Elucidation and Design of NO Reduction Reaction Process by First-Principles Multiscale Simulation

通过第一性原理多尺度模拟阐明和设计 NO 还原反应过程

基本信息

  • 批准号:
    21J10648
  • 负责人:
  • 金额:
    $ 0.96万
  • 依托单位:
  • 依托单位国家:
    日本
  • 项目类别:
    Grant-in-Aid for JSPS Fellows
  • 财政年份:
    2021
  • 资助国家:
    日本
  • 起止时间:
    2021-04-28 至 2023-03-31
  • 项目状态:
    已结题

项目摘要

We studied the co-adsorption of NO-H2O on Cu(111) using the van der Waals density functional theory method. We first studied the adsorption of NO and H2O clusters on Cu(111). The energetics, adsorption geometries, and vibrational properties of several NO-H2O complexes are estimated, and the relative stabilities of those complexes are compared with respective NO and H2O clusters on Cu(111). We find that the mixed complexes between NO and H2O on Cu(111) are more stable than the separated clusters of NO and water, which arises from the hydrogen bonding between NO and H2O and NO - NO interaction. Electronic structure analysis indicates that attractive NO-H2O interaction arises from the hydrogen bonding with the enhancements of back-donation to valence orbitals of NO, while the NO - NO interaction arises from the hybridization among valance orbitals. The vibrational analysis also confirms the formation of the mixed NO-H2O complexes and N-O stretching modes are red-shifted due to hydrogen bonding with water. Our result provides an insightful interpretation of experimental observation.We also have studied the metal-support interaction (MSI) of the platinum metal group (PGM) supported on some metal oxide materials under three-way catalyst (TWC) operating conditions using machine-learning enhanced global optimization and thermodynamics.
采用货车德瓦尔斯密度泛函方法研究了NO-H2O在Cu(111)表面的共吸附.我们首先研究了NO和H_2O团簇在Cu(111)表面的吸附。计算了几种NO-H_2 O络合物的能量、吸附几何和振动性质,并与NO和H_2 O在Cu(111)表面上的相对稳定性进行了比较.结果表明,在Cu(111)表面上,NO和H_2O的混合络合物比NO和水的分离团簇更稳定,这是由于NO和H_2O之间的氢键以及NO - NO相互作用的结果。电子结构分析表明,NO-H_2 O相互作用主要是通过氢键作用产生的,且对NO价轨道的反馈作用增强,而NO-NO相互作用主要是通过价轨道间的杂化作用产生的.振动分析也证实了混合NO-H_2 O络合物的形成,并且由于与水的氢键作用,N-O伸缩模发生了红移。我们的研究结果提供了一个有见地的解释实验观察.我们还研究了铂族金属(PGM)负载在一些金属氧化物材料在三效催化剂(TWC)操作条件下的金属-载体相互作用(MSI)使用机器学习增强的全局优化和热力学.

项目成果

期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

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