VIRTUAL

 Thursday, March 31st    2022

3:45 – 4:45 pm (MT)

WEBEX 

 Speaker:  Prof. Ivan Oleynik,

University of South Florida

“Materials in Extremes: Discovery Science with Big Computers and Machine-Learning”

 

Abstract: 

Being of utmost importance for developing models of planetary interiors, achieving inertial fusion energy, and stockpile stewardship, the behavior of matter at extreme pressures and temperatures is the current research frontier, which challenges our understanding of fundamental physics at the atomic scale. Recent experiments involving powerful lasers, pulsed power and bright X-ray sources opened up an exciting opportunity to recreate extreme conditions in the laboratory and observe materials response at the lattice level. However, to fully uncover atomic-scale dynamics of materials response in dynamic compression experiments, predictive atomic scale molecular dynamics (MD) simulations at experimental time and length scales are urgently sought. In this talk I will describe our recent advance in developing machine learning interatomic potentials that provide description of bond-breaking and remaking at extreme conditions with unprecedented quantum accuracy. Algorithmic innovations in the implementation of quantum-accurate machine learning molecular dynamics on GPU-based supercomputers and access to the most powerful high-performance computing systems in the world enable transformative science impact of billion atom simulations by uncovering synthesis pathways of elusive BC8 post-diamond high pressure phase of carbon, atomic-scale mechanisms of inelastic deformations and anomalously high strength of shock-compressed diamond

Bio:

Ivan Oleynik is a computational physicist whose research focused on studies of matter at extreme pressures and temperatures, design and prediction of properties of novel materials, and the development of new methods for materials simulations at the atomic level. He is best known for large-scale molecular dynamics simulations of shock compression of materials, computational discovery of high-nitrogen energetic materials, and the theory and applications of analytic bond order potentials.

Ivan has recently led collaborative simulation teams to successfully compete for leadership class high performance computing (HPC) allocations within DOE’s ASCR Leadership Class Computing Challenge (ALCC) and the Innovative and Novel Computational Impact on Theory and Experiment (INCITE) programs. He is also leading collaborative experimental/theory/simulation teams to perform experiments at Sandia’s Z pulsed power facility and National Ignition Facility at Lawrence Livermore National Laboratory to realize groundbreaking predictions from simulations. He is also a team leader of SNAP-MD team, which has been selected as 2021 Gordon Bell Prize finalist for record breaking billion atom simulations of carbon at extreme conditions and experimental time and length scales.

Dr. Oleynik received his PhD in Chemical Physics from Russian Academy of Sciences, was the Royal Society research fellow at the University of Bath and senior research scientist at the University of Oxford before joining Physics faculty at USF. He is a Fellow of American Association for Advancement of Science, American Physical Society (APS), and American Vacuum Society. He is a past chair of the APS Topical Group on Shock Compression of Condensed Matter, a unit of APS aimed at promoting the science of matter at extreme conditions.