Suppr超能文献

在台阶状铂表面上常压下的一氧化碳(CO)吸附构型:由神经网络加速的第一性原理建模

CO organization at ambient pressure on stepped Pt surfaces: first principles modeling accelerated by neural networks.

作者信息

Sumaria Vaidish, Sautet Philippe

机构信息

Department of Chemical and Biomolecular Engineering, University of California Los Angeles CA 90094 USA

Department of Chemistry and Biochemistry, University of California Los Angeles CA 90094 USA.

出版信息

Chem Sci. 2021 Nov 15;12(47):15543-15555. doi: 10.1039/d1sc03827c. eCollection 2021 Dec 8.

Abstract

Step and kink sites at Pt surfaces have crucial importance in catalysis. We employ a high dimensional neural network potential (HDNNP) trained using first-principles calculations to determine the adsorption structure of CO under ambient conditions ( = 300 K and = 1 atm) on these surfaces. To thoroughly explore the potential energy surface (PES), we use a modified basin hopping method. We utilize the explored PES to identify the adsorbate structures and show that under the considered conditions several low free energy structures exist. Under the considered temperature and pressure conditions, the step edge (or kink) is totally occupied by on-top CO molecules. We show that the step structure and the structure of CO molecules on the step dictate the arrangement of CO molecules on the lower terrace. On surfaces with (111) steps, like Pt(553), CO forms quasi-hexagonal structures on the terrace with the top site preferred, with on average two top site CO for one multiply bonded CO, while in contrast surfaces with (100) steps, like Pt(557), present a majority of multiply bonded CO on their terrace. Short terraced surfaces, like Pt(643), with square (100) steps that are broken by kink sites constrain the CO arrangement parallel to the step edge. Overall, this effort provides detailed analysis on the influence of the step edge structure, kink sites, and terrace width on the organization of CO molecules on non-reconstructed stepped surfaces, yielding initial structures for understanding restructuring events driven by CO at high coverages and ambient pressure.

摘要

铂表面的台阶和扭结位点在催化过程中至关重要。我们使用通过第一性原理计算训练的高维神经网络势(HDNNP)来确定在环境条件(300 K和1 atm)下CO在这些表面上的吸附结构。为了全面探索势能面(PES),我们使用了一种改进的盆地跳跃方法。我们利用探索得到的PES来识别吸附质结构,并表明在所考虑的条件下存在几种低自由能结构。在所考虑的温度和压力条件下,台阶边缘(或扭结)完全被顶位吸附的CO分子占据。我们表明台阶结构以及台阶上CO分子的结构决定了较低台面上CO分子的排列。在具有(111)台阶的表面上,如Pt(553),CO在台面上形成准六边形结构,优先占据顶位,平均一个多重键合的CO对应两个顶位CO,而相比之下,具有(100)台阶的表面上,如Pt(557),其台面上大部分是多重键合的CO。短台面的表面,如Pt(643),具有被扭结位点打断的方形(100)台阶,限制了CO分子平行于台阶边缘的排列。总体而言,这项工作详细分析了台阶边缘结构、扭结位点和台面宽度对未重构台阶表面上CO分子排列的影响,为理解高覆盖率和环境压力下由CO驱动的重构事件提供了初始结构。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/96e6/8654054/19245f3f7584/d1sc03827c-f1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验