◆ Journal of Materials Chemistry A2025-12-24· Artificial intelligence
Predicting the HER activity of SACs on MXenes with simple features and interpretable machine learning models
Chandra Chowdhury, Matteo Lovato, Giovanni Di Liberto, Francesc Viñes, Francesc Illas, Gianfranco Pacchioni, Livia Giordano
原始摘要（英文原文）· Original abstract
An interpretable machine learning model was developed using DFT data to predict hydrogen adsorption energies, enabling accurate and transparent screening of HER catalysts with performance comparable to the intrinsic accuracy of DFT methods.