arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2008.07016cond-mat.mtrl-sciphysics.comp-ph
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基于接触图的晶体结构全局优化预测

Contact Map based Crystal Structure Prediction using Global Optimization

Jianjun Hu, Wenhui Yang, Rongzhi Dong, Yuxin Li, Xiang Li, Shaobo Li

摘要:

晶体结构预测在发现新材料中起着越来越重要的作用。全局优化方法如遗传算法(GA)和粒子群优化(PSO)已经与第一原理自由能计算相结合,以预测给定组成或仅化学体系的晶体结构。虽然这些方法可以在其搜索过程中利用某些晶体模式,例如对称性和周期性,但它们通常不利用大量已知晶体结构中包含的原子构型的大量隐含规则和约束。他们目前只能处理相对较小系统的晶体结构预测。受知识丰富的蛋白质结构预测方法的启发,在本文中,我们探索已知的几何约束,如目标晶体材料的原子接触图,是否可以帮助预测其结构,给出其空间群信息。我们提出了一个基于全局优化的算法,CMCrystal,用于基于原子接触图的晶体结构重建。基于广泛的实验,使用六个全局优化算法,我们表明,它是可行的,以重建晶体结构给定的原子接触图的一些晶体材料,但需要更多的约束条件,为其他目标材料,以实现成功的重建。这意味着从现有材料中获得的原子相互作用信息可以用于改进晶体结构预测。

英文摘要:

Crystal structure prediction is now playing an increasingly important role in discovery of new materials. Global optimization methods such as genetic algorithms (GA) and particle swarm optimization (PSO) have been combined with first principle free energy calculations to predict crystal structures given composition or only a chemical system. While these approaches can exploit certain crystal patterns such as symmetry and periodicity in their search process, they usually do not exploit the large amount of implicit rules and constraints of atom configurations embodied in the large number of known crystal structures. They currently can only handle crystal structure prediction of relatively small systems. Inspired by the knowledge-rich protein structure prediction approach, herein we explore whether known geometric constraints such as the atomic contact map of a target crystal material can help predict its structure given its space group information. We propose a global optimization based algorithm, CMCrystal, for crystal structure reconstruction based on atomic contact maps. Based on extensive experiments using six global optimization algorithms, we show that it is viable to reconstruct the crystal structure given the atomic contact map for some crystal materials but more constraints are needed for other target materials to achieve successful reconstruction. This implies that atomic interaction information learned from existing materials can be used to improve crystal structure prediction.

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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