Exploring the impact of operating parameters and catalyst design on propane catalytic oxidation: a machine learning perspective
Abstract
We integrate a database, machine learning models, and SHAP analysis to guide the design of efficient catalysts for low-temperature propane catalytic oxidation, enabling accurate performance prediction and key parameter identification.
Fields of Study & Subjects
Catalysis and Oxidation Reactions
Machine Learning in Materials Science
Catalytic Processes in Materials Science
Publication details
- Journal / source
- Physical Chemistry Chemical Physics
- Volume
- 28
- Issue
- 3
- Pages
- 2454–2466
- Publication date
- 1 January 2026
- Language
- EN