| NSF Org: |
CHE Division Of Chemistry |
| Recipient: |
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| Initial Amendment Date: | August 5, 2020 |
| Latest Amendment Date: | August 5, 2020 |
| Award Number: | 1951328 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Ryan Jorn
rjorn@nsf.gov (703)292-4514 CHE Division Of Chemistry MPS Directorate for Mathematical and Physical Sciences |
| Start Date: | August 15, 2020 |
| End Date: | July 31, 2024 (Estimated) |
| Total Intended Award Amount: | $480,000.00 |
| Total Awarded Amount to Date: | $480,000.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
1 UNIVERSITY OF NEW MEXICO ALBUQUERQUE NM US 87131-0001 (505)277-4186 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
Albuquerque NM US 87131-0001 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | Chem Thry, Mdls & Cmptnl Mthds |
| Primary Program Source: |
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| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.049 |
ABSTRACT
Dr. Hua Guo of University of New Mexico is supported by an award from the Chemical Theory, Models and Computational Methods program in the Division of Chemistry to study elementary steps in chemistry at gas-metal interfaces, such as adsorption, desorption, scattering, trapping and diffusion, energy transfer, and reactions, using state-of-the-art computational models. Despite a large number of chemical processes, such as corrosion and heterogeneous catalysis, occurring at the interfaces between difference phases, our understanding of these reactive processes is still quite limited, due to complexity of the interaction and dynamics. The knowledge gained from such fundamental studies can help to design predictive models of interfacial phenomena, thus allowing more efficient use of energy and materials and the ultimate control of chemical reactions.
Specifically, Dr. Guo plans to develop and apply novel theoretical and computational models to understand some key issues in surface dynamics, such as the relative efficacy of different energies in the impinging molecule, dependence of reactivity on surface sites, and role of metal electron-hole pairs. He focuses on the accurate determination of high-dimensional Born-Oppenheimer potential energy surfaces for the interaction of gas phase species with metal surfaces, as well as other properties such as friction tensors, using machine learning tools. These high-dimensional properties enable dynamical investigations of these surface processes with high efficiency and accuracy. He will pay particular attention to dissipative channels due to phonons and electron-hole pairs of the metal surfaces on how they affect energy flow and bond forming/breaking events. Building on strong collaborations with leading experimental groups around the world, his theoretical studies will help to advance a systematic and comprehensive understanding of surface reaction dynamics by establishing and testing key principles and theories for interfacial chemistry.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
With the support of this NSF grant, Dr. H. Guo and his team have been investigating dynamics of various surface processes, such as scattering, adsorption/desorption, diffusion, and reactions, using computational methods. These elementary processes play important roles in many physical and chemical processes such as corrosion, materials fabrication, heterogeneous catalysis. In collaboration with experimentalists around the world, the theoretical studies by Guo and his coworkers advanced insightful understanding of experimental observations. Such synergistic collaborations allowed testing of new principles and models, which eventually lead to a deeper understanding of chemical and physical processes at the gas-surface interface. Such knowledge helps the establishment of predictive models for surface science.
During the funding period, Dr. Guo and his colleagues investigated several key issues in surface science. One such issue is the influence of dissipation on surface processes. Important energy loss channels include the adiabatic coupling of adsorbed species with surface phonons, and the nonadiabatic coupling with surface electron-hole pairs. These effects, which are absent in the gas phase, can have a significant impact on the outcome of a surface process. Another issue is the possible impact of quantum effects on reaction rates of surface processes. These quantum effects include tunneling and zero-point energy, and they cannot be easily included in classical dynamics. Novel theories including such quantum effects are needed to understand their roles in chemical transformation. Finally, we have leveraged machine learning in our theoretical modeling of surface processes. Training models that are capable of handling long time and rare events in surface processes allowed us to examine many new phenomena that is off limit to conventional dynamical methods.
Advances like this are expected to advance our fundamental knowledge of complex chemical systems and help to establish predictive models for catalysis.
Last Modified: 01/07/2025
Modified by: Hua Guo
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