Toward Improving the Selectivity of Organic Halide Electrocarboxylation with Mechanistically Informed Solvent Selection
Abstract
The use of a liquid electrolyte is nearly ubiquitous in electrosynthetic systems and can have a significant impact on the selectivity and efficiency of electrochemical reactions. Solvent selection is thus a key step during optimization, yet this selection process usually involves trial-and-error. As a step toward more rational solvent selection, this work examines how the electrolyte solvent impacts the selectivity of electrocarboxylation of organic halides. For the carboxylation of a model alkyl bromide, hydrogenolysis is the primary side reaction. Isotope-labeling studies indicate the hydrogen atom in the hydrogenolysis product comes solely from the aprotic electrolyte solvent. Further mechanistic studies reveal that under synthetically relevant electrocarboxylation conditions, the hydrogenolysis product is formed via deprotonation of the solvent. Guided by these mechanistic findings, a simple computational descriptor based on the free energy to deprotonate a solvent molecule was shown to correlate strongly with carboxylation selectivity, overcoming limitations of traditional solvent descriptors such as pKₐ. Through careful mechanistic analysis surrounding the role of the solvent, this work furthers the development of selective electrocarboxylation systems and more broadly highlights the benefits of such analysis to electrosynthetic reactions.
Additional Information
© 2023 The Authors. Published by American Chemical Society. Attribution 4.0 International (CC BY 4.0) This work was supported by the National Science Foundation under Grant 1955628. N.C. gratefully acknowledges graduate research fellowships from the National Science Foundation under Grant 1745302. We are thankful for the help of MIT's Department of Chemistry Instrumentation Facility in acquiring NMR spectra. We thank Gang Wang and Ariel Furst at MIT for their help with column chromatography. We also thank Yunsie Chung at MIT for advice with running DFT calculations. This work used the Extreme Science and Engineering Discovery Environment (XSEDE) Expanse cluster at the SDSC through allocation CHE200049, which is supported by National Science Foundation Grant ACI-1548562. The authors declare no competing financial interest.Attached Files
Published - jacs.2c10561.pdf
Supplemental Material - ja2c10561_si_001.pdf
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Additional details
- Eprint ID
- 119184
- Resolver ID
- CaltechAUTHORS:20230209-988069100.22
- CHE-1955628
- NSF
- DGE-1745302
- NSF Graduate Research Fellowship
- ACI-1548562
- NSF
- Created
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2023-03-17Created from EPrint's datestamp field
- Updated
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2023-03-17Created from EPrint's last_modified field