拉斯普到原子模拟的未来:智能和自动化
Xin-Tian Xie1, Zheng-Xin Yang1, Dongxiao Chen1
1Collaborative Innovation Center of Chemistry for Energy Material, Shanghai Key Laboratory of Molecular Catalysis and Innovative Materials, Key Laboratory of Computational Physical Science, Department of Chemistry, Fudan University, Shanghai 200433, China.
Precision chemistry
|December 30, 2024
概括
通过使用先进的神经网络潜力和自动化,LASP软件增强了原子模拟. 现在它为复杂的材料和反应问题解决提供了更高的准确性和效率.
科学领域:
- 计算材料科学科学 计算材料科学
- 化学物理 化学物理
- 化学中的人工智能.
背景情况:
- 准确的潜在能量表面和高效的罕见事件捕获对于原子模拟至关重要.
- 为了应对这些挑战,开发了LASP软件 (具有神经网络潜力的大型原子模拟).
研究的目的:
- 审查LASP软件的最新发展,重点是提高智能和自动化.
- 突出LASP在解决复杂材料和反应问题的能力.
主要方法:
- 利用全球多体函数纠正神经网络 (G-MBNN) 来提高潜在能量表面精度和线性缩放效率.
- 结合ASOP和ML接口方法用于表面/接口结构预测.
- 采用ML-TS和MMLPS方法来识别最低能量反应途径.
主要成果:
- 通过LASP 3.7,可以以较低的成本实现更高精度的潜在能量表面描述.
- 该软件在大型原子模拟中展示了线性缩放效率.
- 新功能使复杂结构和反应途径的自动预测成为可能.
结论:
- 拉斯普作为一个智能数据生成器,用于创建计算数据库.
- 该软件为诸如热带石设计和催化剂开发等应用程序提供了数据库构建的便利.
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