Unfolding the structure-property relationships of Li2S anchoring on two-dimensional materials with high-throughput calculations and machine learning

Lithium-sulfur (Li-S) batteries are notable for their high theoretical energy density, but the ‘shuttle effect’ and the limited conversion kinetics of Li-S species can downgrade their actual performance. An essential strategy is to design anchoring materials (AMs) to appropriately adsorb Li-S species. Herein, we propose a new three-procedure protocol, named InfoAd (Informative Adsorption) to evaluate the anchoring of Li2S on two-dimensional (2D) materials and disclose the underlying importance of material features by combining high-throughput calculation workflow and machine learning (ML). In this paradigm, we calculate the anchoring of Li2S on 1255 2D AxBy (B in the VIA/VIIA group) materials and pick out 44 (un)reported nontoxic 2D binary AxBy AMs, in which the importance of the geometric features on the anchoring effect is revealed by ML for the first time. We develop a new Infograph model for crystals to accurately predict whether a material has a moderate binding with Li2S and extend it to all 2D materials. Our InfoAd protocol elucidates the underlying structure–property relationship of Li2S adsorption on 2D materials and provides a general research framework of adsorption-related materials for catalysis and energy/substance storage.