All Articles

Lithium-ion battery health prognosis via electrochemical impedance spectroscopy using CNN-BiLSTM model

Thermal stability prediction of copolymerized polyimides via an interpretable transfer learning model

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

Theoretical design of dendrite-free zinc anode through intrinsic descriptors from symbolic regression

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

Clustering molecular energy landscapes by adaptive network embedding

Crystal structure prediction using neural network potential and age-fitness Pareto genetic algorithm

High hydrogen evolution activities of dual-metal atoms incorporated N-doped graphenes achieved by coordination regulation

Computational design of spatially confined triatomic catalysts for nitrogen reduction reaction

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

Regulating the electrocatalytic performance for nitrogen reduction reaction by tuning the N contents in Fe₃@N_xC_20-x (x = 0~4): a DFT exploration

Physics infused machine learning force fields for 2D materials monolayers

Recent advances in the interface structure prediction for heteromaterial systems

Understanding oxidation resistance of Pt-based alloys through computations of Ellingham diagrams with experimental verifications

Characterizing the wetting behavior of 2D materials: a review

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

Recent advances and applications of machine learning in electrocatalysis