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Journal articles on the topic 'Artificial shape memory analogs'

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Author: Grafiati

Published: 10 December 2022

Last updated: 28 January 2023

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1

Zhang, Yunlan, Mirian Velay-Lizancos, David Restrepo, Nilesh D. Mankame, and Pablo D. Zavattieri. "Architected material analogs for shape memory alloys." Matter 4, no. 6 (June 2021): 1990–2012. http://dx.doi.org/10.1016/j.matt.2021.04.015.

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2

Izawa, Hideki, Yukio Sekiguchi, and Yasuhito Shiota. "The artificial muscle from shape memory alloy." Journal of Life Support Engineering 17, Supplement (2005): 124. http://dx.doi.org/10.5136/lifesupport.17.supplement_124.

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3

Takashima, Kazuto, Jonathan Rossiter, and Toshiharu Mukai. "McKibben artificial muscle using shape-memory polymer." Sensors and Actuators A: Physical 164, no. 1-2 (November 2010): 116–24. http://dx.doi.org/10.1016/j.sna.2010.09.010.

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4

ISHIKAWA, Toshiya, and Takeshi NAKADA. "Shape Memory Alloy Actuator for Artificial Muscle." Journal of Environment and Engineering 5, no. 1 (2010): 105–13. http://dx.doi.org/10.1299/jee.5.105.

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5

Chen, Yujie, Chi Chen, Hafeez Ur Rehman, Xu Zheng, Hua Li, Hezhou Liu, and Mikael S. Hedenqvist. "Shape-Memory Polymeric Artificial Muscles: Mechanisms, Applications and Challenges." Molecules 25, no. 18 (September 16, 2020): 4246. http://dx.doi.org/10.3390/molecules25184246.

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Shape-memory materials are smart materials that can remember an original shape and return to their unique state from a deformed secondary shape in the presence of an appropriate stimulus. This property allows these materials to be used as shape-memory artificial muscles, which form a subclass of artificial muscles. The shape-memory artificial muscles are fabricated from shape-memory polymers (SMPs) by twist insertion, shape fixation via Tm or Tg, or by liquid crystal elastomers (LCEs). The prepared SMP artificial muscles can be used in a wide range of applications, from biomimetic and soft robotics to actuators, because they can be operated without sophisticated linkage design and can achieve complex final shapes. Recently, significant achievements have been made in fabrication, modelling, and manipulation of SMP-based artificial muscles. This paper presents a review of the recent progress in shape-memory polymer-based artificial muscles. Here we focus on the mechanisms of SMPs, applications of SMPs as artificial muscles, and the challenges they face concerning actuation. While shape-memory behavior has been demonstrated in several stimulated environments, our focus is on thermal-, photo-, and electrical-actuated SMP artificial muscles.

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6

TAKAGI, Toshiyuki, Yun LUO, Shinya HARA, Tomoyuki YAMABE, Shintaro AMAE, Motoki WADA, and Hirokazu NAKAMURA. "An artificial sphincter using shape memory alloy actuators." Journal of Advanced Science 12, no. 3 (2000): 337–42. http://dx.doi.org/10.2978/jsas.12.337.

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7

TAKAGI, Toshiyuki, Yun LUO, Hirokazu NAKAMURA, Shintaro AMAE, Tomoyuki YAMBE, Takamichi KAMIYAMA, Motoki WADA, Shinya Hara, Jun Makino, and Kiyoshi Yamauchi. "Application of Shape Memory Alloys in Artificial Sphincters." Proceedings of the JSME annual meeting 2000.1 (2000): 55–56. http://dx.doi.org/10.1299/jsmemecjo.2000.1.0_55.

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8

Luo, Yun, Toshiyuki Takagi, and Kenichi Matsuzawa. "Design of an artificial sphincter using shape memory alloys." International Journal of Applied Electromagnetics and Mechanics 14, no. 1-4 (December 20, 2002): 411–16. http://dx.doi.org/10.3233/jae-2002-423.

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9

Miki, Hiroyuki, Takeshi Okuyama, Shingo Kodaira, Yun Luo, Toshiyuki Takagi, Tomoyuki Yambe, and Takeshi Sato. "Artificial-esophagus with peristaltic motion using shape memory alloy." International Journal of Applied Electromagnetics and Mechanics 33, no. 1-2 (October 8, 2010): 705–11. http://dx.doi.org/10.3233/jae-2010-1176.

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10

Cui, Yande, Dong Li, Chen Gong, and Chunyu Chang. "Bioinspired Shape Memory Hydrogel Artificial Muscles Driven by Solvents." ACS Nano 15, no. 8 (August 16, 2021): 13712–20. http://dx.doi.org/10.1021/acsnano.1c05019.

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11

Luo, Yun, Toshiyuki Takagi, and Kenichi Matsuzawa. "Thermal responses of shape memory alloy artificial anal sphincters." Smart Materials and Structures 12, no. 4 (June 25, 2003): 533–40. http://dx.doi.org/10.1088/0964-1726/12/4/304.

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12

Yambe, T., Y. Luo, T. Takagi, T. Kamiyama, S. Amae, and S. Nitta. "ARTIFICIAL SPHINCTER BY THE USE OF SHAPE MEMORY ALLOY." ASAIO Journal 49, no. 2 (March 2003): 206. http://dx.doi.org/10.1097/00002480-200303000-00258.

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13

Silva, André Fellipe Cavalcante, Alexsandro José Virgínio dos Santos, Cícero da Rocha Souto, Carlos José de Araújo, and Simplício Arnaud da Silva. "Artificial Biometric Finger Driven by Shape-Memory Alloy Wires." Artificial Organs 37, no. 11 (November 2013): 965–72. http://dx.doi.org/10.1111/aor.12227.

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14

Movchan, A. A. "Combined model of phase-structural deformation of shape memory alloys." Deformation and Fracture of Materials, no. 11 (November 2020): 2–10. http://dx.doi.org/10.31044/1814-4632-2020-11-2-10.

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A combined model of inelastic deformation of shape-memory alloys for phase and structural transformations is proposed, taking into account the fundamental difference between these two mechanisms and the influence of the first mechanism on the second. In contrast to the known analogs, the model allows for non-monotonic loading processes to exceed the long arc of phase-structural deformation (an analogue of the Odqvist parameter in the theory of plasticity) of the intensity of crystallographic deformation of the phase transition.

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15

Huang, Xiaonan, Michael Ford, Zach J. Patterson, Masoud Zarepoor, Chengfeng Pan, and Carmel Majidi. "Shape memory materials for electrically-powered soft machines." Journal of Materials Chemistry B 8, no. 21 (2020): 4539–51. http://dx.doi.org/10.1039/d0tb00392a.

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16

Albanesi, M. G., and M. Ferretti. "Shape detection with limited memory." Pattern Recognition 24, no. 12 (January 1991): 1153–66. http://dx.doi.org/10.1016/0031-3203(91)90142-r.

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17

Takashima, Kazuto, Toshiro Noritsugu, Jonathan Rossiter, Shijie Guo, and Toshiharu Mukai. "Curved Type Pneumatic Artificial Rubber Muscle Using Shape-Memory Polymer." Journal of Robotics and Mechatronics 24, no. 3 (June 20, 2012): 472–79. http://dx.doi.org/10.20965/jrm.2012.p0472.

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A novel pneumatic artificial muscle actuator is presented which is based on the design of a conventional curved type pneumatic bellows actuator. By inhibiting the extension of one side with fiber reinforcement, bending motion can be induced when air is supplied to the internal bladder. In this study, we developed a new actuator by replacing the fiber reinforcement with a Shape-Memory Polymer (SMP). The SMP can be deformed above its glass transition temperature (Tg) and maintains a rigid shape after it is cooled below Tg. When next heated above Tg, it returns to its initial shape. When only part of our actuator is warmed above Tg, only that portion of the SMP is soft and can actuate. Therefore, the direction of the motion can be controlled by heating. Moreover, our actuator can be deformed by an external force above Tg and fixed by cooling it below Tg.

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18

NAKAMURA, Hirokazu, Toshiyuki TAKAGI, Yun LUO, Shintaro AMAE, Tomoyuki YANBE, Takamichi KAMIYAMA, and Motoshi WADA. "519 Development of an Artificial Sphincter Using Shape Memory Alloy." Proceedings of Conference of Tohoku Branch 2000.35 (2000): 194–95. http://dx.doi.org/10.1299/jsmeth.2000.35.194.

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19

Kim, Min‐Soo, Hye‐Sung Lee, Younggyun Cho, Jae Kyung Heo, Ying‐Jun Quan, Seung Woo Lee, Heui Jae Pahk, and Sung‐Hoon Ahn. "Surface Nanopatterned Shape Memory Alloy (SMA)‐Based Photosensitive Artificial Muscle." Advanced Optical Materials 10, no. 5 (December 23, 2021): 2102024. http://dx.doi.org/10.1002/adom.202102024.

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20

Taniguchi, Hironari. "Flexible Artificial Muscle Actuator Using Coiled Shape Memory Alloy Wires." APCBEE Procedia 7 (2013): 54–59. http://dx.doi.org/10.1016/j.apcbee.2013.08.012.

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21

Luo, Yun, Toshiyuki Takagi, Shintaro Amae, Motoshi Wada, Tomoyuki Yambe, Takamichi Kamiyama, Kotaro Nishi, Takeshi Okuyama, Toshihiko Komoriya, and Hidetoshi Matsuki. "Shape Memory Alloy Artificial Muscles for Treatments of Fecal Incontinence." MATERIALS TRANSACTIONS 45, no. 2 (2004): 272–76. http://dx.doi.org/10.2320/matertrans.45.272.

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22

Yambe, Tomoyuki, Shintaro Amae, Shigenao Maruyama, Yun Luo, Hiroyuki Takagi, Shun-suke Nanka, Akira Tanaka, et al. "Application of a shape memory alloy for internal artificial organs." Journal of Artificial Organs 4, no. 2 (June 2001): 88–91. http://dx.doi.org/10.1007/bf02481416.

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23

Shang, Jiaojiao, Xiaoxia Le, Jiawei Zhang, Tao Chen, and Patrick Theato. "Trends in polymeric shape memory hydrogels and hydrogel actuators." Polymer Chemistry 10, no. 9 (2019): 1036–55. http://dx.doi.org/10.1039/c8py01286e.

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Recently, “smart” hydrogels with either shape memory behavior or reversible actuation have received particular attention and have been further developed into sensors, actuators, or artificial muscles.

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24

Mitchell, Kellen, Lily Raymond, and Yifei Jin. "Material Extrusion Advanced Manufacturing of Helical Artificial Muscles from Shape Memory Polymer." Machines 10, no. 7 (June 22, 2022): 497. http://dx.doi.org/10.3390/machines10070497.

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Rehabilitation and mobility assistance using robotic orthosis or exoskeletons have shown potential in aiding those with musculoskeletal disorders. Artificial muscles are the main component used to drive robotics and bio-assistive devices. However, current fabrication methods to produce artificial muscles are technically challenging and laborious for medical staff at clinics and hospitals. This study aims to investigate a printhead system for material extrusion of helical polymer artificial muscles. In the proposed system, an internal fluted mandrel within the printhead and a temperature control module were used simultaneously to solidify and stereotype polymer filaments prior to extrusion from the printhead with a helical shape. Numerical simulation was applied to determine the optimal printhead design, as well as analyze the coupling effects and sensitivity of the printhead geometries on artificial muscle fabrication. Based on the simulation analysis, the printhead system was designed, fabricated, and operated to extrude helical filaments using polylactic acid. The diameter, thickness, and pitch of the extruded filaments were compared to the corresponding geometries of the mandrel to validate the fabrication accuracy. Finally, a printed filament was programmed and actuated to test its functionality as a helical artificial muscle. The proposed printhead system not only allows for the stationary extrusion of helical artificial muscles but is also compatible with commercial 3D printers to freeform print helical artificial muscle groups in the future.

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25

Maksimkin, A. V., S. D. Kaloshkin, M. V. Zadorozhnyy, F. S. Senatov, A. I. Salimon, and T. Dayyoub. "Artificial muscles based on coiled UHMWPE fibers with shape memory effect." Express Polymer Letters 12, no. 12 (2018): 1072–80. http://dx.doi.org/10.3144/expresspolymlett.2018.94.

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26

ISHIKAWA, Toshiya, and Takeshi NAKADA. "Shape Memory Alloy Actuator for Artificial Muscle (Characteristics of Motor Unit)." Transactions of the Japan Society of Mechanical Engineers Series C 74, no. 738 (2008): 359–64. http://dx.doi.org/10.1299/kikaic.74.359.

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27

Yang, Qianxi, Jizhou Fan, and Guoqiang Li. "Artificial muscles made of chiral two-way shape memory polymer fibers." Applied Physics Letters 109, no. 18 (October 31, 2016): 183701. http://dx.doi.org/10.1063/1.4966231.

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28

Luo, Yun, Toshiyuki Takagi, Takeshi Okuyama, Shintaro Amae, Motoshi Wada, Kotaro Nishi, Takamichi Kamiyama, Tomoyuki Yambe, and Hidetoshi Matsuki. "Functional Evaluation of an Artificial Anal Sphincter Using Shape Memory Alloys." ASAIO Journal 50, no. 4 (July 2004): 338–43. http://dx.doi.org/10.1097/01.mat.0000131819.07741.ef.

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29

WANG, Feng, Ryohei KATSUKI, Mami TANAKA, Chikasi SIBATA, and Seiji CHONAN. "2508 Development of Artificial Rectum Valves Using Shape Memory Alloy Actuators." Proceedings of the Conference on Information, Intelligence and Precision Equipment : IIP 2005 (2005): 353–54. http://dx.doi.org/10.1299/jsmeiip.2005.353.

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30

Liang, Chenghao, and Naibao Huang. "Electrochemical characteristic of TiNi shape memory alloy in artificial body fluids." Journal of Biomedical Materials Research Part A 89A, no. 1 (April 2009): 266–69. http://dx.doi.org/10.1002/jbm.a.32062.

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31

Wang, Shiquan, Qiuguo Zhu, Rong Xiong, and Jian Chu. "Flexible Robotic Spine Actuated by Shape Memory Alloy." International Journal of Advanced Robotic Systems 11, no. 4 (April 4, 2014): 56. http://dx.doi.org/10.5772/58399.

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32

Takashima, Kazuto, Daiki Iwamoto, Shun Oshiro, Toshiro Noritsugu, and Toshiharu Mukai. "Characteristics of Pneumatic Artificial Rubber Muscle Using Two Shape-Memory Polymer Sheets." Journal of Robotics and Mechatronics 33, no. 3 (June 20, 2021): 653–64. http://dx.doi.org/10.20965/jrm.2021.p0653.

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We have developed a pneumatic artificial rubber muscle having a bending direction that can be changed using two shape-memory polymer (SMP) sheets, the stiffness of which depends on the temperature. In the present study, we attached two SMP sheets with embedded electrical heating wires to both sides of a pneumatic artificial rubber muscle in order to realize multidirectional actuation and evaluated the basic characteristics of the artificial muscle. The actuator is based on the design of a conventional curved-type artificial rubber muscle. Since only a heated SMP sheet becomes soft, the rigid SMP sheet inhibits the extension of the side of the actuator. Therefore, bending motion can be induced when air is supplied to the internal bladder. By controlling the temperature of the SMP sheets, the bending direction of the prototype actuator could be changed. Namely, three kinds of motions, such as two-directional bending and axial extension, became possible. Moreover, we improved the manufacturing method and the structure of the artificial muscle, such as the stitching method and the SMP sheet thickness, and evaluated the characteristics of the two-directional bending and the axial extension motions of the prototype actuator. We also calculated the theoretical values and compared these values with the experimental results. Furthermore, we examined the application of the actuators to a robot hand. Using the two-directional motion of the actuator, the proposed robot hand can grasp either small or large objects. The experimental results conducted using this prototype confirm the feasibility of the newly proposed actuator.

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33

Li, Hong Nan, Di Cui, and Gang Bing Song. "Hysteresis Model for Superelasticity of Shape Memory Alloy Based on ANN." Key Engineering Materials 340-341 (June 2007): 1175–80. http://dx.doi.org/10.4028/www.scientific.net/kem.340-341.1175.

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Superelasticity is one of the most important properties of shape memory alloy. In this paper, the superelastic deformation behavior of NiTi shape memory alloy subjected to cyclic loading with stable superelasticity is experimentally investigated. According to test data, a constitutive model for the superelasticity of shape memory alloy is presented based on the artificial neural network (ANN). Numerical results agree well with experimental observations that verified the constitutive model being of high accuracy. This model can avoid the difficulties of other models on the determination of the parameters and is suitable for practical engineering application. Thus, a new method is provided for building the constitutive model of shape memory alloy.

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34

Hmede, Rodayna, Frédéric Chapelle, and Yuri Lapusta. "Review of Neural Network Modeling of Shape Memory Alloys." Sensors 22, no. 15 (July 27, 2022): 5610. http://dx.doi.org/10.3390/s22155610.

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Shape memory materials are smart materials that stand out because of several remarkable properties, including their shape memory effect. Shape memory alloys (SMAs) are largely used members of this family and have been innovatively employed in various fields, such as sensors, actuators, robotics, aerospace, civil engineering, and medicine. Many conventional, unconventional, experimental, and numerical methods have been used to study the properties of SMAs, their models, and their different applications. These materials exhibit nonlinear behavior. This fact complicates the use of traditional methods, such as the finite element method, and increases the computing time necessary to adequately model their different possible shapes and usages. Therefore, a promising solution is to develop new methodological approaches based on artificial intelligence (AI) that aims at efficient computation time and accurate results. AI has recently demonstrated some success in efficiently modeling SMA features with machine- and deep-learning methods. Notably, artificial neural networks (ANNs), a subsection of deep learning, have been applied to characterize SMAs. The present review highlights the importance of AI in SMA modeling and introduces the deep connection between ANNs and SMAs in the medical, robotic, engineering, and automation fields. After summarizing the general characteristics of ANNs and SMAs, we analyze various ANN types used for modeling the properties of SMAs according to their shapes, e.g., a wire as an actuator, a wire with a spring bias, wire systems, magnetic and porous materials, bars and rings, and reinforced concrete beams. The description focuses on the techniques used for NN architectures and learning.

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35

ISHIKAWA, Toshiya, and Takeshi NAKADA. "SHAPE MEMORY ALLOY ACTUATOR PROTECTED BY ROLLED FILM TUBE FOR ARTIFICIAL MUSCLE." Proceedings of the JFPS International Symposium on Fluid Power 2008, no. 7-3 (2008): 841–46. http://dx.doi.org/10.5739/isfp.2008.841.

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36

Chen, Chi, Yangyuanchen Liu, Ximin He, Hua Li, Yujie Chen, Ying Wei, Yusen Zhao, et al. "Multiresponse Shape-Memory Nanocomposite with a Reversible Cycle for Powerful Artificial Muscles." Chemistry of Materials 33, no. 3 (January 19, 2021): 987–97. http://dx.doi.org/10.1021/acs.chemmater.0c04170.

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37

Luo, Yun, Takeshi Okuyama, Toshiyuki Takagi, Takamichi Kamiyama, Kotaro Nishi, and Tomoyuki Yambe. "Thermal control of shape memory alloy artificial anal sphincters for complete implantation." Smart Materials and Structures 14, no. 1 (November 27, 2004): 29–35. http://dx.doi.org/10.1088/0964-1726/14/1/003.

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38

Nishi, Kotaro, Takamichi Kamiyama, Motoshi Wada, Shintaro Amae, Tomohiro Ishii, Toshiyuki Takagi, Yun Luo, et al. "Development of an implantable artificial anal sphincter using a shape memory alloy." Journal of Pediatric Surgery 39, no. 1 (January 2004): 69–72. http://dx.doi.org/10.1016/j.jpedsurg.2003.09.009.

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39

YAMAGUCHI, Mitsuyoshi, Takeshi OKUYAMA, Toshiyuki TAKAGI, Tomoyuki YAMBE, and Hiroyuki MIKI. "502 Evaluation of an artificial esophagus with peristalsis using shape memory alloy." Proceedings of Conference of Tohoku Branch 2006.41 (2006): 195–96. http://dx.doi.org/10.1299/jsmeth.2006.41.195.

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40

Bergamasco, M., F. Salsedo, and P. Dario. "Shape memory alloy micromotors for direct-drive actuation of dexterous artificial hands." Sensors and Actuators 17, no. 1-2 (May 1989): 115–19. http://dx.doi.org/10.1016/0250-6874(89)80071-x.

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41

Liu, Hongjian, Yun Luo, Masaru Higa, Xiumin Zhang, Yoshifumi Saijo, Yasuyuki Shiraishi, Kazumitsu Sekine, and Tomoyuki Yambe. "Biochemical evaluation of an artificial anal sphincter made from shape memory alloys." Journal of Artificial Organs 10, no. 4 (December 2007): 223–27. http://dx.doi.org/10.1007/s10047-007-0395-y.

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42

Mareci, D., R. Chelariu, A. Cailean, and D. Sutiman. "Electrochemical characterization of Ni47.7 Ti37.8 Nb14.5 shape memory alloy in artificial saliva." Materials and Corrosion 63, no. 9 (December 7, 2011): 807–12. http://dx.doi.org/10.1002/maco.201106337.

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43

Mitchell, Kellen, Lily Raymond, Joshua Wood, Ji Su, Jun Zhang, and Yifei Jin. "Material Extrusion of Helical Shape Memory Polymer Artificial Muscles for Human Space Exploration Apparatus." Polymers 14, no. 23 (December 6, 2022): 5325. http://dx.doi.org/10.3390/polym14235325.

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Astronauts suffer skeletal muscle atrophy in microgravity and/or zero-gravity environments. Artificial muscle-actuated exoskeletons can aid astronauts in physically strenuous situations to mitigate risk during spaceflight missions. Current artificial muscle fabrication methods are technically challenging to be performed during spaceflight. The objective of this research is to unveil the effects of critical operating conditions on artificial muscle formation and geometry in a newly developed helical fiber extrusion method. It is found that the fiber outer diameter decreases and pitch increases when the printhead temperature increases, inlet pressure increases, or cooling fan speed decreases. Similarly, fiber thickness increases when the cooling fan speed decreases or printhead temperature increases. Extrusion conditions also affect surface morphology and mechanical properties. Particularly, extrusion conditions leading to an increased polymer temperature during extrusion can result in lower surface roughness and increased tensile strength and elastic modulus. The shape memory properties of an extruded fiber are demonstrated in this study to validate the ability of the fiber from shape memory polymer to act as an artificial muscle. The effects of the operating conditions are summarized into a phase diagram for selecting suitable parameters for fabricating helical artificial muscles with controllable geometries and excellent performance in the future.

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44

Vélez, José, Ángel Sánchez, Belén Moreno, and José L. Esteban. "Fuzzy shape-memory snakes for the automatic off-line signature verification problem." Fuzzy Sets and Systems 160, no. 2 (January 2009): 182–97. http://dx.doi.org/10.1016/j.fss.2008.05.021.

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45

Rațoi, Mihaela, Sergiu Stanciu, Nicanor Cimpoeşu, Iulian Cimpoeşu, Boris Constantin, and Ciprian Paraschiv. "A Potential Biodegradable Metallic Material with Shape Memory Effect Based on Iron." Advanced Materials Research 814 (September 2013): 110–14. http://dx.doi.org/10.4028/www.scientific.net/amr.814.110.

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FeMnSi alloys are promising shape memory alloys which have been used for pipe joints but no previous work pays any attention to their biomedical application. Following the outline of the aforementioned development of biodegradable Fe-based alloys, we believe that it is worthwhile to investigate the feasibility of FeMnSi alloy as biodegradable metal candidate, since element Si is widely used in biomedical metallic materials as an alloying element. A shape memory metallic material based on FeMnSi was obtained through classical melting method. The material was analyzed as cast and plastic deformed through rolling concerning materials microstructure (scanning electrons microscopy - SEM), chemical analyses (X-ray analyze by EDAX) and corrosion resistance (or biodegradation rate) in an artificial saliva electrolytic solutions (Fusayama) artificial aerated by linear and cyclic curves determination (potentiometry - VoltaLab).

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46

Joshi, Keyur B., Alex Villanueva, Colin F. Smith, and Shashank Priya. "Modeling of Artificial Aurelia aurita Bell Deformation." Marine Technology Society Journal 45, no. 4 (July 1, 2011): 165–80. http://dx.doi.org/10.4031/mtsj.45.4.13.

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AbstractRecently, there has been significant interest in developing underwater vehicles inspired by jellyfish. One of these notable efforts includes the artificial Aurelia aurita (Robojelly). The artificial A. aurita is able to swim with similar proficiency to the A. aurita species of jellyfish even though its deformation profile does not completely match the natural animal. In order to overcome this problem, we provide a systematic finite element model (FEM) to simulate the transient behavior of the artificial A. aurita vehicle utilizing bio-inspired shape memory alloy composite (BISMAC) actuators. The finite element simulation model accurately captures the hyperelastic behavior of EcoFlex (Shore hardness-0010) room temperature vulcanizing silicone by invoking a three-parameter Mooney-Rivlin model. Furthermore, the FEM incorporates experimental temperature transformation curves of shape memory alloy wires by introducing negative thermal coefficient of expansion and considers the effect of gravity and fluid buoyancy forces to accurately predict the transient deformation of the vehicle. The actual power cycle used to drive artificial A. aurita vehicle was used in the model. The overall profile error between FEM and the vehicle profile is mainly due to the difference in initial relaxed profiles.

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47

Omar, Mostafa, Bohan Sun, and Sung Hoon Kang. "Good reactions for low-power shape-memory microactuators." Science Robotics 6, no. 52 (March 17, 2021): eabh1560. http://dx.doi.org/10.1126/scirobotics.abh1560.

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48

Wang, Bao Lai, Yan Bo Wang, and Yu Feng Zheng. "Phase Constitution, Mechanical Property and Corrosion Resistance of the Ti-Nb Alloys." Key Engineering Materials 324-325 (November 2006): 655–58. http://dx.doi.org/10.4028/www.scientific.net/kem.324-325.655.

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Recently, people devote to the development of Ni-free shape memory alloys in order to avoid the Ni-hypersensitivity and toxicity and pursue absolute safety. The shape memory effect and superelasticity have been reported in the biomedical Ti-Nb based alloys. The purpose of this paper is to report the phase constitution, tensile property, shape memory effect and corrosion resistance of the Ti-Nb alloys. The phase constitutions of the Ti-Nb alloys are investigated by means of X-ray diffraction (XRD). The results reveal that β+α′′ phases are presented in the Ti-35Nb alloy and only β phase in the Ti-52Nb alloy at room temperature. The tensile test and bending tests indicate that the Ti-35Nb alloy exhibits shape memory effect. The shape recovery ratio is near to 80% when the bending strain is 4.4% and decreases with the increase of the total bending strain. The corrosion resistance of the Ti-Nb alloys in the Hank's solution and artificial saliva (pH=7.4) at 37 are investigated by OCP, Tafel and anodic polarization methods. The results indicate that the Ti-35Nb alloy has a better corrosion resistance in the artificial saliva and can replace the Ti-Ni alloy in the dental application. In the non-oral condition, the Ti-52Nb alloy may be preferable.

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49

SAKUMA, Masato, Shuichi WAKIMOTO, Koya MATSUSHITA, and Takefumi KANDA. "Fabrication and Evaluation of Shape Memory Polymer Fibers for Application to Artificial Muscles." Proceedings of Mechanical Engineering Congress, Japan 2020 (2020): J11117. http://dx.doi.org/10.1299/jsmemecj.2020.j11117.

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50

Trehern, W., R. Ortiz-Ayala, K. C. Atli, R. Arroyave, and I. Karaman. "Data-driven shape memory alloy discovery using Artificial Intelligence Materials Selection (AIMS) framework." Acta Materialia 228 (April 2022): 117751. http://dx.doi.org/10.1016/j.actamat.2022.117751.

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