Department of Chemistry - Seminar - First Principles and Machine Learning Studies of Water and Carbon in a Large Pressure-temperature Range

11:00am - 12:30pm
Room 4504, 4/F, Lift 25/26, Academic Building, HKUST

Speaker: Professor Ding PAN

Institution: Department of Physics and Department of Chemistry, The Hong Kong University of Science and Technology

Hosted By: Professor Haipeng LU

 

Abstract

In this talk, we will introduce a series of interesting aqueous carbon reactions studied by first principles (ab initio) molecular dynamics simulations in our group, including formation of carbon acid, formate, and hydrocarbons.
We will show our recent method development to calculate solvation properties using first principles and machine learning.
To keep a strong connection with experiments, we will discuss how to measure water and carbon using spectroscopic methods such as infrared absorption, Raman scattering, and sum frequency generation.
Our studies have great implications for deep carbon cycle, abiogenic petroleum origin, and even the origin of life.

 

About the speaker

Prof Ding Pan obtained BS in physics in the 00 Class (SCGY) at University of Science and Technology of China in 2005, and ScD at Institute of Physics, Chinese Academy of Sciences in 2011.  During the ScD study, he was a visiting researcher at the Fritz-Haber-Institute of the Max Planck Society in Berlin, Germany and a Thomas Young Centre Junior Research Fellow at the University College London, UK. After he worked as a postdoctoral researcher in the Department of Chemistry at the University of California at Davis (2011-2014) and the Pritzker School of Molecular Engineering at the University of Chicago (2014-2016), he joined HKUST in 2016.  His achievements have been recognized by multiple awards from international scientific organizations, including Croucher Innovation Award in 2018, Deep Carbon Observatory Emerging Leader Award in 2019, Excellent Young Scientists Award in 2020 (Hong Kong and Macau, Natural Science Foundation of China), and HKUST School of Science Research Award in 2022.

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