Contact Information
Biography
Dr. Jingyun Ye is currently an Assistant Professor in the Department of Chemistry
& Biochemistry at Duquesne University. She received her B.S and Ph. D. degree in Chemical
Engineering at Tianjin University, where her graduate research focused on theoretical
and experimental study In2O3 for CO2 hydrogenation to methanol. She started as a postdoctoral
research associate with Prof. Karl Johnson at University of Pittsburgh in 2014 and
her research focused on computational design and screening of stratified functional
nanoporous materials for CO2 capture and conversion. In 2016, she transferred to University
of Minnesota and worked with Prof. Donald G. Truhlar, Prof. Laura Gagliardi and Prof.
Christopher J. Cramer. Her research at University of Minnesota focuses on computational
study of the structure and reaction mechanism of the single site-metal supported on
metal organic frameworks for energy related catalytic reactions, such as ethylene
oligomerization, methane to methanol, alkyne to alkene. Her research have been reported
by multiple medias, including C&EN, Science Daily, Eurekalert |AAAS News, Phys.org, NextPittsburgh News.
Education
- Postdoc, Chemistry, University of Minnesota
- Postdoc, Chemical Engineering, University of Pittsburgh
- Ph.D., Chemical Engineering, Tianjin University
- B.S., Chemical Engineering, Tianjin University
Research Interests or Expertise
- Using state-of-the-art quantum chemistry calculations and kinetic modeling to investigate the catalyst structures, reaction mechanisms, thermodynamics and kinetics of catalytic reactions at the molecular level.
- Exploring structure-function relationships to identify the physical and chemical descriptors that govern catalytic activity for large-scale computational screening, and further guide catalysts design.
- Constructing open-access DFT database and combine with big data and machine learning for the novel materials discovery.
- Developing new computational methods and models for catalysis.
Our group works on a wide range of materials including metal, metal oxides, metal
complexes, zeolites, metal organic frameworks, as well as other hybrid materials for
heterogeneous and homogeneous catalysis. The ultimate goal is to use computational
modeling to study, predict and design multi-functional materials for the applications
relating to energy and environment, such as CO2 capture and conversion, natural gas
conversion, polymerization and
green energy generation.
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