Research

At MCIG, we are a group of computational materials scientists interested in developing and leveraging fundamental knowledge and theories to address critical questions in practical material applications. By coupling density functional theory (DFT) calculations, molecular dynamic (MD) simulations, and CALPHAD modeling with high-throughput computation and machine learning techniques, we aim to develop novel computational and data-science approaches to understand and design novel materials and optimize their synthesis and processing pathways. Our research spans advanced structural alloys and functional inorganic compounds, centering on understanding fundamental mechanisms governing material deformation, phase transformation, phase equilibria, electronic functionality, and the intricate relationships between structure, processing, and properties. By closely collaborating with experimentalists, our goal is to develop integrated computational approaches and databases for quantitative designs of materials chemistry and synthesis/processing pathways, thereby speeding up the innovation, development, and manufacturing of new materials.

The current research at MCIG focuses on:

• Data-driven design of complex concentrated alloys
• Multiscale modeling of deformation mechanisms in Mg alloys
• Machine-learning-facilitated predictions of synthesis pathways for novel inorganic compounds
• Structure-processing-property relationships of Titania nanofilaments