THE SYNTHESIS PROJECT

Advances in computational materials design have enabled rapid screening for desirable properties of both real and virtual compounds. However, the pace of commercially-realized advanced materials may now be limited by trial-and-error synthesis techniques.

The goal of this research project is to advance computational learning around materials synthesis approaches by creating a predictive synthesis system for advanced materials design and processing — to do for materials synthesis what modern computational methods have done for materials properties.

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This predictive synthesis system has been applied to several materials science domains including metallic oxides, titania, perovskites, zeolites, metal-insulator transition materials, solid-state electrolytes, alloys, and alternative cements. 

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