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Material characterization and multi-scale modeling of light activated SMP

机译:光活化SMP的材料表征和多尺度建模

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Stiffness variation versus stimulation for a light activated shape memory polymer (LASMP) is predicted with a multiscale modeling approach. The multiscale model utilizes rotational isomeric state theory to build a polymer chain conformation, Johnson distributions to model the distances between crosslinks, junction constraints to model neighboring chain interactions, and Boltzmann statistical mechanics to relate the entropy of the chain to the macroscopic response. It is shown that a novel choice for the equation describing stress dependence on strain, capturing the polymer's departure from affine deformation, results in a stress strain curve with an expected shape. The fitting parameters characterizing the interaction with neighboring chains can also be phenomenologically fit to experimental data, yielding accurate modulus predictions. The result is a bottom up model accurately predicting the material response of the polymer with parameters that can be derived almost entirely from the molecular formula of the polymer, allowing sufficiently similar polymers to be modeled accurately, reducing the time, effort, and resources required in the development of new polymer systems.
机译:使用多尺度建模方法可以预测光活化形状记忆聚合物(LASMP)的刚度变化与刺激。多尺度模型利用旋转异构状态理论来构建聚合物链构象,利用Johnson分布对交联之间的距离进行建模,利用结约束来对相邻链之间的相互作用进行建模,并采用Boltzmann统计力学将链的熵与宏观响应联系起来。结果表明,对于描述应力对应变的依赖性的方程式的一种新颖选择,捕获了聚合物从仿射变形的偏离,产生了具有预期形状的应力应变曲线。表征与相邻链相互作用的拟合参数也可以在现象学上适合于实验数据,从而产生准确的模量预测。结果是一个自下而上的模型,该模型精确地预测了聚合物的材料响应,其参数几乎可以完全从聚合物的分子式得出,从而可以对足够相似的聚合物进行精确建模,从而减少了所需的时间,精力和资源。新聚合物系统的开发。

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