Trade-Off Analysis in High-Throughput Materials Exploration

This Research Article presents a strategy to identify the optimum compositions in metal alloys with certain desired properties in a high-throughput screening environment, using a multiobjective optimization approach. In addition to the identification of the optimum compositions in a primary screening, the strategy also allows pointing to regions in the compositional space where further exploration in a secondary screening could be carried out. The strategy for the primary screening is a combination of two multiobjective optimization approaches namely Pareto optimality and desirability functions. The experimental data used in the present study have been collected from over 200 different compositions belonging to four different alloy systems. The metal alloys (comprising Fe, Ti, Al, Nb, Hf, Zr) are synthesized and screened using high-throughput technologies. The advantages of such a kind of approach compared to the limitations of the traditional and comparatively simpler approaches like ranking and calculating figures of merit are discussed.