在有效恒定化学潜力下的平衡固体-液体接口的建模,使用机器学习的原子间潜力
Ademola Soyemi1, Khagendra Baral1, Tibor Szilvási1
1Department of Chemical and Biological Engineering, The University of Alabama, Tuscaloosa, Alabama 35487, United States.
我们开发了代的近常化学潜力分子动力学 (iqCμMD) 来模拟溶液中的度目标. 这种方法在与实验相比的大规模条件下高效地模拟接口,克服了传统分子动力学限制.
科学领域:
- 计算化学是一种计算化学.
- 材料科学是一种材料科学.
- 物理化学 物理化学
背景情况:
- 化学潜力 (μ) 对于界面过程至关重要.
- 传统的分子动力学 (MD) 努力保持恒定的化学潜力,特别是在动态条件下.
- 溶液迁移到接口可以改变散装度,限制模拟的准确性.
研究的目的:
- 引入代的近常化学潜力分子动力学 (iqCμMD) 用于模拟目标度.
- 在与实验设置相美的散装条件下实现接口的MD模拟.
- 提供一个计算效率高的方法来克服固定组成的MD的局限性.
主要方法:
- 开发和实施了 iqCμMD 模拟方法.
- 应用iQCμMD与机器学习原子间潜力 (MLIPs) 对Na2SO4 ((aq) - 石墨烯接口.
- 经过验证的可转移性使用NaCl (aq) -空气和NaCl (aq) -石墨接口的经典力场.
主要成果:
- iqCμMD在两次代内有效地实现了目标批量离子度.
- 基于MLIP的 iqCμMD 能够通过较小规模的模拟实现融合结果.
- 结果与之前的CμMD模拟和DFT级准确度相似.
结论:
- iqCμMD提供了一个强大而简单的计算框架,用于恒定化学电位模拟.
- 该方法只需要能够将界面模拟与可测量的散装区域进行融合.
- 将 iqCμMD 与 MLIP 结合起来,在有效恒定化学电位下准确建模固体-液体接口.
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