Machine-learning-assisted descriptor identification for catalysts in catalytic ozonation of VOCs
Abstract
-xylene and 1,2-dichloroethane (1,2-DCE) under constrained conditions, which validated the accuracy of the SHAP analysis. This work highlights ML as a practical tool for efficient design of catalysts, and provides appropriate descriptors for ML-assisted development of catalysts for catalytic ozonation of VOCs. The protocol allows for the prediction of promising promoter combinations for catalysts under various constrained conditions, providing guidance for catalyst design and development.
Fields of Study & Subjects
Catalytic Processes in Materials Science
Machine Learning in Materials Science
Catalysis and Oxidation Reactions
Publication details
- Journal / source
- Physical Chemistry Chemical Physics
- Publisher
- Royal Society of Chemistry (RSC)
- Volume
- 28
- Issue
- 15
- Pages
- 9720–9725
- Publication date
- 1 January 2026
- Language
- EN