由响应性先进材料实现的可变形软机器和系统。

IF 9.1 2区 材料科学 Q1 CHEMISTRY, PHYSICAL
Shubham Jaiswal, Chetna Dhand, Neeraj Dwivedi
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引用次数: 0

摘要

软机器人技术通过实现受生物学启发的适应性、灵活性和运动性,彻底改变了机器人的设计。与传统的刚性机器人不同,软机器人系统与环境动态交互,使其成为生物医学设备的理想选择。这些系统的一个关键部件是执行器。形状记忆聚合物(SMPs)由于其可编程的形状变换响应各种刺激、可逆变形和可调的机械性能而成为一种有前途的驱动技术。然而,驱动速度、抗疲劳性和长期耐久性仍然是它们的主要瓶颈。SMP复合材料,结合外来材料,可以提高软机器和系统的功能和耐用性。这项工作批判性地考察了smp驱动的驱动技术及其在塑造下一代软机器人方面的潜力。讨论了软机器人对智能聚合物(如smp)的需求,smp的按需工程,软系统的各种受激响应,以及smp支持的软机器和系统在人造肌肉,夹具,传感器(高温探测器),开关和RFID应用中的应用。多刺激响应smp及其与人工智能的集成也得到了强调。最后,讨论了形状记忆软机器和系统目前面临的挑战和前景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Shape Morphable Soft Machines and Systems Enabled by Responsive Advanced Materials.

Soft robotics revolutionizes robotic design by enabling adaptability, flexibility, and motion inspired by biology. Unlike traditional rigid robots, soft robotic systems interact dynamically with their environment, making them ideal for biomedical devices. A key component of these systems is the actuator. Shape memory polymers (SMPs) have emerged as a promising actuation technology due to their programmable shape transformations in response to various stimuli, reversible deformations, and tunable mechanical properties. However, actuation speed, fatigue resistance, and long-term durability remain their major bottlenecks. SMP composites, incorporating foreign materials, can enhance the functionality and durability of soft machines and systems. This work critically examines SMP-driven actuation technologies and their potential in shaping the next generation of soft robotics. The need for smart polymers such as SMPs for soft robotics, the engineering of SMPs on demand, various stimulated responses of soft systems, and finally, the applications of SMP-enabled soft machines and systems for artificial muscles, grippers, sensors (high-temperature detectors), switches, and RFID applications are discussed. Multi-stimuli-responsive SMPs and their integration with artificial intelligence to advance functionality are also highlighted. In the end, the current challenges and prospects in shape-memorable soft machines and systems are discussed.

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来源期刊
Small Methods
Small Methods Materials Science-General Materials Science
CiteScore
17.40
自引率
1.60%
发文量
347
期刊介绍: Small Methods is a multidisciplinary journal that publishes groundbreaking research on methods relevant to nano- and microscale research. It welcomes contributions from the fields of materials science, biomedical science, chemistry, and physics, showcasing the latest advancements in experimental techniques. With a notable 2022 Impact Factor of 12.4 (Journal Citation Reports, Clarivate Analytics, 2023), Small Methods is recognized for its significant impact on the scientific community. The online ISSN for Small Methods is 2366-9608.
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