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使用可扩展神经网络潜力的表面反应超热产物平衡动力学的建模,具有第一原则准确度
Qidong Lin1, Bin Jiang1,2
1Key Laboratory of Precision and Intelligent Chemistry, Key Laboratory of Surface and Interface Chemistry and Energy Catalysis of Anhui Higher Education Institutes, Department of Chemical Physics, University of Science and Technology of China, Hefei, Anhui 230026, China.
在表面O2解离的热氧原子表现出复杂的动态. 最初的方向和表面温度显著影响原子运动,挑战了之前关于弹道运动的预测.
科学领域:
- 表面科学是一门科学.
- 化学物理 化学物理
- 材料科学 是一种材料科学.
背景情况:
- 在表面分子解离后了解原子的动态对于催化和材料设计至关重要.
- 以前的模型建议热氧原子在上解离后的弹道运动.
研究的目的:
- 在Pd(100) 和Pd(111) 表面O2解离后,研究热氧原子的平衡动态.
- 改进对解离后原子行为的理解,并确定影响原子运动的因素.
主要方法:
- 使用可扩展的神经网络潜力的分子动力学模拟.
- 对O2和O与可变超级细胞相互作用的第一原则计算.
- 分析了数百个轨迹,并进行了适当的初始采样.
主要成果:
- 模拟准确地复制了平衡原子对在Pd上的实验距离分布.
- 热原子在Pd(100) 上的弹道运动在理想条件下被发现是一种罕见的事件.
- 最初的O2分子方向和表面的热波动显著影响Pd上的解离后动态.
- 两个表面的分离氧原子倾向于停留在它们的初始位置附近,并随机行走.
结论:
- 该研究提供了对金属表面热原子动态的更细致的理解,突出了初始条件和表面环境的重要性.
- 这些发现挑战了简化的模型,并强调需要详细的模拟来捕捉复杂的表面相互作用.
- 开发出来的神经网络潜力可以为氧-相互作用提供准确的第一原则模拟.
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