封闭在Pd间层中的氧气的表面依赖界面度:具有神经网络潜力的分子动力学
Feicheng Huan1, Feng Shi1, Gaoyang Luo1
1State Key Laboratory of Green Chemical Synthesis and Conversion, College of Chemical Engineering, Zhejiang University of Technology, Hangzhou 310032, P. R. China.
ACS applied materials & interfaces
|September 26, 2025
概括
对于催化剂来说,了解 (Pd) 表面的氧气动态是关键. 这项研究使用神经网络潜力和分子动力学来揭示限制如何影响不同PD表面的氧气度和反应性.
科学领域:
- 材料科学 材料科学 材料科学
- 表面化学 表面化学
- 计算化学计算化学
背景情况:
- 了解氧气在 (Pd) 表面的界面动态对于工业催化非常重要.
- 开发反应-运输合机制,以提高基于Pd的催化剂活性和在封闭环境中的稳定性,仍然是一个挑战.
研究的目的:
- 通过使用集成全球神经网络 (G-NN) 潜力和分子动力学 (MD) 模拟,研究Pd介层中受限O2分子的界面度.
- 为了阐明影响氧气行为和反应能力的因素,在不同的Pd表面限制下.
主要方法:
- 利用一个反应性神经网络 (NN) 潜力,根据密度函数理论 (DFT) 基准验证.
- 采用分子动力学 (MD) 模拟来研究Pd介层上的界面O2度.
- 分析了平均平方位移,反应速率,密度分布和辐射分布函数.
主要成果:
- 开发的反应NN潜能准确地区分了三个Pd表面 (Pd(100),Pd(211),Pd(111) 之间的差异,误差很小.
- Pd(100) 显示出最高的反应性,其次是Pd(211),然后是Pd(111).
- 层间的封闭 (大约. 1 nm) 和表面重建显著影响了氧气度和反应性.
结论:
- 界面封闭和特定表面的原子排列有效调节Pd表面上的界面氧度.
- 这项工作提供了指导,通过大规模模拟来理解局限系统中的批量-接口度联系.
- 这些发现对于设计用于工业应用的基于Pd的先进催化剂至关重要.
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