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The Materials Informatics Lab

We use the concepts of data science and materials science to design novel materials, identify materials synthesis pathways and study environmental sustainability of materials. 

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Welcome to Our Lab: A Quick Introduction

Dive into our world of scientific exploration by watching our introduction video. Discover how we're pushing the boundaries of knowledge and innovation in our quest to make impactful contributions to science and society. Join us on this exciting journey of discovery and innovation. Watch our video now to learn more about who we are and what we do!​​

PROJECTS

In the Materials Informatics Lab, or the MI-Lab, the research revolves around the fusion of data science (AI or machine learning) with materials computations to guide experiments and accelerate design of advanced materials. We primarily utilize first-principles electronic structure methods (DFT), molecular dynamics simulations, and many data-driven techniques, including deep learning, multi-fidelity learning and reinforcement learning. We focus on synthesis of metastable phases, discovery of “green polymers, and automation of materials laboratories.

Metastable Phases of Materials
Depolymerizable Polymers
Self-driving materials laboratory

LATEST PUBLICATION

Learning Metastable Phase diagram
Peptide Design
ML in Materials Science
Multifidelity Learning
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