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Updated: Feb 5, 2026

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使用协作差分进化进行双金属集群结构优化的C++工具包
Xiaomin Wu1, Miao He2, Yousi Lin1
1School of Optoelectronic and Communication Engineering, Xiamen University of Technology, Xiamen 361024, China.
Journal of chemical information and modeling
|February 4, 2026
概括
我们开发了一个协作差异进化 (CDE) 算法,用于高效的纳米集群结构预测. 这种方法加速了对双金属和单金属集群的稳定配置的发现.
科学领域:
- 材料科学 材料科学 材料科学
- 计算化学的计算化学
- 纳米技术纳米技术
背景情况:
- 双金属和单金属集群结构的全球优化是计算密集的.
- 随着系统的大小和复杂性,可能的配置 (同质组) 的数量迅速增加.
研究的目的:
- 开发一种高效的算法,用于预测纳米集群系统的稳定结构.
- 解决各种集群结构在全球优化的计算挑战.
主要方法:
- 一个协作差异进化 (CDE) 算法的介绍.
- 利用多个子群的协作架构与专门的子群进行探索,开发和平衡.
- 为金属纳米集群量身定制的适应性操作的实施以及作为在线C++工具包的可用性.
主要成果:
- 通过对Pt-Pd,Cu-Au双金属和单金属Pt集群的结构优化,证明了多功能性和强度.
- 与传统方法相比,实现了比50-100%更快的趋同.
- 在所有测试系统中,在结构预测方面展示了卓越的稳定性.
结论:
- CDE算法是一个强大的和可泛化的工具,用于加速在多种集群材料中发现稳定的配置.
- 开发的工具包为纳米集群结构预测提供了高效和用户友好的解决方案.
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