ArticleJournal of chemical theory and computation2023
Prediction of Redox Power for Photocatalysts: Synergistic Combination of DFT and Machine Learning.
Article in Journal of chemical theory and computation, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
6 citing papers in PubMed.
- High-Resolution Tuning of Iridium(III) 4'-Aryl-terpy Chromophores: A Hammett Parameter-Guided General Methodology for Systematic Property Control through Orbital Decoupling.Inorganic chemistry · 2026Article
- Silicon Photocatalytic Water-Treatment: Synthesis, Modifications, and Machine Learning Insights.Nanomaterials (Basel, Switzerland) · 2025Review
- Benchmarking Density Functionals for Ground- and Excited-State Reduction and Oxidation Potentials of Organic Photoredox Catalysts.The journal of physical chemistry. A · 2025Article
- Furan-Indole-Chromenone-Based Organic Photocatalyst for α-Arylation of Enol Acetate and Free Radical Polymerization Under LED Irradiation.Molecules (Basel, Switzerland) · 2025Article
- Machine Learning Approach to Vertical Energy Gap in Redox Processes.Journal of chemical theory and computation · 2024Article
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Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The accurate prediction of excited state properties is a key element of rational photocatalyst design. This involves the prediction of ground and excited state redox potentials, for which an accurate description of electronic structures is needed. Even with highly sophisticated computational approaches, however, a number of difficulties arise from the complexity of excited state redox potentials, as they require the calculation of the corresponding ground state redox potentials and the estimation of the 0-0 transition energies (
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Registered trials
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