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热可训练的双网水凝

Shanming Hu1, Yuhuang Fang1, Chen Liang1

  • 1Department of Applied Physics, Aalto University, P.O. Box 15100, Espoo, FI 02150, Finland.

Nature communications
|June 22, 2023
PubMed
概括

研究人员开发了可训练的水凝系统,可以训练它来执行活跃的工作. 这一突破允许增强或减少体积反应,使适应性人工肌肉和软机器人技术的新应用成为可能.

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科学领域:

  • 材料科学 材料科学 材料科学
  • 聚合物科学 聚合物科学
  • 生物材料是一种生物材料.

背景情况:

  • 可训练的响应性材料对于适应性和智能系统至关重要.
  • 目前的可训练材料缺乏执行活跃工作的能力,并且具有单向的功能变化.

研究的目的:

  • 为了展示可调节体积响应的可热训练的水凝系统.
  • 为了实现热诱导变形的正或负训练.
  • 为了使水凝能够执行积极的工作,并实现所需的机械性能,如软化,硬化或硬化.

主要方法:

  • 使用了由两个热敏聚合物组成的双网络水凝系统.
  • 实施了一个超过特定值温度的训练过程,以修改体积反应.
  • 设计的网络架构来控制培训的方向 (正面或负面).

主要成果:

  • 通过热训练实现可控增强或减少体积反应.
  • 通过训练证明了通过训练实现水凝的软化,硬化或硬化的能力.
  • 成功创建了可训练的水凝执行器,能够执行增加的活跃工作或最初不可能的任务.

结论:

  • 开发的双网络水凝为生物灵感软系统提供了一种新的培训策略.
  • 这种方法可以创建自适应的人工肌肉和先进的软机器人.
  • 这些发现为更复杂的智能材料系统铺平了道路.