As the big data generated by the development of modern experiments and computing
technology becomes more and more accessible, the material design method based on …

Understanding the phase stability of a chemical system constitutes the foundation of
materials science. Knowledge of the equilibrium state of a system under arbitrary …

Abstract Knowledge of phase diagrams is essential for material design as it helps in
understanding microstructure evolution during processing. The determination of phase …

The lack of appropriate data and data imbalance hindered the development of ML models
for identifying novel high-entropy ceramics. To circumvent data imbalance for ML-based …

Phase diagrams provide considerable information that is vital for materials exploration.
However, the determination of multidimensional phase diagrams typically requires a …

Abstract Machine learning emerges to accelerate first-principles calculations in materials
discovery and property prediction, but developing high-accuracy prediction models requires …

Phase boundary indicates the conditions of transition between phase regions, which is a key
constituent of a phase diagram. We propose an approach to determine the phase boundary …

Stimuli-responsive polymers with complicated but controllable shape-morphing behaviors
are critically desirable in several engineering fields. Among the various shape-morphing …

Obtaining a fine approximation of a black-box function is important for understanding and
evaluating innovative materials. Active learning aims to improve the approximation of black …

To know phase diagrams is a time saving approach for developing novel materials. To
efficiently construct phase diagrams, a machine learning technique was developed using …