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稠密胶体悬浮液中弛豫的结构起源。

Structural origin of relaxation in dense colloidal suspensions.

作者信息

Sahu Ratimanasee, Sharma Mohit, Schall Peter, Maitra Bhattacharyya Sarika, Chikkadi Vijayakumar

机构信息

Physics Division, Indian Institute of Science Education and Research Pune, Pune 411008, India.

Polymer Science and Engineering Division, CSIR - National Chemical Laboratory, Pune 411008, India.

出版信息

Proc Natl Acad Sci U S A. 2024 Oct 15;121(42):e2405515121. doi: 10.1073/pnas.2405515121. Epub 2024 Oct 9.

Abstract

Amorphous solids relax via slow molecular rearrangement induced by thermal fluctuations or applied stress. Microscopic structural signatures predicting these structural relaxations have been long searched for but have so far only been found in dynamic quantities such as vibrational quasi-localized soft modes or with structurally trained neural networks. A physically meaningful structural quantity remains elusive. Here, we introduce a structural order parameter derived from the mean-field caging potential experienced by the particles due to their neighbors, which reliably predicts the occurrence of structural relaxations. The structural parameter, derived from density functional theory, provides a measure of susceptibility to particle rearrangements that can effectively identify weak or defect-like regions in disordered systems. Using experiments on dense colloidal suspensions, we demonstrate a strong correlation between this order parameter and the structural relaxations of the amorphous solid. In quiescent suspensions, this correlation increases with density, when particle rearrangements become rarer and more localized. In sheared suspensions, the order parameter reliably pinpoints shear transformations; the applied shear weakens the caging potential due to shear-induced structural distortions, causing the proliferation of plastic deformation at structurally weak regions. Our work paves the way to a structural understanding of the relaxation of a wide range of amorphous solids, from suspensions to metallic glasses.

摘要

非晶态固体通过热涨落或外加应力引起的缓慢分子重排来弛豫。预测这些结构弛豫的微观结构特征长期以来一直是人们寻找的目标,但迄今为止仅在诸如振动准局域软模等动态量中或通过结构训练的神经网络中被发现。一个具有物理意义的结构量仍然难以捉摸。在此,我们引入一个结构序参量,它源自粒子由于其邻居而经历的平均场笼蔽势,该序参量能可靠地预测结构弛豫的发生。这个从密度泛函理论导出的结构参数提供了一种对粒子重排敏感性的度量,它能有效地识别无序系统中的薄弱或类似缺陷的区域。通过对稠密胶体悬浮液的实验,我们证明了这个序参量与非晶态固体的结构弛豫之间存在很强的相关性。在静态悬浮液中,当粒子重排变得更稀少且更局域化时,这种相关性随密度增加。在剪切悬浮液中,序参量能可靠地确定剪切转变;外加剪切由于剪切诱导的结构畸变而削弱了笼蔽势,导致在结构薄弱区域塑性变形的扩散。我们的工作为从悬浮液到金属玻璃等广泛的非晶态固体弛豫的结构理解铺平了道路。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a24f/11494359/6ac908b017aa/pnas.2405515121fig01.jpg

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