TiO2光脱附的从头算机理和设计原理

IF 9.4 1区 材料科学 Q1 CHEMISTRY, PHYSICAL
Aaron R. Altman, Felipe H. da Jornada
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引用次数: 0

摘要

光催化反应通常表现出快速的动力学和高的产物选择性,这些品质在热过程中很难同时实现。然而,由于在光学激发态中真实模拟催化剂的挑战,光驱动机制仍然知之甚少。在这里,我们应用多体微扰理论(MBPT)计算,通过研究金红石型TiO2(110)表面质子解吸的典型光催化反应来深入了解这些机制。我们的研究结果揭示了光激发后的剧烈变化,包括脱附能减少50%以上和能量垒的出现。我们使用基于Fano理论的可推广模型来合理化这些发现,并解释了当质子从表面分离时,激子效应的惊人增加。我们的模型还将各种电离势的排列与激发态势能表面的形状联系起来。这些结果没有被约束密度泛函理论定性地捕获,强调了MBPT计算如何为光催化反应设计提供信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Ab initio mechanisms and design principles for photodesorption from TiO2

Ab initio mechanisms and design principles for photodesorption from TiO2

Photocatalytic reactions often exhibit fast kinetics and high product selectivity, qualities difficult to achieve simultaneously in thermal processes. However, photo-driven mechanisms remain poorly understood due to challenges in realistically modeling catalysts in optically excited states. Here, we apply many-body perturbation theory (MBPT) calculations to gain insight into these mechanisms by studying a prototypical photocatalytic reaction, proton desorption from a rutile TiO2 (110) surface. Our results reveal dramatic changes upon photoexcitation, including an over 50% reduction in the desorption energy and the emergence of an energy barrier. We rationalize these findings using a generalizable model based on Fano theory, and explain the surprising increase of excitonic effects as the proton detaches from the surface. Our model also connects the alignment of various ionization potentials to the shape of the excited-state potential energy surface. These results, not qualitatively captured by constrained density-functional theory, highlight how MBPT calculations can inform photocatalytic reaction design.

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来源期刊
npj Computational Materials
npj Computational Materials Mathematics-Modeling and Simulation
CiteScore
15.30
自引率
5.20%
发文量
229
审稿时长
6 weeks
期刊介绍: npj Computational Materials is a high-quality open access journal from Nature Research that publishes research papers applying computational approaches for the design of new materials and enhancing our understanding of existing ones. The journal also welcomes papers on new computational techniques and the refinement of current approaches that support these aims, as well as experimental papers that complement computational findings. Some key features of npj Computational Materials include a 2-year impact factor of 12.241 (2021), article downloads of 1,138,590 (2021), and a fast turnaround time of 11 days from submission to the first editorial decision. The journal is indexed in various databases and services, including Chemical Abstracts Service (ACS), Astrophysics Data System (ADS), Current Contents/Physical, Chemical and Earth Sciences, Journal Citation Reports/Science Edition, SCOPUS, EI Compendex, INSPEC, Google Scholar, SCImago, DOAJ, CNKI, and Science Citation Index Expanded (SCIE), among others.
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