玻璃形成液体中的玻璃动力学:对二烯的初步研究
Florian Pabst1, Stefano Baroni1,2
1Scuola Internazionale Superiore di Studi Avanzati, SISSA - , Trieste, Italy.
了解玻璃化过渡附近的液体粘度变化是关键. 机器学习揭示了粘度增加与更动态相关的分子相关,但并非所有玻璃动态特征.
科学领域:
- 凝聚物质物理学 凝聚物质物理学
- 材料科学是一种材料科学.
- 计算化学是一种计算化学.
背景情况:
- 玻璃过渡过程涉及到液体粘度的大幅增加.
- 这种粘度增加的微观起源仍然不太清楚.
- 在玻璃过渡附近模拟缓慢动态的挑战.
研究的目的:
- 研究玻璃制造器粘度增加背后的微观机制.
- 使用机器学习来加速玻璃动态的模拟.
- 确定控制粘度变化的关键分子水平因素.
主要方法:
- 采用机器学习来加速分子动力学模拟.
- 实现了模拟的第一原则准确性.
- 研究了玻璃原型的托卢烯.
主要成果:
- 粘度的增加与动态相关分子的数量 (N*) 密切相关.
- 身体衰老现象也与N*相关.
- 放松伸展行为与N*没有直接联系.
结论:
- 动态相关的分子在玻璃过渡附近的粘度变化中起着至关重要的作用.
- 机器学习加速了对复杂的凝聚物质现象的研究.
- 区分玻璃状状态的不同动态特征.
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