在图形理论动力蒙特卡洛模拟中加速检测吸附剂侧面相互作用
Raz L Benson1, Sai Sharath Yadavalli1, Michail Stamatakis1
1Department of Chemical Engineering, University College London, Torrington Place, London WC1E 7JE, U.K.
The journal of physical chemistry. A
|November 21, 2023
概括
新的算法加速了用于催化剂发现的动力蒙特卡洛 (KMC) 模拟. 集成到Zacros中的RI算法显著加快了涉及复杂吸附物相互作用的计算,从而实现了更高效的异质催化剂设计.
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.
- 化学工程是化学工程的组成部分.
背景情况:
- 动力蒙特卡洛 (KMC) 对于异质催化剂的发现至关重要.
- 由于复杂的吸附物相互作用,模拟是计算密集的.
- 扎克罗斯软件使用集群扩展 (CE) 框架来进行这些交互.
研究的目的:
- 为了降低KMC模拟的计算成本.
- 在Zacros包中实现和基准分图等同算法 (VF2和RI).
- 提高在催化中模拟侧向吸附物相互作用的效率.
主要方法:
- 适应KMC模拟的VF2和RI子图等同算法.
- 将这些算法集成到Zacros软件包中.
- 使用催化NO氧化和甲裂解模型进行基准性能测试.
主要成果:
- VF2和RI算法为具有远程相互作用的KMC模拟提供了显著的加速度.
- 该RI算法,特别是与OpenMP并行实现,实现了超过150×的加速度.
- RI在高表面覆盖面的甲裂变模拟中显示了显著的性能改进.
结论:
- VF2 和 RI 算法提高了 Zacros 中 KMC 模拟的计算效率.
- 提高了效率,为催化剂发现提供了更现实的,更广泛的模拟.
- 这些进步使催化过程能够更好地建模,特别是在苛刻的条件下.
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