基于摩擦调谐的软杆网络紧急可编程机械记忆

Harsh Jain, Shankar Ghosh
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引用次数: 0

摘要

我们提出了在软细胞材料中出现的机械记忆存储行为。细胞材料是一个柔软的超弹性棒的网络,储存形状变化,特别是局部压痕。这发生在施加在材料上的整体压缩应变下。材料的欠应变从弹性状态(能够“忘记”压痕后的任何应用压痕)过渡到塑性状态(无限期地存储由于压痕而发生的形状变化)。内存可以通过移除应用的全局应变来擦除,因此可以重新编程。我们在实验中描述了这种行为,并提出了一个简单的模型,利用摩擦来理解这种行为。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Emergent reprogrammable mechanical memory in soft rods network via friction tuning
We present emergent mechanical memory storage behavior in soft cellular materials. The cellular materials are a network of soft hyperelastic rods which store shape changes, specifically local indentation. This happens under an applied global compressive strain on the material. The material transits under strain from an elastic state (capable of `forgetting' any applied indentation after un-indentation) to plastic state (indefinitely storing the shape change due to indentation). The memory can be erased via removal of applied global strains and is therefore re-programmable. We characterise this behaviour experimentally and present a simple model that makes use of friction for understanding this behavior.
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