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A data-driven comparative study of thermomechanical properties in rare-earth zirconate and tantalate oxides for thermal barrier coatings

Agentic material science

Accelerating materials discovery via AI-Agent integration of large language models and simulation tools

Machine learning-accelerated transition state prediction for strain-engineered high-entropy alloy catalysts

Multi-objective optimization of fiber laser welding parameters for 316L stainless steel

Exploring the Pareto front of strength-conductivity trade-off: interpretable machine learning for property prediction and composition design in high-strength high-conductivity Cu alloys

Machine learning-driven new paradigm for Co-based superalloys

Uncertainty estimation affects predictor selection and its calibration improves materials optimization

Multiscale simulations of Ge–Sb–Se–Te phase-change alloys for photonic memory applications

Advances in graph neural networks for alloy design and properties predictions: a review

The synergy of geometric tolerance factor and machine learning in discovering stable materials

Ultralow thermal conductivity via weak interactions in PbSe/PbTe monolayer heterostructure for thermoelectric design