All Articles

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

Effects of solutes on thermodynamic properties of (TMZrU)C (TM = Ta, Y) medium-entropy carbides: a first-principles study

Virtual sample generation in machine learning assisted materials design and discovery

Assessment of phase equilibria and thermodynamic properties in the Fe-RE (RE = rare earth metals) binary systems

Composition- and temperature-dependence of β to ω phase transformation in Ti-Nb alloys

Machine learning accelerated discovery of high transmittance in (K_0.5Na_0.5)NbO₃-based ceramics