We develop and apply a variety of computational methods, including: atomistic simulation, density functional theory and structure prediction to investigate the materials’ structure-property relation.

Our goal is to discover and design new materials in the following aspects:

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Materials Informatics

Big data and machine learning in materials sciences.

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Organic Crystal Polymorphism

Predicting the crystal structures for a given molecule could help determine the existence of different forms and suggest as yet unseen polymorphs of currently known structures.

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Defects in Materials

Understanding the structural and functional properties influenced by defects is key to optimizing next-gen materials needed for advanced energy applications.

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Materials Under Extreme Conditions

Extended solids formed under ultrahigh pressure exhibit dramatic changes in their properties and may offer significant improvements over their original forms.