Graduate Student Seminar
December 05, 2025
12:45 p.m. ET
7500 Wean Hall
December 05, 2025
12:45 p.m. ET
7500 Wean Hall
Quantum materials such as delafossites and perovskites exhibit remarkable magnetic, electronic, and catalytic behaviors arising from their complex atomic structures. Understanding and predicting these properties remain challenging due to their vast compositional diversity and correlated interactions. Recent advances in graph-based machine learning integrated with ab initio modeling are helping to address these challenges. In delafossites, graph neural networks reveal how stacking geometry and d-shell occupancy govern magnetic ordering, while in perovskite oxides, machine learning enables rapid prediction of electronic descriptors - such as oxygen p- and metal d-band centers - directly from unrelaxed structures, accelerating catalyst discovery. These studies highlight how physics-informed AI approaches can complement theory and experiment to uncover structure–property relationships across materials classes. The seminar will discuss emerging opportunities and challenges in integrating explainable AI with quantum materials research for data-driven materials design.
Mina Yoon, Senior R&D Staff & Group Leader, Microstructural Evolution Modeling GroupDr. Mina Yoon is the Group Leader of Microstructural Evolution Modeling Group in the Materials Science and Technology Division (MSTD) at Oak Ridge National Laboratory (ORNL) and a Joint Faculty at the Department of Physics and Astronomy, University of Tennessee (UTK), Knoxville. Her research focuses on the application of materials theory, advanced computational approaches, and data analytics/ML to understand fundamental physical phenomena and translate the knowledge into the development of novel energy materials, including nanoscale materials and topological quantum materials. Prior to joining the laboratory Dr. Yoon spent three years on a Max Planck Fellowship at the Fritz Haber Institute of the Max Planck Society. She is a recipient of the Lee Hsun Young Scientist Award from the Institute of Metal Research, Chinese Academy of Science, and Outstanding Scholarly Output team award in 2020 and 2023 UT-Battelle Awards Night program.
December 10 2025
8:30 AM - 5:00 PM ET
Materials Science and Engineering
Molecular Engineering of Soft Materials Symposium
The symposium will highlight cross-disciplinary research across CMU departments, with the goal of advancing soft materials research.
5201 Scott Hall
December 11 2025
4:00 PM ET
Materials Science and Engineering
M.S. Program Information Session
Join us online to learn more about becoming part of the graduate student community through our master's degree programs.
Virtual