Investigation of early stages of crystallization in supercooled atomic liquids by time-resolved x-ray scattering from microscopic laminar jets in conjunction with machine learning-based data analysis.

通过微观层流射流的时间分辨 X 射线散射结合基于机器学习的数据分析来研究过冷原子液体的早期结晶阶段。

• 批准号: 499455518
• 负责人: Privatdozent Dr. Robert Evaristo Grisenti
• 金额: --
• 依托单位: Institut für Kernphysik
• 依托单位国家: 德国
• 项目类别: Research Grants
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/499455518?language=en
• 关键词: Investigation; early; stages; crystallization; supercooled

Freezing of a liquid is a ubiquitous change of state that affects many aspects of our daily life, but many aspects of this so familiar phase transition are still poorly understood. At the microscopic level, crystallization is classically viewed as a two-steps process. Thermal fluctuations in the supercooled liquid — that is, below its melting point — initially trigger the spontaneous formation of a small, localized nucleus of the new ordered phase, which subsequently grows to macroscopic dimensions. However, crystallization is by far more complex than represented by this classical description and many details of the process still lack an adequate microscopic understanding. Here we aim to combine x-ray scattering at the European X-ray Free-Electron Laser with microscopic liquid jets of the atomic elements argon and krypton as a powerful approach to the study the early stages of crystallization in supercooled liquids. This approach uniquely addresses the problems of very short time scale and the inherently stochastic nature of the crystal nucleation process as no a priori knowledge of the spatial and temporal coordinates of the spontaneous solid formation is in general available. In combination with computer simulations and state-of-the-art ML-based techniques for data analysis, we expect to be able to gain deeper insights into many fundamental aspects of the crystallization process, thereby providing new benchmarks for current theories of crystal nucleation and growth.

液体的冻结是一种普遍存在的状态变化，影响着我们日常生活的许多方面，但这种如此熟悉的相变的许多方面仍然知之甚少。在微观层面上，结晶通常被视为两步过程。过冷液体中的热波动-即低于其熔点-最初触发新有序相的小的局部核的自发形成，其随后生长到宏观尺寸。然而，结晶是远比这个经典的描述所代表的复杂，许多细节的过程仍然缺乏足够的微观理解。在这里，我们的目标是结合联合收割机的X射线散射在欧洲的X射线自由电子激光器与微观液体射流的原子元素氩和氪作为一个强大的方法来研究结晶的早期阶段在过冷液体。这种方法独特地解决了非常短的时间尺度和晶体成核过程固有的随机性的问题，因为通常没有自发固体形成的空间和时间坐标的先验知识。结合计算机模拟和最先进的基于ML的数据分析技术，我们希望能够更深入地了解结晶过程的许多基本方面，从而为当前的晶体成核和生长理论提供新的基准。