SLAC National Accelerator Laboratory
Showing 11-20 of 88 Results
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Hao Chen
Postdoctoral Scholar, Photon Science, SLAC
Bio“Understanding interfacial phenomena for solar H2 production and N2 reduction”
Postdoctoral Researcher 2022.11 – present
•Stanford University, CA 94305
(Supervisor: Prof. Amy Cordones-Hahn & Kelly Gaffney)
“Catalysis Program”
Postdoctoral Researcher 2020.1 – 2022.10
•Lawrence Berkeley National Laboratory, Berkeley, CA
(Supervisor: Prof. Miquel Salmeron)
Joint Ph.D. in Physical Chemistry 2013-2019
*2013-2018: Dalian Institute of Chemical Physics, Chinese Academy of Sciences, China (Supervisor: Prof. Xinhe Bao)
*2018-2019: Institute for Applied Physics, Vienna University, of Technology, Austria (Supervisor: Prof. Ulrike Diebold)
B.S. in Chemistry, Zhengzhou University, China 2009-2013 -
Zhihengyu Chen
Postdoctoral Scholar, Photon Science, SLAC
BioPh. D. in Chemistry, Stony Brook University, 2018-2023
B. Eng. in Chemical Engineering, Tianjin University, 2014-2018
B. S. in Chemistry, Nankai University, 2014-2018 -
Igor Daniel de Araujo Evangelista
Postdoctoral Scholar, Photon Science, SLAC
BioDr. Evangelista's primary research focus lies in computational modeling and theoretical analysis of semiconductor materials using advanced quantum mechanical methods, including Density Functional Theory, Quantum Monte Carlo, and ab-initio Molecular Dynamics. Evangelista investigates the electronic, structural, and mechanical properties of materials, collaborating closely with experimental groups to bridge theoretical predictions with empirical results. He is also interested in the development of empirical potentials and enhancing materials modeling through the application of machine learning techniques.
Evangelista entered the Department of Materials Science and Engineering at the University of Delaware as a Ph.D. candidate in 2018, after completing an master degree in Physics 2016-2018 at Federal Fluminense University (Brazil). Recent work includes collaborations with experimental groups to bridge theoretical predictions with empirical results, as well as applying machine learning to creating of empirical potentials to accelerate materials modeling. Evangelista has also contributed to understanding electron mobility in metal-oxide semiconductors and strain effects in two-dimensional materials. These studies showcase his expertise in electronic structure and materials design for next-generation semiconductor technologies.
