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Samuel Rothfarb

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Jul 2026

Data-Driven Material Design: Harnessing High-Throughput Simulations and AI

This work will present the current work on inverse material design, where AI methods—particularly generative pretrained transformers—are used to predict new material candidates based on desired properties, pushing the boundaries of materials innovation.

I. Gonzales, R. Ullberg, Andrew H Salij et al. · 0 citations