SMEs refers to the ability of the material to memorise a shape and materials that possess these properties have a multitude of exciting technical and medical applications (1–14). For materials such as alloys this is commonly in a one-way SME (7, 15), however, there are a variety of materials that are capable of reverting to their permanent shape or original state upon exposure to a stimulus (such as a temperature change) or indeed multiple stimuli (16). SMP-based materials have been widely investigated since the 1980s because of the abundance of potential applications imparted by their interesting properties (for instance, stimuli-responsiveness and ability to change shape), which can lead to technological innovation and the generation of new high value products for technical and medical applications (1, 17–19).

The reversible transformation of SMPs functions by primary crosslinking net points (hard segments) memorising and determining the permanent shape, and secondary switching segments (soft segments) with a transition (T_trans) to reduce strain stress and hold the temporary shape. Below the T_trans, the material will be in its permanent shape and be stiffer than when T_trans is reached and the SMPs are more malleable and can be deformed into a desired shape (usually through application of an external force). The deformed state is maintained once the external force has been removed and the system is no longer at or above T_trans. SMPs revert to their original state once the T_trans conditions are met. This process describes the SME pathway of SMP-based materials that are thermally-induced (albeit not for some light or chemical-induced systems).

While most SMP-based materials hold a single permanent shape and a single temporary shape, recent advances in SMP technology have allowed the generation of multiple-shaped-memory materials with different stimuli responses (light or chemical) (16, 20, 21). An interesting example of this is a triple shaped-memory material generated by combining two dual SMPs with different glass transition temperatures (T_g) (22, 23), where the SMPs switch from one temporary shape to another at the first T_trans, and then back to the permanent shape at another, higher activation temperature (22).

SMPs have a large range of properties from stable to biodegradable and transient, elastic to rigid or soft to hard, depending on the structural units that constitute the SMP. Consequently, SMPs not only respond to temperature (24) and magnetism (25) like shape-memory alloys (SMAs) (26), but also to moisture (27), electricity (28), light (29) and chemical stimuli (such as a pH change) (30). Moreover, there are other principles of SME; for instance, a thermal-responsive SMP can proceed via a Diels-Alder reaction (chemical crosslinking/reversible covalent bonds) (31). SMPs tend to have much milder processing conditions than SMAs (<200°C, low pressure), have a greater extent of deformation (strain more than 200% for most materials) and tend to be based on cheap starting materials with simple synthetic procedures (12, 32). After the term ‘shape-memory’ was first proposed by Vernon in 1941 (32), the significance of SMPs was not fully realised until the 1960s, when crosslinked polyethylene (PE) was used to make heat-shrinkable tubes and films (33). Significant investment in the development of SMPs began in the 1980s (34) with rapid progress realised in the last decade, particularly with a view to the generation of shape-memory materials with exciting and versatile features.

Two important quantities used to describe SMEs are the strain recovery rate (R_r) and the strain fixity rate (R_f). R_r describes the ability of a material to memorise its permanent shape, while R_f describes the ability of switching segments to fix the mechanical deformation. R_r is calculated using Equation (i):

(i)

where N is the cycle number, ε_m is the maximum strain imposed on the material and ε_p is the strain of the sample after recovery. R_f is calculated using Equation (ii):

(ii)

where ε_u is the strain in the fixed temporary shape. SMPs respond to specific stimuli through changes in their macroscopic properties (for example, shape) (26). The polymer network underlying active movement involves a dual system, one that is highly elastic and another that can reduce the stiffness upon application of a certain stimulus. The latter system incorporates either molecular switches or stimulus sensitive domains (35). Their shape-memory feature is a result of the combination of the polymer’s architecture, and a programming procedure that enables the formation of a temporary shape. Net points consist of covalent bonds or intermolecular interactions and the SMP’s hard segments form the net points that link the soft segments (acting as a fixed phase), whereas the soft segments work as the molecular switches (acting as a reversible phase). The fixed phase prevents free flow of the surrounding polymer chains upon the application of stress. The reversible phase, on the other hand, undergoes deformation in a shape-memory cycle and is responsible for elasticity. For example, if the T_trans is T_g, the micro-Brownian motion of the network chains is fixed at low temperature (below T_g) and will be switched back on at high temperature (above T_g), recovering its original state. When T_trans is the crystal melting temperature (T_m), the switching segments crystallise at low temperature (below T_m), and then recover their original state at high temperature (above T_m). In addition, T_g normally extends over a broader temperature range compared to T_m, which tends to have relatively sharper transitions in most cases (26). Moreover, after the exposure to a specific stimulus and the T_trans is achieved, the strain energy in the deformed state is released, resulting in the shape recovery phenomenon. The general process of this SME for SMPs is depicted in Figure 1, wherein the polymer network structure is either chemically or physically crosslinked and the switching units are made from a semi-crystalline or amorphous phase.

Fig. 1.

Shape-memory behaviour can be demonstrated in various polymer systems that are significantly different in molecular structure and morphology. SME mechanisms differ according to the specific SMP(s); for instance, the SME mechanism of the chemically crosslinked semi-crystalline PE SMP. The crystalline phase, with a T_trans being T_m, is used as the molecular switching unit providing shape fixity. The chemically crosslinked PE network memorises the permanent shape after deformation upon heating (12, 36, 37), and the mechanism of the thermally-induced shape-memory PE (SMPE) is depicted in Figure 2.

Fig. 2.

The associated modulus of elasticity is dictated by configurational entropy reduction that occurs with deformation of the constituent chains and is therefore often termed entropy elasticity. For T>T_trans (T_g, T_m or other), polymer networks exhibit super-elasticity wherein the polymer chain segments between crosslink points can deform quite freely and are prone to being twisted randomly via rotations about backbone bonds, maintaining a maximum entropy and minimum internal energy as macroscopic deformation occurs (12). The classic prediction from rubber elastic theory is that the resulting elastic shear modulus (G) is proportional to both crosslink density and temperature (Equation (iii)):

(iii)

where ν is the number density of network chains, p the mass density, R the universal gas constant and M_C the molecular weight between crosslinks. From a macroscopic viewpoint, the SME in SMPs can be graphically represented in three-dimensions (3D). Tensile strain vs. temperature and tensile stress (for example, elongation) is depicted in Figure 3.

Fig. 3.

Using the shape-memory strain-temperature-stress relationship description in Figure 3, the features of SMPs that allow for good shape-memory behaviour include: a sharp transition that can be used to quickly fix the temporary shape at low temperature, and the ability to trigger shape recovery at high temperature; super-elasticity above T_trans that leads to the eventual shape recovery and avoids residual strain (permanent deformation); and complete and rapid fixing of the temporary shape by immobilising the polymeric chains without creep thereafter (12, 37). Thus far, the SME models describing how SMPs recover their original state prominently involve thermo-responsive SMPs. However, careful design of the polymers allows the opportunity for SMPs to possess different stimuli responses and applications.

A multitude of different triggers for SMEs and SMPs exist. However, an in-depth review is outside the scope of this mini-review, and therefore a few examples are highlighted below.

It is possible to generate thermally-induced SMEs in a variety of materials (18–20, 38–40), however a comprehensive overview is outside the scope of this mini-review. As previously discussed, the SME of SMPs can be thermally-induced, and these SMPs are the most common (26). Figure 1 depicts a general overview of the SME mechanism of SMPs, with a schematic of the SME mechanism for thermally-induced SMPs with T_g (amorphous cases) and T_m (crystalline cases). Figure 2 presents a specific example of the SME mechanism for SMPE with the T_trans being T_m. In addition, advanced thermomechanical constitutive models have been used to study the materials’ behaviour (for example strain-temperature-stress development with time) in a very accurate way (41). By applying these models to SME mechanistic studies and the detailed characterisation of the SMPs (crosslinks, intermolecular and intramolecular interactions involving the SMPs) (12), a deeper understanding of the SME of SMPs can be achieved, which has proven beneficial for the development of new SMPs and their proposed applications (31). For example, poly(ε-caprolactone) (PCL), typically a biodegradable polymer, has been reported to possess high shape fixity and recovery. This was achieved by integrating reversible bonds within the PCL polymer network via the Diels-Alder addition of 1,2,4-triazoline-3,5-dione (TAD)-anthracene and Alder-ene addition of TAD-indole (42). These PCL SMPs were reported to attain recovery ratios greater than 99% (43). Furthermore, a dual-functional (self-healing and shape-memory) polymer network was achieved by crosslinking a polydimethylsiloxane (PDMS) polymer containing dense carboxylate groups (100% mol) (PDMS-COOH) with small amount of poly(ethylene glycol) diglycidyl ether (PEGDGE) (44). This SMP (PDMS‐COO-E) actuates at body temperature (37°C) with possible strain ca. 200% and shape recovery ratios at 98.06%. In addition, a 25 mm × 4 mm × 1 mm sample cut into two separate pieces healed (the two pieces become one whole piece with no evidence of a cut) when the two cut surfaces were brought into contact after 6 h at 25°C. Thus, the unique material, PDMS‐COO-E, may have a wide range of applications in many fields, including wearable electronics, biomedical devices and four‐dimensional (4D) printing (1, 19). Interestingly, the material was also reported to possess a greater than 85% light transmittance (425 nm to 700 nm) (44), therefore PDMS-COO-E has potential applications in transparent electronic devices. Figure 4 illustrates the possible SME mechanism of PDMS-COO-E. The short PDMS linear chains are crosslinked by chemical covalent interactions and abundant hydrogen bonds into a 3D network. The covalent crosslinked networks of PDMS-COO-E maintain the permanent shape and resilience, whereas, at ca. 37°C the weak hydrogen bonds are broken, and the dynamics of polymer chains increase, resulting in recovering the permanent shape. Meanwhile, a large number of hydrogen bonds enable the samples to heal at temperature without external stimulus (44).

Fig. 4.

It is possible to generate light-induced SMEs in a variety of materials (18–20, 38, 40, 45), however a comprehensive overview is outside the scope of this mini-review. Light-activated SMPs (LASMPs) (46) typically use photothermal or photochemical (photocrosslinking or photocleavage) triggers for SMEs. For instance, photothermal LASMPs typically employ photo-absorber molecules and particles that convert light to heat, thereby increasing the temperature at the desired region within the LASMP. Photochemical LASMPs incorporate photosensitive molecules to create or cleave bonds during irradiation with light, imparting potentially very swift SMEs (47, 48). It is possible to improve the response time of SMPs by increasing the thermal conductivity with various conductive additives (49). However, the heating and cooling of materials with substantial thickness takes time, which can be minimised by using light to trigger transitions in LASMPs (46). It is also possible to generate multistimuli-responsive materials using components of the materials that respond to different wavelengths of light (for example, one wavelength of light to induce photocrosslinking, while a second wavelength of light cleaves bonds). It is possible to produce materials that can be reversibly switched between an elastomer and a rigid polymer employing polymers containing cinnamic groups (48) that can be fixed into pre‐determined shapes utilising ultraviolet (UV) light illumination (>260 nm), and then recovered their original state when exposed to UV light at a different wavelength (<260 nm) (49). Figure 5 depicts one example of the process of LASMPs shape recoverability.

Fig. 5.

It is possible to generate electrically-induced SMEs in a variety of materials (18, 20, 50–55), however a comprehensive overview is outside the scope of this mini-review. A variety of electrically conductive materials including organic electronic materials (including conductive polymers such as polypyrrole (PPy) (28, 56–58) and carbon nanotubes (CNTs) (59, 60)) and inorganic electronic materials (such as alloys, metals (61) and silver nanowires (NWs)), have been incorporated in materials displaying SMEs to impart swift triggers to the SMEs, enabling a variety of interesting applications.

Highlighting some of the potential of electrically-induced SMEs, electrically-induced SMP composites incorporating shape-memory polyurethane (SMPU) and Ag NWs in a bilayer structure exhibits flexibility and electrical conductivity (62–64), which may find applications as capacitive sensors, healable transparent conductors and wearable electronics (65). In such materials the Ag NWs are randomly distributed on the surface layer of the composite to form a conductive percolating network that retains conductivity (200 Ω sq⁻¹) after a 12% elongation. However, continual increase in elongation causes a dramatic increase to the composites’ resistance value and the eventual loss of electrical conductivity (66). When the material (deformed or in its original state), is connected to a typical circuit, a low voltage of 1.5 V was enough to activate a light-emitting diode (LED) (65). The composites possessing a higher Ag NW content exhibited a higher recovery ratio and reached the maximum recovery speed quicker (66). It was assumed that all the heat from electrical (Joule) heating was absorbed by the sample, i.e. no convective loss (67). Therefore, the composites with higher Ag NW content had a lower resistance value and the heating effectiveness was promoted. Heat initiates the thermal T_trans of the SMPU leading to an improved shape recovery, and voltages as low as 5 V reverted bent composites to their original state within 3 s (66). This represents a good example of a multifunctional SMP and demonstrates the potential of SMP designs driving technological innovation. A schematic of the composite is shown in Figure 6.

Fig. 6.

Polymeric blend SMPs can be constructed from two immiscible polymeric matrices. The shape-recovery of these systems can be controlled with relative ease by varying the ratio of the polymer blends (68). However, this process may have adverse effects on shape-memory characteristics and diminish the material’s performance, thereby limiting potential applications. On the other hand, SMP functionality may also be enhanced with other capabilities. For instance, it was recently reported that a new hybrid SMP was developed by combining single-walled CNTs (SWCNT) into a poly(lactic acid) (PLA) and thermoplastic polyurethane (TPU) SMP system, containing poly(ethylene glycol) (PEG) plasticiser (68). By incorporating PEG, the hybrid SMP composite achieved a lower temperature T_g (for example, 10 wt% of PEG lowered T_g of the PLA/TPU sample from 60°C to 40°C), meanwhile enhancing the dispersion of SWCNT (for instance, even at 4 wt% of SWCNT loading, 100% SMP tensile strain was possible, much greater than previously reported electrically-induced SMP studies, i.e. 12% discussed previously). In addition, the presence of the SWCNT can stabilise the SMP system and enhance its shape-fixity after deformations at room temperature conditions (68). Furthermore, the material was capable of a conductivity above 10⁻⁷ S cm⁻¹, which can be considered conductive, as documented (68). The PLA/TPU SMP composite (2 wt% SWCNT and 10 wt% PEG) also achieved shape-recovery, via Joule heating derived from electricity, in 80 s when currents of 125 mA were applied. The high stiffness of SWCNT filler results in decreasing shape-recovery performance because of the hindrance on the polymer chain movements (68). As a result, under room temperature stretching, the R_f and R_r values obtained were ca. 80% and 65%, respectively. Therefore, when its shape-recoverability is compared to other SMPs (shape-recovery ratios being upwards of 98%), the material is lacking. However, the hybrid SMP composite does possess electroactive ability, thus a trade-off relationship between shape-memory/recovery and electroactive ability needs to be carefully considered when designing similar materials.

It is possible to generate water-induced SMEs in a variety of materials (18, 20, 38, 39, 69–72), however a comprehensive overview is outside the scope of this mini-review. Water is an important stimulus due to the fact it is abundant in a multitude of different environments, non-toxic and safe for a variety of applications.

An interesting example highlighting the potential of such materials is based on strong and flexible composite films (73) utilising the combination of a flexible interpenetrating polyol-borate network (74) and electroactive PPy (75, 76) that exchange water with the environment resulting in film expansion or contraction. The free-standing multi-functional SMP films were prepared by electropolymerisation of pyrrole in the presence of the polyol-borate complex (composed of pentaerythritol ethoxylate (PEE) coordinated to boron(III)) (74), wherein the interpenetrating network enables water-gradient-induced displacement, converting chemical potential energy in water gradients to mechanical work (73), and results in adaptation of the architecture in response to an environmental condition change (i.e. sorption and desorption of water which drives the SME process, as depicted in Figure 7). The design of the water-responsive PPy-PEE composites was creatively applied to prepare actuators and generators driven by water gradients. The film actuator can generate contractile stress up to 27 MPa, lift objects 380 times heavier than itself and transport cargo 10 times heavier than itself (73). An assembled generator associating the actuator with a piezoelectric element driven by water gradients, outputs alternating electricity at ca. 0.3 Hz, with a peak voltage of ca. 1 V (73). The electrical energy can be stored in capacitors that could power micro and nanoelectronic devices (73). The SME mechanism for this SMP differs to that of Figure 1 and Figure 2, utilising water as the shape-memory trigger for T_trans, and the original and deformed state interchange automatically via water sorption and desorption states. However, the shape-memory phenomenon remains the same, further demonstrating the potential of SMP designs driving technological innovation.

Fig. 7.

It is possible to generate pH-induced SMEs in a variety of materials (18, 20, 38, 77–80), however a comprehensive overview is outside the scope of this mini-review. An example of the interesting properties of such pH-responsive SMPs and their composites is produced by blending poly(ethylene glycol)-poly(ε-caprolactone)-based polyurethane (PECU) with functionalised cellulose nanocrystals (CNCs) displaying pH responsive pyridine moieties (CNC-C₆H₄NO₂) (81, 82). At high pH values the pyridine is deprotonated, facilitating hydrogen bonding interactions between the pyridine groups and hydroxyl moieties on the cellulose, whereas at low pH values, the protonation of the pyridine moieties diminishes these interactions. By comparison, carboxylic acid functionalised cellulose nanocrystals (CNC-CO₂H) responded to pH variation in the opposite manner (83–85). When the functionalised CNCs were combined with PECU polymer matrix to form a nanocomposite network, the mechanical properties of PECU were improved along with the pH-responsiveness of CNCs (85). The percolated network of pH-sensitive CNC in the polymer matrix served as the switching units for the shape-memory composite, the SME process of this material is depicted in Figure 8 (81, 82). The CNC serves as the switching unit of the SMP composite within the matrix of PECU which is physically crosslinked and microphase separated to yield the net points. Such pH-responsive shape-memory nanocomposites have promise in the design of biomaterials for biomedical applications (for example, SMP-based drug delivery systems triggered by transition along the digestive tract) (83).

Fig. 8.

It is possible to generate magnetically-induced SMEs in a variety of materials (18, 20, 38, 86–88), however a comprehensive overview is outside the scope of this mini-review. The SMP devices discussed thus far are being researched with potential application into wearable electronics, nanoelectronics (such as actuators), biomaterials and biomedical devices (1, 18, 19). However, in some instances (such as medical devices) a key challenge is the design and implementation of a safe and effective method of actuating a variety of device geometries in vivo. As previously discussed, a pH‐triggered SMP design can be potentially effective when utilised as drug delivery devices, when the target environment has a substantial pH difference (for instance, the digestive system) (83). However, the development of electrically and thermally-triggered devices that safely operate in vivo is difficult due to the (generally) high temperatures these SMPs can reach (relative to biological systems). For instance, the electroactive PLA-TPU SMP composite (2 wt% SWCNT and 10 wt% PEG) reaches temperatures greater than 70°C in 80 s as shape-recovery is achieved (68).

An alternative method of achieving actuation is inductive heating by loading ferromagnetic particles into an SMP system and exposing the doped device to an alternating electromagnetic field (89), benefiting from the innate thermoregulation offered by a ferromagnetic material’s Curie temperature (T_c, at which a ferromagnetic material becomes paramagnetic, losing its ability to generate heat via a hysteresis loss mechanism) (90). By using particle sizes and materials that will heat mainly via a magnetic hysteresis loss mechanism over an eddy current mechanism, it is possible to have an innate thermoregulation mechanism that limits the maximum achievable temperature to T_c (89). Therefore, by selecting ferromagnetic particle materials with a T_c within safe medical limits, Curie thermoregulation eliminates the danger of overheating and the need for a feedback system to monitor implanted device temperatures (89). However, this technology is not only useful when applied to medical devices. Other useful applications include remote activation in which wires or connections to SMP devices could be eliminated, simplifying the design and reducing possible points of failure. An example of this method of actuation involves the incorporation of 10% by volume nickel zinc ferrites (for example C2050 (Ceramic Magnetics Inc, USA) and CMD5005 (Ceramic Magnetics Inc), particle sizes ca. 50 μm with spherical shapes) with an ester-based thermoset polyurethane (PU) SMP, MP5510 (SMP Technologies Inc, Japan) (T_g of 55°C) (89). The magnetic field utilised to achieve shape-recovery was a copper-wound solenoid coil with a 2.54 cm diameter, 7.62 cm length and with a total of 7.5 turns. The unit possessed an adjustable power setting capable of outputting 27 W to 1500 W at between 10 MHz and 15 MHz frequency (note: this high frequency may induce eddy currents in the tissue, causing undesirable direct heating of the human body in medical applications) (91). However, an alternating magnetic field of 12.2 MHz and approx. 400 A m⁻¹ (centre of the inductive coil) at room temperature was used for actuation to demonstrate proof of concept for the device. It was also reported that clinically useable frequencies (50 kHz to 100 kHz) (92) should still be effective (89), albeit this could result at a different quantitative level (i.e. shape-recovery and memory performance may be reduced). Furthermore, C2050 and CMD5005 possess a T_c of 340°C and 130°C, respectively. These temperatures exceed physiological limits and are therefore not practical for medical devices currently, however, these doped SMP composites did not exceed temperatures above the respective Ni Zn particle T_c values, signifying a thermoregulation characteristic. In addition, it was stated that the 10% volume of Ni Zn particles did not impact the SMPs shape-memory properties significantly (89). The T_g increased from 55°C to 61.4°C and the shape-recovery of a flower and foam-based device was achieved within 15 s to 25 s, at a temperature range of 23°C to 78.6°C. The potential applications for this device are illustrated in Figure 9. Optimisation of this device/design is still required before it can be considered clinically viable, however, this SMP composite highlights very interesting characteristics, remote activation (via magnetic fields inducing thermally-triggered actuation) and thermoregulation (via T_c temperature of the material being employed).

Fig. 9.

As highlighted above, SMP materials are diverse and respond to many different external stimuli (including temperature, light, electricity, water, pH and electromagnetic fields) by a variety of mechanisms. Although SMPs can be classified based on their composition and structure, stimulus and shape-memory function, their classification can be difficult, as organising these polymeric smart materials into one or two simple categories is an over-simplification of their abilities and characteristics (93).

SMPs are considered to consist of net points and molecular switches or stimuli sensitive domains. These net points can be achieved by covalent bonds (chemically crosslinked) or intermolecular interactions (physically crosslinked). Chemically crosslinked SMPs involve suitable crosslinking chemistry and are referred to as thermosets (94, 95). Physically crosslinked SMPs involve a polymer morphology consisting of at least two segregated domains and are referred to as thermoplastics (96). The network chains of the SMP can be either amorphous or crystalline and therefore, the T_trans is either a T_g or T_m. The network architectures are thought to be constructed through crosslinking net points, with polymer segments connecting adjacent net points. The strongly crosslinked architectures ensure the polymer can maintain a stable shape on the macroscopic level (93). Thermoplastic polymers exhibit a more reversible nature (97), meaning the physical crosslinked net points can be disrupted and reformed with relative ease. The interconnection of the individual polymer chains in a physically crosslinked network is achieved by the formation of crystalline or glassy phases. For thermoset polymers, the individual polymer chains are connected by covalent bonds and are therefore more stable than physically crosslinking networks and show an irreversible nature (98–100).

Regarding thermo-responsive SMPs, they can be classified according to the nature of their permanent net points and the T_trans related to the switching domains into four different categories: (a) physically crosslinked thermoplastics, T_trans = T_g; (b) physically crosslinked thermoplastics, T_trans = T_m; (c) chemically crosslinked amorphous polymers, T_trans = T_g; (d) chemically crosslinked semi-crystalline polymer networks T_trans = T_m (93).

For the physically crosslinked SMPs, the formation of a phase-segregated morphology is the fundamental mechanism behind the thermally-induced SME of these materials (93, 99). One phase provides the physical crosslinks while the other acts as a molecular switch. They can be further classified into linear polymers, branched polymers or a polymer complex. Linear SMPs may consist of block copolymers and high molecular weight polymers, the typical physically crosslinked SMP is linear block copolymers, such as PU. In polyesterurethanes (PEU), oligourethane segments are the hard-elastic segments, while polyester serves as the switching segment (99).

For chemically crosslinked SMPs, two methods are commonly used to synthesise covalently crosslinked networks (36, 41). The first method relies on addition of a multi-functional crosslinker during polymerisation (41), whereas the second method relies on the subsequent crosslinking of a linear or branched polymer (36). The networks are formed based on many different polymer backbones. Covalently crosslinked SMPs possess chemically interconnected structures determining the original macroscopic shape. The switching segments of these materials are generally the network chains between net points, and a T_trans of the polymer segments is used as the shape-memory switch. The chemical, thermal, mechanical and shape-memory properties are determined by the reaction conditions, curing times, the type and length of the network chains and the crosslinking density (35). Comparing physically crosslinked SMPs with chemically crosslinked SMPs, the chemically crosslinked SMPs often show less creep, thus, any irreversible deformation of the polymer during shape recovery is less. This is because covalent crosslinked networks are more stable than physical crosslinked networks. As a result, chemically crosslinked SMPs usually show better chemical, thermal, mechanical and shape-memory properties than physically crosslinked SMPs (96). For example, the shape recovery ratio of thermoplastic SMPU is usually in the range of 90% to 95% within 20 shape recovery cycles, and the elastic modulus is between 0.5 GPa and 2.5 GPa at room temperature (26). Additionally, when exposed to air, it is sensitive to moisture and therefore possesses unstable mechanical properties. In contrast, an epoxy SMP shows better overall performance as a shape-memory material. The shape recovery ratio typically reaches 98–100%, the elastic modulus between 2 GPa and 4.5 GPa, and it is generally stable in the presence of moisture (26). Thermoplastic SMPs (such as SMPU) are mostly researched and used as functional materials at a small scale, such as for biomaterials (30, 97). However, thermosetting SMPs (for example styrene-based SMP (SSMP) and epoxy SMPs) are generally used for structural materials, such as space deployable structures and automobile actuators (97, 98).

The approaches to designing different shape-memory functions become more abundant as scientists and engineers better understand the SME mechanism of SMPs. For instance, discussed thus far are examples of SMPs with polymeric blends, addition of crosslinking species, incorporation of electroactive and ferromagnetic substances. All of which enhances an SMP device functionality, enabling unique and interesting characteristics which can be tailored to a plethora of applications (for example, self-healing and wearable electronics, drug delivery and implantable medical devices) (101–110). Further still, one-way SMEs, two-way SMEs (such as dual shape PPy-PEE, discussed previously), triple SMEs, multiple SMEs and even temperature-memory effects (TMEs) have been widely investigated in SMPs (34). As the types of SMP materials increasingly diversify, two and even three different types of shape-memory functions can be achieved simultaneously in the same SMP material (34, 111). These types of materials can usually be achieved when combining different SMPs possessing different properties. A schematic of one-way, two-way, dual shape and triple shape functionality SMPs is shown in Figure 10, and an integrated insight into the classification of SMPs is shown in Figure 11.

Fig. 10.

Fig. 11.

An example of a selective triple shape multicomposite SMP was documented to incorporate a neat SSMP (112) and two SSMP composites (113). One incorporated iron(II, III) oxide nanoparticles while the other CNT nanoparticles. This unique SMP composite successfully possessed three different regions within the sample: neat SSMP, SSMP-Fe₃O₄ and SSMP-CNT. Because of this, the material also possessed distinct shape-memory capabilities with different triggers. For instance, the material was documented undergoing a three-step shape-memory recovery process, subjected to an alternating magnetic field of 30 kHz, a radio frequency (RF) field of 13.56 MHz and direct oven heating at 130°C (113). Furthermore, the R_f and R_r for the original shape to the first temporary shape (and back to the original shape) was reported at 93% and 93%, respectively. Meanwhile, the R_f and R_r for the first temporary shape to the second temporary shape (and back to the first temporary shape) was at 95% and 99%, respectively (113). The SME mechanism for this multicomposite is represented in Figure 12 and it was concluded that this unique material has promising characteristics to be used in biomimetic materials. Examples of applications of SMP-based materials and their composites are highlighted in Table I.

Fig. 12.

As the understanding of SMPs continually develops among the academic and industrial communities, the generation of new and potentially innovative SMPs will be more rapid while we realise the full potential of these materials. SMPs are one of the most interesting of polymer classes within the field of functional polymers. In addition, SMP composites can enhance the already impressive capabilities of SMPs by imparting new functional characteristics, broadening the potential applications of these materials and enabling a multipurpose material. SMPs and their composites are capable of industrially important applications (examples of which include: self-healing (101–104), generators driven by water gradients (73), sensors (72), task-specific medical devices (18, 105) and wearable electronics (106–110), a few examples of which are highlighted in Table I. The literature published to date de-risks investment from governments and industry to raise the technology readiness levels towards products on the market.

The massive discharge of volatile organic compounds (VOCs) has a great negative impact on the environment (1). Toluene is a common pollutant in VOCs and is produced in a large number of industrial activities, such as chemical refining and dye processing. Toluene stimulates skin and mucosa, and when it reaches a certain high concentration, it also causes paralysis of the human nervous system. Compared with photocatalysis and chemical oxidation, using a biofilter to remove VOCs is more economical and environmentally friendly (2). More important is that it does not produce secondary pollution. The key element to ensure the removal capacity of the biofilter is the preparation of the filler. As a carrier for the transfer of pollutants, the filler can provide a suitable growth environment for microorganisms (3).

Micro-embedding technology is a method which uses physical or chemical methods to keep microorganisms in a defined space, ensuring microorganisms with high activity. The principle of using micro-embedding technology to degrade VOCs is to use a hollow porous membrane to intercept microorganisms inside the filler. The pore size of the hollow porous membrane is smaller than that of microbial cells, so that microorganisms can be embedded. The VOCs can enter the interior of the embedded carrier freely due to the small particle size, and the degradation products can flow out of the carrier through the pore size (4, 5).

A large number of studies have been carried out on different types of fillers. Chen et al. (6) used a two-layer biofilter filled with new mixed packing materials to remove hydrogen sulfide gas. Dumont et al. (7) prepared a nutritional slow-release filler (UP20) to biodegrade H₂S. In the above studies, the fillers were not embedded with microorganisms. The concentration of microorganisms in the filler was small, and the removal efficiency of the biofilter was low in the start-up phase, resulting in a longer start-up period. Zhu et al. (8) used a composite packing material with functional microorganisms to remove H₂S. However, toluene does not biodegrade easily due to the presence of a benzene ring. Zuo et al. (9) found that engineered P. putida could simultaneously degrade organophosphates, pyrethroids and carbamates. Muñoz et al. (10) studied the long-term performance and stability of P. putida in a toluene removal bioreactor. The above studies have found that P. putida is highly effective in degrading organics containing benzene rings.

However, there is a lack of studies on filler micro-embedded P. putida for toluene biodegradation. Existing problems with biofilters packed with fillers include bed clogging, low biomass concentration and pressure drops. These problems become more prominent when the biofilter is operated under high VOC loading rates or long-term operation (11). For example, Ryu et al. (12) found that the benzene removal efficiency of a well-designed biofilter decreased from greater than 90% to approximately 75% after 27 days of operation due to clogging caused by the excess growth of biomass.

The main objective of this study was to evaluate the performance of a self-developed filler micro-embedded with P. putida for toluene removal under various inlet loading rates. The variations in start-up period, pressure drop, biomass concentration and tolerance to transient shock loading were monitored throughout the experiments. Special attention was paid to the analysis of the microbial community attached to these fillers and to monitoring the evolution of the microbial community in various periods.

2.1 Preparation of Filler

2.2 Experimental Setup

2.3 Toluene Concentration Analysis

The determination of toluene concentration was carried out by adsorption of activated carbon and desorption of carbon disulfide, and then the toluene gas was injected into a gas chromatograph (GC-2014, Shimadzu, Japan) equipped with a packed column (free fatty acid phase (FFAP) capillary column, 30 m × 0.25 mm × 0.25 μm) and a flame ionisation detector (FID). The gas chromatography nitrogen was used as the carrier gas with a flow rate of 1 ml min⁻¹. Temperatures of the injection port, column and detection port were set to 150°C, 65°C and 150°C, respectively. Gas samples were collected from the inlet and outlet of the biofilter with a gas-tight syringe and injected into the GC daily (14). Data were obtained from the workstation by automatic comparison of the peak area of the inlet and outlet samples with the baseline of toluene. The performance of the biofilter was evaluated in terms of (%) RE and the elimination capacity (EC) as a function of toluene loading. The RE and EC were calculated as in Equations (i)–(iii):

(i)

(ii)

(iii)

where the C_in and C_out are the inlet and outlet toluene concentration (mg m⁻³), the V is the volume of the whole biofilter (l) and Q is the gas flow rate (l min⁻¹).

2.4 Physical and Chemical Property Analysis

2.5 DNA Extraction and Sequencing

3.1 Physicochemical Properties of the Filler

3.2 Start-up Performance

3.3 Continuous Biodegradation Performance

3.4 Tolerance for Transient Shock Loading

3.5 Biomass Concentration and Pressure Drop in the Biofilter

To explore the bacterial communities in the biomass attached to BF1, genetic sequencing analyses were carried out. Sequencing of 16S rRNA genes amplified from the active bacterial communities during the operational stages revealed 21 phyla, 41 classes, 96 orders, 184 families and 347 genera (28, 29). The community analysis at phylum level of the fillers is shown in Figure 7. The four operational stages were sampled at the 25th day, the 65th day, the 95th day and the 145th day, where the 25th day, the 65th day and the 95th day had a different EBRT and the same inlet toluene concentration, and the 145th day was after two interference-shutdown experiments. The dominant phyla were Firmicutes (63.4 ± 8.7%), followed by Actinobacteria (14.6 ± 3.9%) and Proteobacteria (10.1 ± 4.2%). With decreased EBRT, the abundance of Firmicutes remained high, but the abundance of Actinobacteria decreased, and the abundance of Proteobacteria increased. This is mainly due to a reduction in residence time leading to the inability of microorganisms to fully utilise toluene, and a reduction in the carbon source leading to a change in the proportion of microorganisms (30). After two interference-shutdown experiments, the abundance of Bacteroidetes increased and the normal microecological balance was broken, which indicated that Bacteroidetes is a sensitive biological indicator, similar to the results found by Wolińska (31). Using this indicator (the increase in Bacteroidetes), it can be judged whether the biofilter is in an unstable state, which would provide some guidance for practical engineering applications.

Fig. 7.

In the four operational periods, few Pseudomonas (abundance less than 1%, as shown in Figure S3) were found in the sampling of the above four periods. As the inlet loading rate increased, the abundance of Pseudomonas genus increased from 4.7 × 10⁻⁴ to 1.9 × 10⁻³. After two intervention-shutdown experiments, the abundance of Pseudomonas genus decreased to 8.5 × 10⁻⁵, which indicates that the biofilter was not in a sterile environment and that there are other microorganisms competing with the P. putida added to the filler. When the environmental conditions and the nutrients in the biofilter became unsuitable for the added microorganisms and were suitable for other microorganisms, the other microorganisms were activated and enriched (32). However, in the start-up phase, the biofilter embedded with P. putida started quickly, and the removal efficiency of toluene remained high, which indicated that the added P. putida contributed to the efficient operation of the biofilter (33). These results indicated that the biomass could maintain itself by microbial community changes, and the rapid re-adaptation of the biofilter could contribute to the activity retention of its biomass during the starvation period.

A composite filler micro-embedded with P. putida was prepared and evaluated for the biodegradation of toluene. The biofilter packed with the fillers could start up quickly with 85% RE on the eighth day, and tolerate substantial transient shock loadings. The RE of the biofilter remained above 90% when the EBRT was 18 s and the intake load was not higher than 41.4 g m⁻³ h⁻¹. In the experimental period of 145 days, no filter plugging phenomenon was observed. Moreover, the high removal efficiency and elimination capacity contributed to rich bacterial communities for the efficient biodegradation of toluene. The communities mainly included Firmicutes, Actinobacteria and Proteobacteria, and the abundance of Bacteroidetes increased significantly during the recovery period. The composite filler exhibited favourable physicochemical properties in this experiment and its practicability in industrial engineering should be further investigated.

Acknowledgments

The authors would like to acknowledge the support of the National Natural Science Foundation of China (No. U1304216), the Science and Technology Plan of He’nan Province, China (No. 122102310366), the University Key Research Project of He’nan Province, China (No. 19A610002 and 19A150010), and the China Postdoctoral Science Foundation (No. 2018M632794).

As humans, we seem to desire structure, relationships and laws to understand the universe. Through increased understanding, we can solve the problems and challenges that we perceive. This method and the output are given the label of science. At its best, science provides exquisite understanding, life-changing solutions or sometimes both.

The downside of the structures and rules we impose is that they can create inertia. Because the structure or rule served a purpose in the past, we can be more willing to stand by it blindly than openly seek the understanding or solutions we truly desire; a dynamic seen in the natural and social sciences alike and revealing more about human nature than the universe. One such structure is that of the disciplines within science. We should challenge ourselves to be very clear on the purpose of any structures we adhere to and be ready to remove barriers that get in the way of progress. One such example is uncovering the fertile ground of interdisciplinary research. In recent years interdisciplinary research has been of increasing importance across the sciences. Volume 64 of the Johnson Matthey Technology Review started a celebration of interdisciplinary science by looking at when chemistry collaborates with physics (1) and in this issue, we will celebrate the cross-disciplinary contributions of biology with other fields.

This wide-ranging issue explores topics such as: what we can continue to learn from organisms in unusual environments; how we might leverage biology in artificial situations; and even how we manage the interface between human-made, controlled systems and the outside world. In particular, the diversity of industrial applications is striking. Some are familiar to Johnson Matthey and this journal such as fine chemical synthesis, while others, such as hides and textiles, show that as boundaries within science are removed, previously distant industries will have much to learn from one another.

I have reflected on three themes as this issue has come together. There are numerous examples on each theme and I would challenge the reader to think “what next?” for each:

This third theme is perhaps the most important as it turns niche expertise into something accessible to scientists across fields. Understanding the technology may be beneficial but is not a prerequisite to accessing it. Biology follows favourably in the footsteps of computing in producing such platform technologies and it is an attribute that perhaps we should value and prioritise more in other fields. To expand on this theme, it is exciting to look both backwards and forwards to the contributions made possible by platform technologies from the field of biology. Often these point back to unlocking our understanding of the structure and function of DNA at a molecular level and have resulted in some of the most impactful scientific contributions of the last 50 years or so. Our health has been a significant beneficiary of these advances with cancer drugs providing an illustrative case study. Looking back, we can see recent classes of therapeutics that were significantly enabled by this flow of understanding and platform technologies such as tyrosine kinase inhibitors and antibody-based therapies (2). Most importantly, patient outcomes have improved substantially in part, thanks to these therapies (3).

Looking to the future, gene and cell therapies appear to be following a similar pattern and will hopefully deliver similar patient benefits. Outside of cancer treatments and healthcare, we can see many industries set to benefit from being able to access biological understanding and technologies. This is particularly as we seek to learn from biology and reduce our impact on the planet by using materials and energy in keeping with what Earth can sustain.

As you read through this issue, I hope you enjoy reading something outside of your current field. I would take you back to my earlier challenge and see if you can gain any greater insights by not seeing the separation between your field and those of the authors. Rather, question what you can leverage, what you can learn and what next?