Computational Studies of Photocatalysis with Metal–Organic Frameworks
Metal–organic frameworks (MOFs) as photocatalysts and photocatalyst supports combine several advantages of homogeneous and heterogeneous catalyses, including stability, post‐reaction separation, catalyst reusability, and tunability, and they have been intensively studied for photocatalytic applicati...
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Published in | Energy & environmental materials (Hoboken, N.J.) Vol. 2; no. 4; pp. 251 - 263 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Hoboken
Wiley Subscription Services, Inc
01.12.2019
Wiley Blackwell (John Wiley & Sons) |
Subjects | |
Online Access | Get full text |
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Summary: | Metal–organic frameworks (MOFs) as photocatalysts and photocatalyst supports combine several advantages of homogeneous and heterogeneous catalyses, including stability, post‐reaction separation, catalyst reusability, and tunability, and they have been intensively studied for photocatalytic applications. There are several reviews that focus mainly or even entirely on experimental work. The present review is intended to complement those reviews by focusing on computational work that can provide a further understanding of the photocatalytic properties of MOF photocatalysts. We first present a summary of computational methods, including density functional theory, combined quantum mechanical and molecular mechanical methods, and force fields for MOFs. Then, computational investigations on MOF‐based photocatalysis are briefly discussed. The discussions focus on the electronic structure, photoexcitation, charge mobility, and photoredox catalysis of MOFs, especially the widely studied UiO‐66‐based MOFs.
Metal–organic frameworks (MOFs) have many advantages as heterogeneous photocatalysts or photocatalytic supports. This review explains the computational tools used to understand the mechanisms and identify potential new photocatalysts, and it discusses theoretical work on this subject. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 USDOE |
ISSN: | 2575-0356 2575-0356 |
DOI: | 10.1002/eem2.12051 |