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arXiv 2501.04552cond-mat.soft
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半结晶网络中无应力双向形状记忆效应的现象学建模:公式化、数值模拟与实验验证

Phenomenological modeling of the stress-free two-way shape-memory effect in semi-crystalline networks: Formulation, numerical simulation, and experimental validation

Matteo Arricca, Nicoletta Inverardi, Stefano Pandini, Maurizio Toselli, Massimo Messori, Ferdinando Auricchio, Giulia Scalet

AI总结:

本文构建一维连续介质现象学模型描述半结晶PCL网络的单向及有/无应力双向SME,并结合系统实验验证变量与演化规律。

摘要:

表现出无应力双向形状记忆效应(SME)的聚合物为实现自支撑可逆驱动提供了一种有吸引力的解决方案,而这是众多应用所需的基本特征。本文提出了一个一维连续介质现象学框架,用于模拟在有应力和无应力条件下同时表现出单向SME和双向SME的单组分半结晶聚合物网络。研究首先对基于聚(ε-己内酯)(PCL)的半结晶网络开展了全面实验,以表征其力学和热学性能,以及材料在不同热-力学条件下的单向和双向形状记忆行为。实验结果指导了模型的构建,阐明了控制变量和相变量的选择,并为其演化规律的选择提供了依据。随后,模型能力通过与实验数据对比得到验证。文中分析并讨论了影响无应力双向SME的所有现象,包括驱动温度、加热/冷却速率、施加的应力/应变以及骨架相和驱动相的含量,为应用开发提供了重要的新见解。

英文摘要:

Polymers exhibiting the stress-free two-way shape-memory effect (SME) represent an appealing solution to achieve self-standing reversible actuation that is a fundamental feature required by numerous applications. The present paper proposes a one-dimensional continuum phenomenological framework to model single-component semi-crystalline polymer networks exhibiting both the one-way SME and the two-way SME under stress and stress-free conditions. A comprehensive experimental campaign is first performed on semi-crystalline networks based on poly($\varepsilon$-caprolactone) (PCL) to characterize the mechanical and thermal properties as well as the one-way and two-way shape memory behavior of the material under different thermo-mechanical conditions. The results guide the formulation of the model, elucidating the selection of the control and phase variables and motivating the choice of their evolution laws. Model capabilities are then demonstrated against experimental data. All the phenomena that influence the stress-free two-way SME, including the actuation temperature, heating/cooling rates, applied stress/strain, and the amount of skeleton and actuation phase, are analyzed and discussed, giving new important insight for application development.

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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