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Farthest point sampling in property designated chemical feature space as an effective strategy for enhancing the machine learning model performance for small scale chemical dataset

Effects of nonlinearity and inter-feature coupling in machine learning studies of Nb alloys with center-environment features

Exploring generic fractions of multi-origin asphalts and revisiting the linkage to their bulk properties via machine learning

Machine learning-enabled optoelectronic material discovery: a comprehensive review

Hot deformation behavior investigation of heat-resistant aluminum matrix composite based on Arrhenius model and machine learning

Phase-field-informed machine learning on creep behavior of Ni-based single-crystal superalloys

Accelerated discovery of high-performance small-molecule hole transport materials via molecular splicing, high-throughput screening, and machine learning

Uncertainty aware design space modeling for sample efficiency in material design of bainitic steels

FT²DP: large atomic model fine-tuned machine learning potential for accelerating atomistic simulation of iron-based Fischer-Tropsch synthesis

Multi-objective optimization in machine learning assisted materials design and discovery

How AI guided the development of green hydrogen production: in the case of solid oxide electrolysis cell?

Prediction of thermal conductivity in multi-component magnesium alloys based on machine learning and multiscale computation