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arXiv 2501.04838cond-mat.soft
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在无序弹性网络中训练受别构效应启发的力学响应

Training Allostery-Inspired Mechanical Response in Disordered Elastic Networks

Savannah D. Gowen

AI总结:

本文受蛋白质别构效应启发,利用定向老化训练无序弹性网络,使局部应变在远距离节点间产生或增强力学耦合,并通过实验与模拟对比验证。

摘要:

无序弹性网络是一种模型材料系统,在其中能够实现可调且可训练的功能。本研究受蛋白质中别构相互作用的启发,考察无序网络中局部力学性质的改变:对一组源节点局部施加应变,会在远处的一组目标节点处触发应变响应。研究首先通过定向老化来改变成对的远距离源节点与目标节点之间既有的力学耦合,随后又将其作为一种手段,在此前相互孤立的源—目标节点对之间诱导耦合。实验结果与模拟预测结果进行了比较。

英文摘要:

Disordered elastic networks are a model material system in which it is possible to achieve tunable and trainable functions. This work investigates the modification of local mechanical properties in disordered networks inspired by allosteric interactions in proteins: applying strain locally to a set of source nodes triggers a strain response at a distant set of target nodes. This is demonstrated first by using directed aging to modify the existing mechanical coupling between pairs of distant source and target nodes, and later as a means for inducing coupling between formerly isolated source-target pairs. The experimental results are compared with those predicted by simulations.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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