Graduate student Zisheng Zhang (Alexandrova group) receives competitive Chemical Computing Group, Inc. (CCG) Excellence Award in recognition of his outstanding graduate research, character and service within the community.
In addition to recognizing talented graduate students, the CCG Excellence Awards were created to stimulate graduate student participation in ACS Computers In Chemistry (COMP) Division activities (symposia and poster sessions) at ACS National Meetings. Those eligible for a CCG Excellence Award are graduate students in good standing who present work within the COMP program. Winners receive $1,150 to offset their travel expenses to attend the ACS National Meeting, as well as a copy of CCG’s Molecular Operating Environment (MOE) software with a one-year license. They are also honored during a ceremony at the meeting, which will take place March 26-30, 2023, in Indianapolis, IN.
The award is given out twice a year, with five graduate students each time being part of the winning group. For the Spring 2023 meeting, there were a good number of applicants, with very competitive submissions over a diverse range of research topics. All eligible applications were reviewed by three independent judges who are experts in computational chemistry.
Zhang is a fourth-year theoretical & computational chemistry Ph.D. student in Professor Anastassia Alexandrova’s group. As an undergraduate at the Southern University of Science and Technology (SUSTech) in China, he was the first chemistry student to visit UCLA as part of the Cross-Disciplinary Scholars in Science and Technology (CSST) program where he conducted summer research in Alexandrova’s group for ten weeks in 2018. In 2020, Zhang was awarded a prestigious 2019-20/2022-23 Edwin W. Pauley Fellowship Pauley Fellowship by the UCLA College of Letters and Sciences, Division of Physical Sciences, and in 2022, he received the department’s Jim and Barbara Tsay Excellence in 2nd Year Research and Academics Award.
Zhang’s research focus is on the theory of heterogeneous thermal and electrocatalysis on interfaces that tend to restructure in reaction conditions. A paradigm shift is required to understand these systems, as they present highly active metastable sites, but only in the reaction conditions, which are often not accessible in traditional simulations. Sometimes these sites are numerous and coexisting, and then reaction mechanisms and rates emerge from the full ensemble of catalyst states with different geometry and stoichiometry. These open up new dimensions for catalyst design but also make the picture highly complex. To address such a sheer complexity, Zhang develops innovative theory, efficient structure search algorithms, dynamics simulation considering realistic aspects, and he works closely with experimental collaborators to characterize and understand the dynamic catalytic interfaces. He is also interested in multi-objective inverse design of functional molecules, automated high throughput computational workflow, and data-driven methods to accelerate chemical discovery.
Penny Jennings, UCLA Department of Chemistry & Biochemistry, email@example.com.