MSE Seminar – Prof. Aloysius Soon (15 July 2026)
15 Jul 2026 (Wed) | 04:00 PM - 05:30 PM
MSE Seminar – Prof. Aloysius Soon (15 July 2026)
| Title: | Intelligent Surface Science: Integrating natural and artificial intelligence for data-driven surface structure determination |
| Speaker: | Prof. Aloysius Soon Full Professor Department of Materials Science & Engineering Yonsei University |
| Date: | 15 July 2026 (Wednesday) |
| Time: | 16:00 – 17:30 |
| Venue: | P4704, 4/F, Yeung Kin Man Academic Building |
| Abstract: | Recent advances in experimental and theoretical methods have greatly enhanced our ability to characterize the physical, chemical, and crystallographic properties of well-defined surfaces and interfaces. In particular, the study of low-dimensional nanomaterials on metal substrates has attracted considerable interest, driven by progress in surface spectroscopy and microscopy. Computational simulations have played a complementary role, providing critical insights through data-driven and theory-guided atomistic modeling. However, reconciling experimental and theoretical descriptions of supported nanostructures remains a major challenge. This talk discusses how modern computational approaches and artificial intelligence (AI) are helping to bridge this gap in theoretical surface science. We revisit the application of ab initio atomistic thermodynamics – commonly used in computational catalysis – to predict stable catalyst surfaces under realistic technical conditions. By incorporating AI-driven global optimization, this method addresses the longstanding pressure and temperature divide between ultra-high vacuum experiments and industrial reactor environments. Using a metastable O/Cu surface oxide as a case study, we illustrate how AI-enhanced first-principles simulations reveal novel nanostructures, thereby broadening the materials search space and reducing dependence on experimental intuition. Looking forward, we showcase the potential of integrating these approaches and extending thermodynamic analysis using nature-inspired collective intelligence. This integrated strategy paves the way for intelligent, data-driven surface structure determination and the discovery of industrially relevant interfacial configurations. |
| Enquiries: | mse@cityu.edu.hk |