Collaborative Research: Processing and Performance of Chained Magnetic Particle Composites for Soft Robotics

合作研究：用于软机器人的链状磁性颗粒复合材料的加工和性能

• 批准号: 1662641
• 负责人: Benjamin Evans
• 金额: $ 10.82万
• 依托单位: Elon University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-04-01 至 2021-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1662641&HistoricalAwards=false
• 关键词: Collaborative; Research; Processing; Performance; Chained

Soft robotics is a rapidly growing field in which soft materials, such as polymers, are formed into devices whose mechanical response can be triggered by physical or chemical stimuli. Magnetically responsive polymer composites containing embedded magnetic particles are especially attractive for soft robotics, because they allow for non-contact actuation with electromagnets or permanent magnets. Furthermore, chaining the magnetic particles within the polymer imparts an enhanced, directional response. This award supports fundamental experimental and theoretical research to investigate the processing and performance of chained magnetic particle composites for soft robotics. Soft robotic devices based on chained magnetic particle composites developed in this research will be immediately useful in practical applications, including non-contact peristaltic pumps and remotely actuated microfluidic valves and mixers for next-generation medical diagnostic devices. Theoretical tools developed in this research will also drive innovation by providing easily accessible metrics to inform the design and evaluate the performance of chained magnetic particle actuators. Themes and results from this research will be integrated into education and outreach activities designed to inspire and recruit the next generation of scientists and engineers.While there have been many reports of magnetoactive elastomers for soft robotics, the design of these materials is usually empirical rather than guided by a predictive model, resulting in missed opportunities to optimize their design and performance, such as with chained-particle formulations. This research aims to develop a framework and figures of merit for predicting the behavior of magnetoactive elastomer actuators and to employ them for designing useful devices with enhanced capabilities. Using these tools, the torque in chained-particle magnetoactive elastomers generated in applied magnetic fields will be maximized, elasticity of the polymer and elastic instabilities will be incorporated in device function, and shape memory polymers will enable realization of magnetoactive elastomer materials and devices that are reconfigurable and selectively addressable. This research will advance the field of chained-particle magnetoactive elastomers by developing tools to guide their design for applications in soft robotics and by demonstrating the capabilities of these materials and devices.

软机器人是一个快速发展的领域，在这个领域中，软材料，如聚合物，被形成设备，其机械响应可以被物理或化学刺激触发。含有嵌入磁性颗粒的磁性响应性聚合物复合材料对软机器人特别有吸引力，因为它们允许使用电磁铁或永久磁铁进行非接触驱动。此外，在聚合物内链接磁性颗粒可提供增强的定向响应。该奖项支持基础实验和理论研究，以研究用于软机器人的链式磁性颗粒复合材料的加工和性能。本研究开发的基于链式磁粉复合材料的软机器人设备将立即在实际应用中发挥作用，包括用于下一代医疗诊断设备的非接触式蠕动泵和遥控微流体阀和混合器。这项研究中开发的理论工具也将通过提供易于访问的指标来推动创新，以指导设计和评估链式磁粉执行器的性能。这项研究的主题和成果将被整合到旨在激励和招募下一代科学家和工程师的教育和推广活动中。虽然已经有许多关于用于软机器人的磁活性弹性体的报告，但这些材料的设计通常是经验的，而不是由预测模型指导的，导致错过了优化其设计和性能的机会，例如使用链状粒子配方。这项研究旨在开发一种框架和优值系数来预测磁活性弹性体致动器的行为，并将其用于设计具有增强能力的有用设备。使用这些工具，链状颗粒磁活性弹性体在外加磁场中产生的扭矩将最大化，聚合物的弹性和弹性不稳定性将被纳入设备功能，形状记忆聚合物将实现可重构和选择性寻址的磁活性弹性体材料和设备。这项研究将通过开发工具来指导链状粒子磁活性弹性体在软机器人中的应用设计，并通过展示这些材料和设备的能力来推动链状粒子磁活性弹性体领域的发展。

项目成果

Photothermally Reconfigurable Shape Memory Magnetic Cilia

• DOI: 10.1002/admt.202000147
• 发表时间: 2020-03
• 期刊: Advanced Materials Technologies
• 影响因子: 6.8
• 作者: Jessica A.‐C. Liu;B. Evans;J. B. Tracy

Magnetically Aligned Nanorods in Alginate Capsules (MANiACs): Soft Matter Tumbling Robots for Manipulation and Drug Delivery

• DOI: 10.3390/mi10040230
• 发表时间: 2019-04-01
• 期刊: MICROMACHINES
• 影响因子: 3.4
• 作者: Mair, Lamar O.;Chowdhury, Sagar;Cappelleri, David J.
• 通讯作者: Cappelleri, David J.

Photothermally and magnetically controlled reconfiguration of polymer composites for soft robotics

• DOI: 10.1126/sciadv.aaw2897
• 发表时间: 2019-08-01
• 期刊: SCIENCE ADVANCES
• 影响因子: 13.6
• 作者: Liu, Jessica A. -C.;Gillen, Jonathan H.;Tracy, Joseph B.
• 通讯作者: Tracy, Joseph B.