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表面覆盖率作为预测电化学CO还原选择性趋势的重要参数。

Surface Coverage as an Important Parameter for Predicting Selectivity Trends in Electrochemical CO Reduction.

作者信息

Morrison Andrew R T, Ramdin Mahinder, van der Broeke Leo J P, de Jong Wiebren, Vlugt Thijs J H, Kortlever Ruud

机构信息

Large-Scale Energy Storage, Process & Energy Department, Faculty of Mechanical, Maritime and Materials Engineering, Delft University of Technology, Leeghwaterstraat 39, 2628 CB Delft, The Netherlands.

Engineering Thermodynamics, Process & Energy Department, Faculty of Mechanical, Maritime and Materials Engineering, Delft University of Technology, Leeghwaterstraat 39, 2628 CB Delft, The Netherlands.

出版信息

J Phys Chem C Nanomater Interfaces. 2022 Jul 28;126(29):11927-11936. doi: 10.1021/acs.jpcc.2c00520. Epub 2022 Jul 13.

Abstract

The electrochemical CO reduction reaction (CORR) is important for a sustainable future. Key insights into the reaction pathways have been obtained by density functional theory (DFT) analysis, but so far, DFT has been unable to give an overall understanding of selectivity trends without important caveats. We show that an unconsidered parameter in DFT models of electrocatalysts-the surface coverage of reacting species-is crucial for understanding the CORR selectivities for different surfaces. Surface coverage is a parameter that must be assumed in most DFT studies of CORR electrocatalysts, but so far, only the coverage of nonreacting adsorbates has been treated. Explicitly treating the surface coverage of reacting adsorbates allows for an investigation that can more closely mimic operating conditions. Furthermore, and of more immediate importance, the use of surface coverage-dependent adsorption energies allows for the extraction of ratios of adsorption energies of CORR intermediates (COOH and HCOO) that are shown to be predictive of selectivity and are not susceptible to systematic errors. This approach allows for categorization of the selectivity of several monometallic catalysts (Pt, Pd, Au, Ag, Zn, Cu, Rh, W, Pb, Sn, In, Cd, and Tl), even problematic ones such as Ag or Zn, and does so by only considering the adsorption energies of known intermediates. The selectivity of the further reduction of COOH can now be explained by a preference for Tafel or Heyrovsky reactions, recontextualizing the nature of selectivity of some catalysts. In summary, this work resolves differences between DFT and experimental studies of the CORR and underlines the importance of surface coverage.

摘要

电化学CO还原反应(CORR)对可持续未来至关重要。通过密度泛函理论(DFT)分析已获得了对反应途径的关键见解,但到目前为止,DFT在没有重要限制条件的情况下无法对选择性趋势给出全面理解。我们表明,电催化剂DFT模型中一个未被考虑的参数——反应物种的表面覆盖率——对于理解不同表面的CORR选择性至关重要。表面覆盖率是大多数CORR电催化剂DFT研究中必须假定的一个参数,但到目前为止,仅处理了非反应性吸附质的覆盖率。明确处理反应性吸附质的表面覆盖率使得能够进行更接近模拟操作条件的研究。此外,更直接重要的是,使用依赖于表面覆盖率的吸附能能够提取CORR中间体(COOH和HCOO)的吸附能之比,这些比值被证明可预测选择性且不易受系统误差影响。这种方法能够对几种单金属催化剂(Pt、Pd、Au、Ag、Zn、Cu、Rh、W、Pb、Sn、In、Cd和Tl)的选择性进行分类,甚至包括像Ag或Zn这样有问题的催化剂,并且仅通过考虑已知中间体的吸附能来做到这一点。现在可以通过对塔菲尔或海洛夫斯基反应的偏好来解释COOH进一步还原的选择性,从而重新审视一些催化剂选择性的本质。总之,这项工作解决了DFT和CORR实验研究之间的差异,并强调了表面覆盖率的重要性。

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