{"title":"Shape Morphable Soft Machines and Systems Enabled by Responsive Advanced Materials.","authors":"Shubham Jaiswal, Chetna Dhand, Neeraj Dwivedi","doi":"10.1002/smtd.202501019","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":229,"journal":{"name":"Small Methods","volume":" ","pages":"e01019"},"PeriodicalIF":9.1000,"publicationDate":"2025-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Small Methods","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.1002/smtd.202501019","RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, PHYSICAL","Score":null,"Total":0}
引用次数: 0
Abstract
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.
Small MethodsMaterials 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.