most citedA machine learning-based classification approach for phase diagram prediction

46 citations · 61 across the 2 of their papers we have counts for

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2 papers

cond-mat.mtrl-sci2024★ 15 cited

Data-driven study of the enthalpy of mixing in the liquid phase

Guillaume Deffrennes, Bengt Hallstedt, Taichi Abe +5

The enthalpy of mixing in the liquid phase is a thermodynamic property reflecting interactions between elements that is key to predict phase transformations. Widely used models exi…

cond-mat.mtrl-sci2022★ 46 cited

A machine learning-based classification approach for phase diagram prediction

Guillaume Deffrennes, Kei Terayama, Taichi Abe +1

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