开发和贝叶斯的不确定性量化粗粒度模型的金属基于嵌入式原子方法的潜力
Abhishek T Sose1, Troy Gustke1, Karteek K Bejagam1
1Department of Chemical Engineering, Virginia Tech, Blacksburg, Virginia 24060, United States.
Journal of chemical theory and computation
|December 5, 2025
概括
我们为FCC金属开发了粗粒嵌入原子方法 (CG EAM) 的潜力. 这种方法准确地模拟材料特性并量化不确定性,使可靠的材料设计成为可能.
科学领域:
- 材料科学 材料科学 材料科学
- 计算化学计算化学
- 凝聚物质物理学 凝聚物质物理学
背景情况:
- 粗粒度 (CG) 分子动力学 (MD) 模拟简化了原子结构,以实现经济高效的材料建模.
- 准确参数化原子间潜力 (力场,FFs) 和不确定性量化仍然是一个重大挑战.
研究的目的:
- 为面中心立方 (FCC) 金属开发粗粒嵌入原子方法 (CG EAM) 的潜力.
- 将参数优化与贝叶斯不确定性量化 (BUQ) 整合在一起,以获得可靠的FF开发.
主要方法:
- 开发了CG EAM潜力,将物理解释性与计算效率相结合.
- 使用粒子集群优化 (PSO) 与CG MD模拟来探索参数空间.
- 使用BUQ精制参数来评估FF参数和预测属性的不确定性.
主要成果:
- 成功对 (Pd),金 (Au),银 (Ag),铜 (Cu) 和 (Pt) 的CG EAM潜力进行了参数化.
- 确定了可靠的参数范围,确保预测属性保持在95%的置信区间内.
- 证明了框架在重现关键物理,机械和热力学性能方面的有效性.
结论:
- 综合PSO和BUQ方法为开发准确可靠的原子间潜能提供了有效的策略.
- 这种方法为设计具有目标性质的材料提供了一个可通用的框架.
- 开发的CG EAM潜力增强了FCC金属的建模能力.
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