Most Cited Papers In Last Two Years

A review on high-throughput development of high-entropy alloys by combinatorial methods

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

Graph neural networks for molecular and materials representation

Recent advances and applications of machine learning in electrocatalysis

Mapping pareto fronts for efficient multi-objective materials discovery

Data-driven design of eutectic high entropy alloys

Virtual sample generation in machine learning assisted materials design and discovery

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

Thermodynamic modeling of the Fe-Sn system including an experimental re-assessment of the liquid miscibility gap

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

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

Recent advances in the interface structure prediction for heteromaterial systems

Characterizing the wetting behavior of 2D materials: a review

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

Development of an accurate “composition-process-properties” dataset for SLMed Al-Si-(Mg) alloys and its application in alloy design

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

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