Group Highlight

  • Xin Research Group 2023

    Together, we are on a journey of discovery, tackling mysteries and making the future a bit brighter with every bit of efforts.

  • Bridging the complexity gap in computational heterogeneous catalysis with machine learning

    It discusses strategies to utilize machine learning to bridge the complexity gap that currently exists between real and computed catalytic systems.

    View the article.
  • Interpretable Machine Learning for Catalytic Materials Design toward Sustainability

    Integrating domain knowledge into artificial intelligence, this Account signifies a transformative shift in catalytic materials discovery toward a sustainable future. Cover designed by Tianyou Mou with help from Xue Han.

    View the article.
  • Infusing theory into deep learning for interpretable reactivity prediction

    A new artificial intelligence framework is developed that can accelerate discovery of materials for important technologies, such as fuel cells and carbon capture devices.

    Read more at VT news.
  • Bayesian learning of chemisorption for bridging the complexity of electronic descriptors

    A Bayesian learning approach based on ab-initio adsorption properties and the d-band model captures physics of adsorbate-metal interactions.

    Read more at VT news.

Welcome to the Xin Group @ Virginia Tech

Our group focuses on modeling structure-function relationships of nanoscale assemblies for energy and electronics applications. Ongoing research includes design of hybrid materials for catalysis, solar energy capture and storage, charge transport, etc. This research will be supported by a collaborative effort in assembling diverse classes of functional materials on the nanoscale. To guide materials design, special attention has been given to the development of a multiscale modeling framework that integrates our expertise in ab-initio calculations, kinetic simulations, and statistical learning. Motivated by recent advances in ultrafast science, we specifically tackle challenging problems in energy and electronics that require fundamental understanding of atomistic and charge dynamiX at interfaces.

Publications

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