| Description |
Prof. Sandro Scandolo will give a talk on his research in computation modeling of materials at extreme conditions of pressure and temperature. The talk follows up the lecture given by Dr. Musa Al Noor, Lawrence Berkeley National Laboratory & University of California, USA, giving an overview of condensed matter physics and ab initio methods on June 23rd. Abstract of Prof. Scandolo's talk: A Journey to the Center of the Earth with Deep-Learning Simulations Buried more than 5,000 km deep, the Earth's inner core is still largely unknown. Thanks to seismic data, we know its density and pressure, and we know that it is a solid composed mainly of iron. But we don't know its temperature, its crystal structure, and why transverse (so-called shear) seismic waves propagate so slowly. Despite recent advances, it is still impossible to reproduce the pressure and temperature conditions of the Earth's center in a controlled way in the laboratory. First-principles atomistic simulations have provided useful insights, but they are limited to simulation cells containing only a few hundred atoms. Using “deep learning” techniques, we were able to extend the size of the simulation cells to millions of atoms, while maintaining “chemical” accuracy in describing the interactions between atoms [1]. Large-scale simulations indicate that the inner core could be composed of a cubic (bcc) alloy of iron and silicon. This Fe-based solid solution reproduces geophysical and seismic data better than any structure hypothesized so far [2,3], and opens new horizons in our understanding of the deepest layers of the Earth. [1] Z. Li, S. Scandolo, Physical Review B 109, 184108 (2024); Computer Physics Communications 304, 109307 (2024) [2] Z. Li, S. Scandolo, Geophysical Research Letters 51, e2024GL110357 (2024) [3] Z. Li, S. Scandolo, Nature Communications, in press (2025) |
PWF Sudan: Expanding Physics Horizons in Sudan: Leveraging Online Seminars for Growth - Sandro Scandolo: A Journey to the Center of the Earth with Deep-Learning Simulations
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