Our first funded project from this network is:
Project title: ''Charge carrier transportation in perovskite materials: an ultrafast x-ray absorption spectroscopic study''.
Researcher: Van Thai Pham (Sweden), Minh Tuan Trinh (USA) and Viet Mui Luong (Japan)
Amount: 100 000 SEK (10 000 euro) for equipments
Funder: The Walter Gyllenberg Foundation, Sweden
Dr. Huy Pham
The knowledge sharing seminar by
Dr. Huy Pham
Staff Scientist at Lawrence Livermore National Laboratory (LLNL), USA
You are most welcome to our knowledge sharing seminar this month presented by Dr. Huy Pham. This young and energetic researcher experienced various academic environments from Asian, Europe to US is expected to open new collaborative opportunities between experimentalists and theorists in our research Network.
Title: Machine Learned Interatomic Potentials for the Calculation of Material Properties with Quantum Accuracy
Abstract: Computer simulations such as molecular dynamics (MD) are powerful tools to provide molecular-level details of many physical and chemical processes that can greatly facilitate experimental design and interpretation. Quantum mechanical-based molecular dynamics has been widely used to achieve a high degree of accuracy for diverse systems. However, these simulations are typically limited in size to less than 1000 atoms and in time to less than 100 ps, while many experimental phenomena can occur over length- and time- scales which are orders of magnitude larger and longer. In this talk, I will present two different types of models in development in our research group to overcome the problem: (1) force fields for molecular dynamics simulations, (2) semi-empirical quantum simulation approaches. In general, our approaches allow for quantum accuracy simulations at much lower computational cost. I will also show some examples where computer simulations play a critical role in understanding experimental observations.
Huy Pham is a Staff Scientist at Lawrence Livermore National Laboratory (LLNL). His research interests include the development/application of quantum mechanical methods/machine learning based potentials to predict materials properties (ambient, extreme conditions and material under shock compression). He joint LLNL in 2018 as a Postdoctoral Researcher and was promoted to Staff Scientist in 2021. Before joining LLNL, he was a Postdoctoral Researcher in the Department of Chemistry and Biochemistry at University of California, San Diego from 2015 to 2018. He received a Ph.D. in Theory and Numerical Simulation of Condensed Matter Physics from the International School for Advanced Studies (SISSA), Trieste, Italy in 2015.
Time: 21:00 - 23:00 in Vietnam, Wednesday, June 22th 2022
Zoom link: https://lu-se.zoom.us/j/62107042752
Chairman: Asst. Prof. Kim Cuong Le