Pre-onlines
The synergy of geometric tolerance factor and machine learning in discovering stable materials
Multiscale simulations of Ge-Sb-Se-Te phase-change alloys for photonic memory applications
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
A data-driven comparative study of thermomechanical properties in rare-earth zirconate and tantalate oxides for thermal barrier coatings
Advances in Graph Neural Networks for alloy design and properties predictions: a review
Advancing carbon dots research with machine learning: a comprehensive review
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
Uncertainty estimation affects predictor selection and its calibration improves materials optimization
Multi-objective optimization of fiber laser welding parameters for 316L stainless steel
Enhanced multi-tuple extraction for materials: integrating pointer networks and augmented attention
Quantification and rating of casting blowhole defects using instance segmentation algorithm
Machine learning and shap-based prediction of multifactor thermal-oxidative aging behavior in glass fiber reinforced polyamide6
Machine learning-driven morphology identification and classification of high-throughput functional oxide films
Computer vision for efficient object detection and segmentation in molecular image analysis
A hybrid deep learning model for robust and data-efficient lithium-ion battery remaining useful life prediction
Physically synthetic data for deep learning-based visual scratch inspection of aerospace alloys with complex geometries
