网络玻璃中塑性流动的普适能量势垒
Universal energy barrier for plastic flow in a network glass
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中文总结 AI 辅助
本文通过机器学习势能模拟非晶碳，发现剪切转变源于单键断裂/形成，能量景观坍缩为普适势垒形状，键跳跃距离通过三次方定律决定势垒高度，从而从键级量预测塑性流动应力，为玻璃塑性模型提供微观基础。
中文摘要 AI 辅助
剪切转变是玻璃中塑性的基本事件，支撑着许多塑性流动的介观模型，然而其原子起源和能量学仍然难以确定。在这里，我们使用机器学习原子间势能表明，在非晶碳作为代表性网络玻璃中，剪切转变对应于单个共价键的断裂或形成。相关反应坐标（键长）的简单性使我们能够提取能量景观和势垒。尽管存在固有的结构无序性，我们发现所有能量景观都坍缩到普适的势垒形状上。键特有的仅是一个尺度，即键跳跃距离，它通过三次方定律确定势垒高度。结合剪切转变的激活统计，这产生了一个模型，该模型从独立确定的键级量预测塑性流动应力。我们的结果为玻璃中塑性流动的现象学模型提供了微观支持，并提出了定量描述非晶塑性的途径。
英文摘要
Shear transformations are the elementary events of plasticity in glasses and underpin many mesoscopic models of plastic flow, yet their atomic origin and energetics remain difficult to establish. Here we use a machine-learned interatomic potential to show that, in amorphous carbon as a representative network glass, a shear transformation corresponds to the breaking or formation of a single covalent bond. The simplicity of the associated reaction coordinate, the bond length, enables us to extract energy landscapes and barriers. Despite the intrinsic structural disorder, we find that all energy landscapes collapse onto a universal barrier shape. What remains bond-specific is a single scale, the bond-jump distance, which fixes the barrier height through a cubic law. Combined with the activation statistics of shear transformations, this yields a model that predicts the plastic flow stress from independently determined bond-level quantities. Our results provide microscopic support for phenomenological models of plastic flow in glasses and suggest a route towards a quantitative description of amorphous plasticity.
发表机构
- University of Freiburg（弗赖堡大学）
- Aalto University（阿尔托大学）
- Fraunhofer IWM（弗劳恩霍夫工业机械研究所）
- Institute of Physics, University of Freiburg（弗赖堡大学物理研究所）
机构由 AI 辅助整理，请以论文原文为准。
