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Chalcogenide glasses as a playground for the application of first-principles molecular dynamics to disordered materials

机译:硫属化物玻璃作为游乐场,用于将第一原理的分子动力学应用于紊乱的材料

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摘要

An overview of the major first-principles methods used to simulate condensed phases is presented, with special emphasis on chalcogenide glasses. The scope of this review article is to offer a survey of fundamental algorithms and techniques, accompanied by a few recent examples particularly representative of computational materials science applied to disordered chalcogenide phases. Special attention is devoted to the inclusion of long-range van der Waals dispersion forces, treatment of the exact exchange, dynamical simulations and extraction of optical and dielectric properties. Machine learning techniques are introduced as recent forefront applications of first-principle methods. In this latter case, accurate quantum-mechanics based simulations are crucial to generate a data base exploited by neuronal-network type algorithms to create accurate interatomic potentials (force fields) allowing for large and long-lasting simulations of realistic disordered materials. The atomic-level knowledge provided by the combination of high-performance computing and advanced computational methods pave the route for a rational approach to the design of novel chalcogenides possessing tuned properties for specific applications in next-generation devices.
机译:提出了用于模拟凝聚阶段的主要第一原理方法的概述,特别强调硫属化物玻璃。本综述文章的范围是提供对基本算法和技术的调查,伴随着几个最近的例子,特别是应用于染色硫属化物阶段的计算材料科学。特别关注纳入远程范德华分散力,处理精确的交换,动力模拟和光学和介电性能的提取。机器学习技术被引入了第一原理方法的最近前沿应用。在后一种情况下,基于精确的量子力学模拟对于生成由神经网络类型算法利用的数据库来创建准确的内部电位(Force Fields),允许大量和长期持久地模拟现实无序材料。通过高性能计算和高级计算方法的组合提供的原子级知识为具有特定应用的新型硫属化合物设计的合理方法提供了一种合理的方法,用于下一代装置中的特定应用。

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