Interpretable Machine Learning Framework for Gas Adsorption Prediction and Screening on Transition Metal Dichalcogenides.
Two-dimensional transition metal dichalcogenides (TMDs) are promising gas-sensing materials, but adsorption behavior across doped host-dopant-gas spaces remains difficult to predict and interpret. Here, we develop a descriptor-informed machine-learning framework for adsorption-energy prediction and regime-level screeni...