The convergence of data science and catalysis: a comprehensive review of machine learning applications in accelerating selective catalytic reduction (SCR) catalyst design and performance prediction
Abstract
This review critically assesses ML approaches—from traditional algorithms to LLMs—for accelerating SCR catalyst design, highlighting data limitations and pathways toward knowledge-guided NO x abatement solutions.
Fields of Study & Subjects
Catalytic Processes in Materials Science
Catalysis and Oxidation Reactions
Machine Learning in Materials Science
Publication details
- Journal / source
- Environmental Science Nano
- Publisher
- Royal Society of Chemistry (RSC)
- Volume
- 13
- Issue
- 4
- Pages
- 1830–1852
- Publication date
- 1 January 2026
- Language
- EN