元动力学
复杂系统
计算机科学
范围(计算机科学)
能源景观
能量(信号处理)
统计物理学
集合(抽象数据类型)
化学
物理
人工智能
数学
分子动力学
计算化学
热力学
统计
程序设计语言
作者
Giovanni Bussi,Alessandro Laio
标识
DOI:10.1038/s42254-020-0153-0
摘要
Metadynamics is an atomistic simulation technique that allows, within the same framework, acceleration of rare events and estimation of the free energy of complex molecular systems. It is based on iteratively ‘filling’ the potential energy of the system by a sum of Gaussians centred along the trajectory followed by a suitably chosen set of collective variables (CVs), thereby forcing the system to migrate from one minimum to the next. The power of metadynamics is demonstrated by the large number of extensions and variants that have been developed. The first scope of this Technical Review is to present a critical comparison of these variants, discussing their advantages and disadvantages. The effectiveness of metadynamics, and that of the numerous alternative methods, is strongly influenced by the choice of the CVs. If an important variable is neglected, the resulting estimate of the free energy is unreliable, and predicted transition mechanisms may be qualitatively wrong. The second scope of this Technical Review is to discuss how the CVs should be selected, how to verify whether the chosen CVs are sufficient or redundant, and how to iteratively improve the CVs using machine learning approaches. Metadynamics is a technique to enhance the probability of observing rare events, such as chemical reactions and phase transitions, in molecular dynamics simulations. This Technical Review surveys the technique, addressing the critical issues that are met in practical applications.
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