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Data generated for the Ti–Al–Cr–V system of metallic alloys from our previous publication, where the composition of 102 alloys were computationally Pareto optimized with the objective of simultaneously maximizing the Young’s modulus and minimizing density for a range of temperatures, was the starting point of the current research, where compositions at different temperatures of these alloys were analyzed for phase stability in order to generate new data for compositions and volume fractions of stable phases at various temperatures. This resulted in a large dataset where a lot of data were still missing as all the phases are not stable at a given temperature for all the compositions. The concept of Self-Organizing Maps (SOM) was then applied to determine correlations between alloy compositions, stabilities of desired phases at various temperatures, associated Young’s moduli and densities, and the effect of the composition of phases on these properties. This work should help alloy designers to determine the required chemical composition of a new alloy with reference to the temperature of application of that alloy and see the effect of temperature and composition on stable phases and associated properties of alloys.


Originally published in Metals.

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