameters used are detailed in Table VII.

A sensitivity analysis was conducted using a Monte Carlo simulation based on the cost parameters in Table VIII, creating an uncertainty framework. The cost parameters were taken from (47), with the exception of renewable electricity sale price where the upper limit for the long-term average price was capped at the current biomass subsidy in China, US$0.109 kWh^–1. This limit was applied due to the decreasing trend in renewable electricity subsidies (58). In contrast, the long-term average prices for isopropanol and acetone were varied ±30% from the forecast price. This provides a stochastic counter to the assumption used to determine the forecast prices: that the deterministic market drivers underpinning the trajectory of the state variables remain largely unchanged. However, given that market drivers are subject to change, the long-term average price may be banded with an equal likelihood of being higher or lower than the forecast price.

A uniform distribution for these parameters was used and varied for the solvent plant and conventional renewable electricity generation (used to value the black liquor). All the cost parameters in Table VIII, other than labour and electricity, were varied independently. 2000 simulations were run, stochastically varying the parameters within the defined lower and upper limits to produce a probability distribution of the solvent plant’s NPV.

A cradle-to-gate LCA model was developed using the ecoinvent 3.6 inventory database, following ISO Standards 14040 (59) and 14044 (60). GHG emissions were calculated based on the most recent Integrated Pollution Prevention and Control 100-year global warming potential (GWP) factors to quantify GHG emissions in terms of carbon dioxide equivalents (CO_2eq) (61). Functional units were defined as 1 kg isopropanol, 1 kg acetone and 1 kWh of electricity. In line with the investment analysis, the LCA model considers the net electricity output of solvent plant by subtracting the foregone electricity from combustion of black liquor at the pulp mill. Life cycle environmental impacts are allocated between these three products using both economic and energy allocation. The GHG emission rate for the external process inputs: cooling water, process water and ammonia were taken from the ecoinvent 3.6 inventory database using the allocation at the point of substitution system model (62), whereas electricity was taken as the 2018 China electricity mix (63). The bio-based solvents isopropanol and acetone sequester biogenic carbon dioxide and hence are credited with a negative GHG emission based on their carbon content. Downstream activities, including the use and end-of-life of isopropanol and acetone products are not considered. These activities are assumed to be identical to those of conventional isopropanol and acetone, given that they are chemically and functionally identical, and therefore have no influence on the relative GHG emissions of renewable and conventional solvent products.

The solvent plant (Figure 2) produces three products, summarised in Table IX. The contribution of each product to the plant’s income is also presented. Whilst isopropanol contributes to almost half the solvent plant income the renewable electricity fraction is the second highest contributor, highlighting the significant amount of renewable electricity generated by the solvent plant.

The investment analyses for the solvent plant and conventional renewable electricity generation are detailed in Tables S9 and S12, as per the investment analysis parameters presented in Table VII. The NPV for conventional renewable electricity generation represents the utility value of the black liquor, valued at US$73 million (Table S12). This is subtracted from the NPV of the solvent plant (US$115 million) to produce the cumulative NPV presented in Figure 9. For the nominal TEA model inputs, the solvent plant’s net cumulative NPV is US$42 million.

Fig. 9

Given the conceptual stage of the TEA, a Monte Carlo simulation was undertaken as per the uncertainty framework outlined in Table VIII. The produced probability distribution in Figure 10 avoids making an investment decision based solely on nominal TEA inputs. The cumulative probability curve presents a 70% probability that the solvent plant will achieve a net cumulative NPV between US$35 million and US$85 million, noting that no negative outcomes are predicted.

Fig. 10

Figure 11 summarises the outcome of the cradle-to-gate LCA for the solvent plant, compared to the conventional fossil derived processes; using both economic and energy allocation for the isopropanol, acetone and renewable electricity products.

Fig. 11

Both solvents achieve negative GHG emissions when produced via the solvent plant using economic and energy allocation. The GHG emission for the two allocation methods are comparable, indicating the price per unit energy (US$ MJ^–1) is similar for all three products. The negative emissions are an intrinsic outcome of the cradle-to-gate framework, which excludes the end use for the products. As the total GHG emissions of the solvent plant are lower than the overall biogenic carbon sequestered, negative GHG emissions are achieved for the solvent products.

The negative GHG emissions compare favourably to the conventional isopropanol (hydration of propene) and acetone (oxidation of cumene) processes. Additionally, the GHG emissions associated with the excess renewable electricity from the solvent plant also compare favourably to the electricity mix in China 2018). Furthermore, as the end use for the solvents remains the same regardless of the production method, the relative GHG emissions are valid beyond the cradle-to-gate framework.

As highlighted in the Introduction, the commercial implementation of gas fermentation is largely dominated by anaerobic fermentation. Therefore, it is important to compare the results to a best-in-class technology. In addition to successfully commercialising ethanol production via gas fermentation, LanzaTech have also investigated gas fermentation to produce acetone, a precursor to isopropanol (64). As such, LanzaTech’s investigation undertaken for the US Department of Energy (US DOE), in collaboration with Oak Ridge National Laboratory, USA, is used as a benchmark anaerobic process (65).

As highlighted previously, the primary differences between anaerobic and aerobic fermentation technologies are inherent to the C1 fixation metabolic pathways. Strictly respiratory (aerobic) cell factories require air to be continuously fed into the bioreactor to facilitate carbon fixation. In addition, owed to the intrinsic thermodynamic inefficiency of the Calvin-Benson-Bassham cycle employed by aerobic bacteria, an excess of low temperature heat is produced. As such, a conventional process flowsheet for aerobic fermentation employs operationally costly compressors and chillers. In contrast, for anaerobic fermentation there is a reduced chiller requirement and the compressor duty is less pronounced. Moreover, owed to the presence of oxygen, aerobic fermentations require the use of more costly stainless steel reactors and more complex process control systems. Whilst the latter is an intrinsic requirement of aerobic fermentations, in this work we have reconciled the increased utility demand of aerobic fermentation through process integration (28). This integration employs a heat pump to utilise the low temperature heat generated by aerobic fermentation to heat the SCWG reactor feed, removing the cooling water burden required by the bioreactors. Additionally, the compressor duty is fully supplied through the electricity generated upon letting down the SCWG reactor’s high-pressure gas product. As a result, the economic and LCA outcomes for the solvent plant should be comparable to anaerobic fermentation technology.

LanzaTech’s anaerobic study achieved a combined selectivity of 94.7% for ethanol and acetone, of which 57.3% was acetone (65). LanzaTech disclosed that by selling acetone at market prices they are able to sell coproduced ethanol at or below the US DOE’s 2022 target of US$3 GGE^–1 (GGE = gallon of gasoline equivalent) (66). Therefore, in this study, the price per GGE was calculated for the solvent products as a biofuel mix, with renewable electricity sold at the current market price. A value of US$2.87 GGE^–1 (Figure 12) was obtained, below the US DOE’s target, highlighting the competitiveness of the heat integrated aerobic solvent plant. Notably, neither isopropanol nor acetone are typically used for their fuel value, highlighted by their higher market prices. As such, the solvent plant is profitable as either a biofuel or commodity chemical facility.

Fig. 12

For LanzaTech’s anaerobic process, the cradle-to-gate LCA using energy allocation produced a calculated GHG emission of –1.9 kg_CO2eq kg^–1_{acetone + ethanol} for a heat integrated scenario (see Table S13 for calculation). In Figure 12, the LCA for the solvent plant is presented, indicating a net GHG emission of –2.04 kg_CO2eq kg^–1_{isopropanol + acetone}, which is in line with LanzaTech’s study (Figure 12). Resultantly, from both the TEA and LCA results, the greater thermodynamic efficiency of the anaerobic Wood-Ljungdahl C1 fixation pathway over the aerobic Calvin-Benson-Bassham Cycle is not evident for the heat integrated solvent plant.