Literature DB >> 28457131

Fast Prediction of CO Binding Energy via the Local Structure Effect on PtCu Alloy Surfaces.

Zhi-Jian Zhao1, Rentao Mu1, Xiaohui Wang2, Jinlong Gong1.   

Abstract

CO poisoning is a major problem for Pt-based catalysts in various catalytic processes. Thus, the prediction of CO binding energies over Pt alloy surfaces is fundamentally important to evaluate their CO poisoning tolerance. This article describes the effect of surface and subsurface coordination environments on the CO binding strength over PtCu alloy surfaces by employing density functional theory calculations. We show that the existence of surface Pt neighbors weakens the CO binding strength on Pt, whereas the subsurface Pt neighbors play the opposite role. Crystal orbital Hamilton population analysis suggests a stronger antibonding interaction for the Ptsurface-Ptsubsurface bond than for the Ptsurface-Ptsurface bond, which indicates less stable subsurface Pt atoms that hence generate an activated surface Pt that attracts CO more strongly. On the basis of the calculated CO binding energies, an empirical formula, with Pt-Pt coordination numbers as the variables, has been fitted to achieve a fast prediction of CO binding energy over PtCu alloy surfaces.

Entities:  

Year:  2017        PMID: 28457131     DOI: 10.1021/acs.langmuir.7b00788

Source DB:  PubMed          Journal:  Langmuir        ISSN: 0743-7463            Impact factor:   3.882


  3 in total

1.  Tunable syngas production from photocatalytic CO2 reduction with mitigated charge recombination driven by spatially separated cocatalysts.

Authors:  Ang Li; Tuo Wang; Xiaoxia Chang; Zhi-Jian Zhao; Chengcheng Li; Zhiqi Huang; Piaoping Yang; Guangye Zhou; Jinlong Gong
Journal:  Chem Sci       Date:  2018-05-25       Impact factor: 9.825

2.  Three-Phase Photocatalysis for the Enhanced Selectivity and Activity of CO2 Reduction on a Hydrophobic Surface.

Authors:  Ang Li; Qian Cao; Guangye Zhou; Bernhard V K J Schmidt; Wenjin Zhu; Xintong Yuan; Hailing Huo; Jinlong Gong; Markus Antonietti
Journal:  Angew Chem Int Ed Engl       Date:  2019-09-04       Impact factor: 15.336

Review 3.  Applications of Machine Learning in Alloy Catalysts: Rational Selection and Future Development of Descriptors.

Authors:  Ze Yang; Wang Gao
Journal:  Adv Sci (Weinh)       Date:  2022-03-01       Impact factor: 17.521

  3 in total

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