Genetic Algorithm to Obtain Accurate Force Constants in Graphene (Adv. Theory Simul. 8/2025)

IF 2.9 4区工程技术 Q1 MULTIDISCIPLINARY SCIENCES

Advanced Theory and Simulations Pub Date : 2025-08-11 DOI:10.1002/adts.202570015

Wenjing Liu, Jinrong Xu, Shulei Gong, Wenrui Huang, Jiahui Hao, Jiangying Yu, Kai Huang, Ying Wang

引用次数: 0

Abstract

A genetic algorithm methodology is employed to simulate the self-organization of isolated carbon atoms into a hexagonal graphene lattice structure, where the interatomic force constants governing the bonding interact atoms are characterized. More details can be found in article 2500124 by Jinrong Xu, Ying Wang, and co-workers.

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石墨烯中精确力常数的遗传算法（Adv. Theory Simul. 8/2025）

采用遗传算法方法模拟孤立碳原子自组织成六方石墨烯晶格结构，其中原子间力常数控制键相互作用原子的特征。更多的细节可以在文章2500124由Jinrong Xu， Ying Wang和同事。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Advanced Theory and Simulations Multidisciplinary-Multidisciplinary

CiteScore

5.50

自引率

3.00%

发文量

221

期刊介绍： Advanced Theory and Simulations is an interdisciplinary, international, English-language journal that publishes high-quality scientific results focusing on the development and application of theoretical methods, modeling and simulation approaches in all natural science and medicine areas, including: materials, chemistry, condensed matter physics engineering, energy life science, biology, medicine atmospheric/environmental science, climate science planetary science, astronomy, cosmology method development, numerical methods, statistics