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arXiv 2101.04673physics.chem-ph
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物理学启发的分子和材料的结构表示

Physics-inspired structural representations for molecules and materials

Felix Musil, Andrea Grisafi, Albert P. Bartók, Christoph Ortner, Gábor Csányi, Michele Ceriotti

摘要:

建立回归模型或数据驱动分析的第一步,旨在预测或阐明物质的原子尺度结构与其性质之间的关系,涉及将原子的笛卡尔坐标转换为合适的表示。原子尺度表示的发展已经并将继续在化学和材料科学的机器学习方法的成功中发挥核心作用。这篇综述总结了目前对原子结构的最常用的结构和化学描述的性质和特征的理解,突出了不同框架之间的深层联系,以及导致计算效率和普遍适用的模型的想法。它强调了性质,结构,它们的物理化学和它们的数学描述之间的联系,提供了最近应用于各种化学和材料科学问题的例子,并概述了该领域的开放问题和最有前途的研究方向。

英文摘要:

The first step in the construction of a regression model or a data-driven analysis, aiming to predict or elucidate the relationship between the atomic scale structure of matter and its properties, involves transforming the Cartesian coordinates of the atoms into a suitable representation. The development of atomic-scale representations has played, and continues to play, a central role in the success of machine-learning methods for chemistry and materials science. This review summarizes the current understanding of the nature and characteristics of the most commonly used structural and chemical descriptions of atomistic structures, highlighting the deep underlying connections between different frameworks, and the ideas that lead to computationally efficient and universally applicable models. It emphasizes the link between properties, structures, their physical chemistry and their mathematical description, provides examples of recent applications to a diverse set of chemical and materials science problems, and outlines the open questions and the most promising research directions in the field.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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