Di Zhang

Pareto Optimization of a Cobalt Carbide Catalyst for Syngas Conversion: Balancing Activity and Selectivity via Interpretable Active Learning

An active-learning (AL)-assisted machine-learning (ML) framework was developed to predict the CO conversion and light-hydrocarbon selectivity over cobalt carbide catalysts, and the predicted Pareto-optimal catalyst configurations showed good agreement with representative reported experimental catalysts.