New Quantum Mechanics Based Methods for Multiscale Simulations with Applications to Reaction Mechanisms for Electrocatalysis
Abstract
Electrocatalysis may provide the solution to some of the most important energy and environmental problems facing society: converting solar energy during the day to fuel (H₂) that can provide power at night (hydrogen fuel cells) through water splitting, ·reducing the CO₂ in the atmosphere to valuable chemicals (methane, ethylene, ethanol). However significant improvements must be made in the selectivity and activity of current electrocatalysts to obtain practical solutions. A great many experiments are underway to find such solutions, but the progress is slow. We consider that quantum mechanics based multiscale simulations can dramatically accelerate the progress by identifying the reaction mechanisms involved and the using in silico methods to predict the best modifications to Improve performance. We will discuss some of the progress in developing the methods needed and applying them to improving electrocatalysts.
Additional Information
© 2020 Springer. Published: 28 September 2020. The research on CO₂ reduction was supported as part of the Joint Center for Artificial Photosynthesis, an Energy Innovation Hub funded by the U.S. Department of Energy, Office of Science. (DE-SC0004993). The research on ORR is funded by ONR (N00014-18-1-2155). The research on OER is funded by NSF (CBET-1805022). There is no direct funding for RexPoN, but it is supported by these other projects. Dedication: To Robert Grasselli, pioneer in improving catalysis and catalysts through atomistic reasoning and mechanism. Inspiration for the Irsee Catalysis meetings and for my entry into the wonderful complex world of Heterogeneous catalysis. We declare no Conflicts of Interest.Attached Files
Accepted Version - 1397-Goddard-IRSEE-VIII-Electrochem-20-01-11-modified-20-08-28-final.pdf
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Additional details
- Eprint ID
- 105630
- Resolver ID
- CaltechAUTHORS:20200929-101500549
- Department of Energy (DOE)
- DE-SC0004993
- Office of Naval Research (ONR)
- N00014-18-1-2155
- NSF
- CBET-1805022
- Created
-
2020-09-29Created from EPrint's datestamp field
- Updated
-
2021-11-16Created from EPrint's last_modified field
- Caltech groups
- JCAP
- Other Numbering System Name
- WAG
- Other Numbering System Identifier
- 1397