12.1 Introduction

Mother Nature displays numerous examples of materials that can autonomously change their shape in response to external stimuli. Examples include the conifer pinecone and the wheat awn, in which the hydration-dictated microscopic change in the fibril orientation governs the macroscopic close–open shape transition [1]. These kind of materials are often referred to as shape-changing materials, and this stimuli-responsive shape change of materials is essential for the survival of such plants and other living organisms.

Shape-memory systems represent an exciting class of “smart” materials that possess similar, unique shape-changing ability upon the application of an external stimulus (e.g., temperature, pH, light, etc.) [2, 3]. One important feature that distinguishes shape-memory materials from shape-changing materials is the programmable nature of the shape change [4, 5]. Shape-memory materials have the ability to program the temporary shape even after the removal of the applied force or the external stimuli used to change the shape, and recover to the original shape when triggered by the external stimuli. It is therefore reasonable to consider that shape-memory materials are subsets of shape-changing materials (Figure 12.1).

The shape-changing process in both shape-changing and shape-memory materials involves dynamic macroscopic movements. It is well known that the microarchitectures of the biological systems in the conifer pinecone and the wheat awn ultimately govern their ability to dynamically change their macroscopic shape [1], which suggests the importance of material architectonics to determine the performance. Therefore, it is obvious that the design principle based on materials architectonics is important to fabricate high-performance shape-memory materials. Since conformational and structural changes at the molecular level within these artificial systems also result in macroscopic actuations, the artificial shape-memory materials are not so dissimilar from the living systems that change shapes in response to external stimuli. The advancements in the field of nanotechnology have made it possible to precisely regulate the nanostructures of materials, and novel shape-memory materials with multiple-memory ability and multifunctionality can be designed on the basis of the materials nanoarchitectonics. This is a novel concept to construct functional materials with nano-units [7–9].

Recently, various types of shape-memory materials including alloys [10], ceramics [11, 12], polymers [2, 3, 5, 13], and supramolecular systems [14, 15] have been prepared. The most remarkable and extensively researched shape-memory materials are shape-memory alloys (SMAs). Tough metallic SMAs have already gained attention as biomedical devices and as material alternatives to conventional actuators in automotive and robotics industries. The soft shape-memory materials such as polymer and supramolecular systems have also attracted tremendous research interest, as evident from the exponential increase in the relevant scientific publications [16]. This is attributed to the structural diversity and the variation in the materials that allow us to tune various parameters of the shape-memory property precisely, thus improving the feasibilities of many future applications.

This chapter highlights the recent advancements in the design and fabrication of soft shape-memory materials, especially the polymeric system. First, the basics of the shape-memory effect (SME) in polymer systems (Section 12.2) is briefly described. In the subsequent section is classified the shape-memory polymers (SMPs) from the nanoarchitectonics point of view (Section 12.3), and the variant SMPs with different hierarchy and architecture have been discussed from the macroscopic point of view (Section 12.4). Next, some of the recent applications of the SMPs (Section 12.5) have been highlighted, and, finally, the future trends for the utilization of the SMPs have been summarized and discussed (Section 12.6).

12.2 Fundamentals of Shape-Memory Effect in Polymers

As discussed in the introduction, shape-memory materials are subsets of shape-changing materials and can exhibit programmable shape shifting (Figure 12.1). This is quite different from the pine cones and hydrogels (except for shape-memory hydrogels) since the shape shifting in shape-memory materials is defined by the process of material fabrication and the environmental thermodynamics. Therefore, molecular or nanoscale switches have to be incorporated into these materials to achieve well-regulated programmable shape shifting.

The SMPs are fascinating systems due to the abundant choices and structural flexibilities. In other words, there is infinite scope for design and no limitation on the targeted property and function. Although various types of SMPs have been designed, one major class is the thermally induced one-way dual-type SMP, as shown in Figure 12.2. The term “thermally induced one-way dual shape-memory effect (SME)” signifies that the materials are able to shift between two programmable shapes (dual), from temporary to permanent, in an irreversible manner (one-way) in response to changes in the temperature. Therefore, the one-way dual SME is an established system for the SMPs. However, researchers have also developed more sophisticated systems that exhibit two-way (reversible), triple-, and multi-SME. The performances of these systems strongly depend on the design and the structure of the molecular skeletons and the switches, clearly indicating the importance of materials nanoarchitectonics. For example, in (semi)crystalline two-way SME, the skeletal structure of the crystallized geometry and the orientation of the molecular switching domain in the system are key factors that precisely control the programming process to make a temporary shape. In fact, the two-way SME is induced by the combination of the processes of crystal-induced elongation and melting-induced contraction at the particular conditions [19–22]. On the other hand, the multi-SME is achieved by incorporating multiple molecular switching domains or utilizing broad molecular transition behaviors such as glass transition [5, 18, 23]. The continuous efforts directed toward improving the tunability of the SME will improve the performance of the SMPs and provide opportunities for new applications.

12.3 Categorization of Shape-Memory Polymers on the Basis of Nanoarchitectonics

The SMP systems are classified on the basis of the mode of the SME as one-way, dual (two-way), and multi-SME. They can also be categorized on the basis of the stimuli-responsiveness of the materials to induce the shape-memory behaviors. However, this is determined by the molecular design used to build the system, and the temperature change which mainly triggers the SME. The thermally driven SMP systems are generally categorized into physically (or chemically) cross-linked glassy (or (semi)crystalline) polymers since the network architecture, the molecular component forming the network, and the switching domain crucially affect the performance (Figure 12.3). One of the major types of the thermally driven SMPs is the physically cross-linked network with the temperature required for the reversible transition (T_switch) within amorphous and (semi)crystalline regions corresponding to the glass transition temperature (T_g) and the melting temperature (T_m), respectively (Figure 12.3a). In this system, a block copolymer is the most prominent building block, and the network is stabilized by hard segment domains that serve as physical cross-linking points [24, 25]. When heated above the maximum temperature stabilizing the permanent shape (T_perm), the network is broken down and molten but this phenomenon, in turn, enables reshaping and reprocessing of the network structure. Another major type of the thermally driven SMP is the chemically cross-linked network with the T_switch corresponding to the T_g or the T_m (Figure 12.3b). This type of SMP exhibits excellent shape-memory ability, and its shape-recovery feature is remarkable due to the chemical cross-linking. However, it is difficult to reshape these materials, which is in contrast to the physically cross-linked system. The T_m-based SMPs generally exhibit sharper transitions than the T_g-based ones, which makes it possible to achieve fast shape-recovery actuation within a narrower temperature range. As an example, we have successfully fabricated chemically cross-linked poly(ϵ-caprolactone) (PCL) [26, 27] which is a well-known, biodegradable semicrystalline polymer. The switching temperature, T_m, of the cross-linked PCL can be easily adjusted to the physiological temperature range by tailoring the branching structure and the length of the molecular chain of PCL. This remarkable designing of the PCL nanoarchitectonics not only improves the thermal properties but also the mechanical properties, the biodegradability, and the shape-memory ability.

Considering the potential applications of the SMPs, the functionality of these materials should be improved without the loss of the shape-memory ability. Hence, the development of multifunctional SMP is promising and a highly interesting challenge for basic and applied research. The approach of combining two or more materials including both organic and inorganic materials has become the gold standard for introducing multifunctionality in the SMPs. From the standpoint of the network structure, (semi)interpenetrating networks (IPNs) or blended structures [28, 29], and composite/hybrid networks with other functional materials [30–32] are very efficient for the fabrication of SMPs with multifunctional properties (Figure 12.3c,d). Here, the solubility and the dispersibility of the selected components in the polymer network strongly influence the properties of the final material. Therefore, it is apparent that the nanoscale regulation of the network structures and the arrangement of the components inside the network, that is, the network nanoarchitectonics govern the properties and the functionality of the shape-memory materials at the macroscopic level.

12.4 Shape-Memory Polymers with Different Architectures

The SMPs have been usually prepared in the form of dense bulk materials; however, other forms, such as fibers, surfaces, and particles, have been developed recently. This has opened up a new paradigm of SMPs to meet the diverse potential applications. This section briefly introduces the variant SMPs and their applications.

The SMPs can be processed in the fiber form using several methods including melt-spinning and electrospinning [33–36]. An important advantage of the SMP nanofiber is the fast shape-memory actuation due to its porous structure. In addition, the porous structure of the fibrous assemblies can be tuned to exhibit the SME. Deng et al. recently developed a shape-memory fiber-shaped supercapacitor (SFSC) with excellent electrochemical performance during deformation (Figure 12.4A) [37]. First, they prepared fibers of shape-memory polyurethane, and subsequently layers of aligned carbon nanotube sheets and gel electrolyte were fabricated on the polyurethane in a layered manner to obtain the SFSC. The capacitance of the developed SFSC was comparable to that of the carbon-based supercapacitor, and its electrochemical performance was maintained through all the shape changes. A single SFSC can therefore adapt to different material forms since the shape-memory ability enables deformation and reshaping of the original form. The structure and the function of the developed nanofibers strongly influence the shape-memory ability and other properties of the obtained macroscopic object. In other words, the three-dimensional (3D) macroscopic functions are regulated by the properties of the one-dimensional nanofibers in a hierarchical manner.

Shape-memory surfaces (SMSs) have been created by shaping and patterning of the surfaces of the SMPs. The application of the SME to surfaces will open up many applications for the SMPs since surface phenomena, such as adhesion and wettability, are strongly relevant in certain applications. In particular, SMSs are useful for biomaterials and tissue engineering applications wherein the interfacial characteristics between the material and the living system are important. As an example, the SMS is a useful tool to characterize the cellular responsiveness to dynamic topography changes that mimic the dynamic natures of disease progression, development process, and so on [41, 42]. We prepared cross-linked PCL exhibiting dynamic topography changes in response to a temperature difference of 5 °C between 32 and 37 °C [43]. Various types of surface topography changes can be induced in the adhered cell by designing an appropriate fabrication process, and successfully guiding the orientation modes as well as the rotational movement at the single-cell level [44, 45]. An SMS enabling the reorientation of temporary nanogrooves by 90° was also designed and applied to investigate cardiac monolayer behaviors (Figure 12.4B) [38]. An orthogonal change in the direction of the nanogrooves triggered the rearrangements of cellular alignment and contraction direction, suggesting the successful dynamic manipulation of cardiac functions at the tissue-like level. In most cases, direct heating was employed to induce the switching of the surface topography, which may not be appropriate for certain applications. The development of shape-memory composites is a potential strategy to overcome the issue of direct heating, and we have already succeeded in inducing the topography change by indirect heating via the photothermal effects of gold nanorods, titanium oxide, and so on [30–32]. In these composites, the materials nanoarchitectonics of the SMSs play an important role in achieving the desired functions.

Nano- and microparticles have been extensively studied, starting from their fabrication to applications, which also include biomedical applications such as drug delivery systems. Considering the miniaturization of the SMP-based devices, it is important to fabricate nano- and microparticles exhibiting the SME, which is quite challenging. Although studies on shape-changing nano- and microparticles have been reported relatively earlier [46, 47], there were no reports on the shape-memory particles until recently. Wischke et al. investigated the SME in SMP particles. They synthesized copolyester urethane, which is a multiblock-copolymer of poly(ω-pentadecalactone) (PPDL) and PCL [48, 49]. Since the crystallizing PPDL segments show higher T_m than the PCL segments, the PPDL and the PCL segments in the physically cross-linked SMP network function as permanent netpoints and switching domains, respectively. They also synthesized chemically cross-linked SMP microparticles composed basically of polyester [39]. The synthesized SMP microparticles clearly showed the SME upon miniaturization to the micrometer range; the particles were programmed into a temporary shape and then returned to the original shape in response to heating (Figure 12.4C-(a)). One of the interesting applications using this platform is to investigate the impact of the particle shape on macrophage phagocytosis because the shapes of the particles significantly affect macrophage phagocytosis via the local cell shape at the initial cell–particle contact point [50, 51]. Gong et al. successfully synthesized micrometer-sized particles with chemically cross-linked networks based on the cross-linked poly(ethylene glycol)-PCL copolymer [40]. Interestingly, these SMP particles exhibited the ability to reversibly change the shape (two-way) from spherical to elliptical either extracellularly or intracellularly within the cyclic temperature change between 43 and 0 °C (Figure 12.4C-(b)). By adjusting the shape anisotropy of the SMP particles, these particles can be utilized as novel drug delivery carriers to either avoid or promote phagocytosis by utilizing the dynamic shape-shifting property.

As discussed in this section, the specific and fascinating characteristics of the SMPs can be obtained by suitably designing the material forms. Using the same SMP, it is possible to obtain novel functions and performances of materials and applications of the SMPs by the regulation of nano- and microarchitectonics.

12.5 New Directions in the Field of Shape-Memory Polymers

Even though our understanding of the basics and the technology relevant to the design and processing of the SMPs has improved, there are only a few examples of commercially available SMPs. However, in conjunction with the progress in interdisciplinary studies, unique and featured SMPs and SME principles have started to appear.

The recently developed concept of thermally induced two-way shape-memory effect (rbSME) is useful for the fabrication of future biomedical devices [19]. In general, the two-way SME is specifically observed under constant stress, which limits its potential applications. Behl et al. developed freestanding two-way SMPs that are driven without the application of stress, and demonstrated its application as a gripper device that can reversibly catch and release a coin (Figure 12.5A) [19]. However, the accuracy, the operation mode, as well as the actuation temperature range of the two-way SMP must be improved for practical applications.

Three-dimensional (3D) printing technology has attracted significant interest because it can be used to complex geometries with precise and predesigned microarchitectures. The combination of 3D printing and SMPs has led to the development of a new technology called four-dimensional (4D) printing since the time-dependent shape shifting in SME offers an additional dimension [55]. Ge et al. successfully fabricated 3D printed SMP architectures with high resolution (up to a few microns) based on high-resolution projection microstereolithography [52]. Various complicated shapes, such as those of the Eiffel tower and fixators were three-dimensionally fabricated using photocurable methacrylate-based copolymers (Figure 12.5B). These 3D printed SMPs with complicated shapes and structures showed excellent shape-shifting properties in response to temperature changes. The 4D printing technology opens up new avenues for creating designer shape-shifting architectures for tissue engineering, biomedical devices, soft robotics, and so forth, using appropriate SMPs.

In addition, deformable and programmable micro-optical devices have been developed by combining surface SME and micro-optics (Figure 12.5C) [53]. These rewritable and switchable optical devices function as SMP holograms; they are believed to be applicable in the biomedical field as novel thermally actuated smart devices. Origami-inspired nanotechnology and manufacturing is another hot topic in materials science and its combination with SMP has led to the development of a novel sequential self-folding robot (Figure 12.5D) [54, 56]. Composite sheets were composed of several laminated layers using an SMP as the building block to achieve highly sophisticated robotic movements. These results indicate the importance of not only materials design but also systems design for the operation of assembled products.

12.6 Conclusions

This chapter discusses the basics of SME in polymer systems and its applications including some of the featured and unique developments reported recently. Since many other interesting materials/systems and unique principles have also been extensively reported, this chapter is not comprehensive. However, it is certain that the fascinating characteristics and functions of SMPs originate from the material nanoarchitectonics and this concept is very important to establish more valuable and practical systems using the SMPs. The SMP systems are expected to be useful for a different set of applications than the shape-memory alloys and ceramics in particular applications.

References

1. 1 Erb, R.M., Sander, J.S., Grisch, R., and Studart, A.R. (2013) Nat. Commun., 4, 1712.
2. 2 Behl, M., Razzaq, M.Y., and Lendlein, A. (2010) Adv. Mater., 22, 3388.
3. 3 Lendlein, A. and Kelch, S. (2002) Angew. Chem. Int. Ed., 41, 2034.
4. 4 Behl, M. and Lendlein, A. (2007) Soft Matter, 3, 58.
5. 5 Zhao, Q., Qi, H.J., and Xie, T. (2015) Prog. Polym. Sci., 49-50, 79.
6. 6 Sun, Y., Liu, S., Du, G., Gao, G., and Fu, J. (2015) Chem. Commun., 51, 8512.
7. 7 Aono, M., Bando, Y., and Ariga, K. (2012) Adv. Mater., 24, 150.
8. 8 Ariga, K. and Li, J. (2016) Adv. Mater., 28, 987.
9. 9 Ariga, K. (2016) ChemNanoMat, 2, 333.
10. 10 Khan, M.I., Pequegnat, A., and Zhou, Y.N. (2013) Adv. Eng. Mater., 15, 386.
11. 11 Swain, M.V. (1986) Nature, 322, 234.
12. 12 Lai, A., Du, Z., Gan, C.L., and Schuh, C.A. (2013) Science, 341, 1505.
13. 13 Liu, C., Qin, H., and Mather, P.T. (2007) J. Mater. Chem., 17, 1543.
14. 14 Yan, X., Wang, F., Zheng, B., and Huang, F. (2012) Chem. Soc. Rev., 41, 6042.
15. 15 Dong, R., Pang, Y., Su, Y., and Zhu, X. (2015) Biomater. Sci., 3, 937.
16. 16 Uto, K., DeForest, C.A., and Kim, D.-H. (2016) Biomaterials Nanoarchitectonics, William Andrew Publishing, p. 237.
17. 17 Behl, M., Kratz, K., Noechel, U., Sauter, T., and Lendlein, A. (2013) Proc. Natl. Acad. Sci. U.S.A., 110, 12555.
18. 18 Xie, T. (2010) Nature, 464, 267.
19. 19 Behl, M., Kratz, K., Zotzmann, J., Nöchel, U., and Lendlein, A. (2013) Adv. Mater., 25, 4466.
20. 20 Chung, T., Romo-Uribe, A., and Mather, P.T. (2008) Macromolecules, 41, 184.
21. 21 Zotzmann, J., Behl, M., Hofmann, D., and Lendlein, A. (2010) Adv. Mater., 22, 3424.
22. 22 Saatchi, M., Behl, M., Nöchel, U., and Lendlein, A. (2015) Macromol. Rapid Commun., 36, 880.
23. 23 Bellin, I., Kelch, S., Langer, R., and Lendlein, A. (2006) Proc. Natl. Acad. Sci. U.S.A., 103, 18043.
24. 24 Lendlein, A. and Langer, R. (2002) Science, 296, 1673.
25. 25 Alteheld, A., Feng, Y., Kelch, S., and Lendlein, A. (2005) Angew. Chem. Int. Ed., 44, 1188.
26. 26 Uto, K., Yamamoto, K., Hirase, S., and Aoyagi, T. (2006) J. Controlled Release, 110, 408.
27. 27 Uto, K., Muroya, T., Okamoto, M., Tanaka, H., Murase, T., Ebara, M., and Aoyagi, T. (2012) Sci. Technol. Adv. Mater., 13, 064207.
28. 28 Wu, Y., Hu, J., Han, J., Zhu, Y., Huang, H., Li, J., and Tang, B. (2014) J. Mater. Chem. A, 2, 18816.
29. 29 Liu, G., Ding, X., Cao, Y., Zheng, Z., and Peng, Y. (2004) Macromolecules, 37, 2228.
30. 30 Shou, Q., Uto, K., Iwanaga, M., Ebara, M., and Aoyagi, T. (2014) Polym. J., 46, 492.
31. 31 Shou, Q., Uto, K., Lin, W.-C., Aoyagi, T., and Ebara, M. (2014) Macromol. Chem. Phys., 215, 2473.
32. 32 Ishii, S., Uto, K., Niiyama, E., Ebara, M., and Nagao, T. (2016) ACS Appl. Mater. Interfaces, 8, 5634.
33. 33 Bao, M., Lou, X., Zhou, Q., Dong, W., Yuan, H., and Zhang, Y. (2014) ACS Appl. Mater. Interfaces, 6, 2611.
34. 34 Chen, H., Cao, X., Zhang, J., Zhang, J., Ma, Y., Shi, G., Ke, Y., Tong, D., and Jiang, L. (2012) J. Mater. Chem., 22, 22387.
35. 35 Kaursoin, J. and Agrawal, A.K. (2007) J. Appl. Polym. Sci., 103, 2172.
36. 36 Luo, X. and Mather, P.T. (2009) Macromolecules, 42, 7251.
37. 37 Deng, J., Zhang, Y., Zhao, Y., Chen, P., Cheng, X., and Peng, H. (2015) Angew. Chem. Int. Ed., 54, 15419.
38. 38 Mengsteab, P.Y., Uto, K., Smith, A.S.T., Frankel, S., Fisher, E., Nawas, Z., Macadangdang, J., Ebara, M., and Kim, D.-H. (2016) Biomaterials, 86, 1.
39. 39 Friess, F., Nöchel, U., Lendlein, A., and Wischke, C. (2014) Adv. Healthc. Mater., 3, 1986.
40. 40 Gong, T., Zhao, K., Wang, W., Chen, H., Wang, L., and Zhou, S. (2014) J. Mater. Chem. B, 2, 6855.
41. 41 Davis, K.A., Burke, K.A., Mather, P.T., and Henderson, J.H. (2011) Biomaterials, 32, 2285.
42. 42 Le, D.M., Kulangara, K., Adler, A.F., Leong, K.W., and Ashby, V.S. (2011) Adv. Mater., 23, 3278.
43. 43 Ebara, M., Uto, K., Idota, N., Hoffman, J.M., and Aoyagi, T. (2012) Adv. Mater., 24, 273.
44. 44 Ebara, M., Akimoto, M., Uto, K., Shiba, K., Yoshikawa, G., and Aoyagi, T. (2014) Polymer, 55, 5961.
45. 45 Ebara, M., Uto, K., Idota, N., Hoffman, J.M., and Aoyagi, T. (2014) Int. J. Nanomed., 9 (Suppl. 1), 117.
46. 46 Yang, Z., Huck, W.T.S., Clarke, S.M., Tajbakhsh, A.R., and Terentjev, E.M. (2005) Nat. Mater., 4, 486.
47. 47 Marshall, J.E., Gallagher, S., Terentjev, E.M., and Smoukov, S.K. (2014) J. Am. Chem. Soc., 136, 474.
48. 48 Wischke, C., Schossig, M., and Lendlein, A. (2014) Small, 10, 83.
49. 49 Wischke, C. and Lendlein, A. (2014) Langmuir, 30, 2820.
50. 50 Champion, J.A. and Mitragotri, S. (2006) Proc. Natl. Acad. Sci. U.S.A., 103, 4930.
51. 51 Gratton, S.E.A., Ropp, P.A., Pohlhaus, P.D., Luft, J.C., Madden, V.J., Napier, M.E., and DeSimone, J.M. (2008) Proc. Natl. Acad. Sci. U.S.A., 105, 11613.
52. 52 Ge, Q., Sakhaei, A.H., Lee, H., Dunn, C.K., Fang, N.X., and Dunn, M.L. (2016) Sci. Rep., 6, 31110.
53. 53 Xu, H., Yu, C., Wang, S., Malyarchuk, V., Xie, T., and Rogers, J.A. (2013) Adv. Funct. Mater., 23, 3299.
54. 54 Felton, S., Tolley, M., Demaine, E., Rus, D., and Wood, R. (2014) Science, 345, 644.
55. 55 Ge, Q., Qi, H.J., and Dunn, M.L. (2013) Appl. Phys. Lett., 103, 131901.
56. 56 Tolley, M.T., Felton, S.M., Miyashita, S., Aukes, D., Rus, D., and Wood, R.J. (2014) Smart Mater. Struct., 23, 094006.