Straightforward computational determination of energy-transfer kinetics through the application of the Marcus theory

Abstract

Energy transfer (EnT) photocatalysis holds the potential to revolutionize synthetic chemistry, unlocking the excited-state reactivity of non-chromophoric compounds via indirect sensitization. This strategy gives access to synthetic routes to valuable molecular scaffolds that are otherwise inaccessible through ground-state pathways. Despite the promising nature of this chemistry, it still represents a largely uncharted area for computational chemistry, hindering the development of structure–activity relationships and design rules to rationally exploit the potential of EnT photocatalysis. Here, we examined the application of the classical Marcus theory in combination with DFT calculations as a convenient strategy to estimate the kinetics of EnT processes, focusing on the indirect sensitization of alkenes recently reported by Gilmour, Kerzig and co-workers for subsequent isomerization [Zähringer et al., J. Am. Chem. Soc., 2023, 145, 21576]. Our results demonstrate a remarkable capability of this approach to estimate free-energy barriers for EnT processes with high accuracy, yielding precise qualitative assessments and quantitative predictions with typical discrepancies of less than 2 kcal mol−1 compared to experimental values and a small mean average error (MAE) of 1.2 kcal mol−1.

Graphical abstract: Straightforward computational determination of energy-transfer kinetics through the application of the Marcus theory

Supplementary files

Article information

Article type
Edge Article
Submitted
22 May 2024
Accepted
02 Aug 2024
First published
07 Aug 2024
This article is Open Access

All publication charges for this article have been paid for by the Royal Society of Chemistry
Creative Commons BY-NC license

Chem. Sci., 2024, Advance Article

Straightforward computational determination of energy-transfer kinetics through the application of the Marcus theory

A. Solé-Daura and F. Maseras, Chem. Sci., 2024, Advance Article , DOI: 10.1039/D4SC03352C

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