Interpretable Machine Learning for Accelerating Reverse Design and Optimizing CO2 Methanation Catalysts with High Activity at Low Temperatures

Q Yang, R Bao, D Rong, J Xiao, J Zhou… - Industrial & …, 2024 - ACS Publications
CO2 methanation represents a promising technological pathway for achieving efficient
carbon dioxide resource utilization and mitigation of greenhouse gas emissions. However …

[HTML][HTML] Learning Effective Good Variables from Physical Data

G Barletta, G Trezza, E Chiavazzo - Machine Learning and Knowledge …, 2024 - mdpi.com
We assume that a sufficiently large database is available, where a physical property of
interest and a number of associated ruling primitive variables or observables are stored. We …