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Machine learning assisted crystal structure prediction made simple

Applications of machine learning method in high-performance materials design: a review

Borides as promising M₂AX phase materials with high elastic modulus using machine learning and optimization

A deep neural network potential model for transition metal diborides

Data-driven strategy for bandgap database construction of perovskites and the potential segregation study

Searching new cocrystal structures of CL-20 and HMX via evolutionary algorithm and machine learning potential

Local environment interaction-based machine learning framework for predicting molecular adsorption energy

Investigation of dual atom doped single-layer MoS₂ for electrochemical reduction of carbon dioxide by first-principle calculations and machine-learning

Physics infused machine learning force fields for 2D materials monolayers

Recent advances in the interface structure prediction for heteromaterial systems

Machine learning for prediction of CO₂/N₂/H₂O selective adsorption and separation in metal-zeolites

Recent advances and applications of machine learning in electrocatalysis