Electrochemical CO2 reduction: Predicting the selectivity
Bibliographic record
Abstract
No abstract is available for this record. The assistant can identify its topic from the title, but cannot infer the study’s results.
Source: Not provided · Quality: missing
Research context
OpenAlex topics: CO2 Reduction Techniques and Catalysts · Advanced Thermoelectric Materials and Devices · Ionic liquids properties and applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (41)
Show source-provided references
1. Catalysts and reaction pathways for the electrochemical reduction of carbon dioxide10.1021/acs.jpclett.5b01559 ↗
2. Hori · 1994
3. New insights into the electrochemical reduction of carbon dioxide on metallic copper surfaces10.1039/c2ee21234j ↗
4. An in situ surface-enhanced infrared absorption spectroscopy study of electrochemical CO2 reduction: selectivity dependence on surface C-bound and O-bound reaction intermediates10.1021/acs.jpcc.8b09598 ↗
5. In situ spectroscopic study of CO2 electroreduction at copper electrodes in acetonitrile10.1021/acscatal.5b02543 ↗
6. Probing the dynamics of low-overpotential CO2-to-CO activation on copper electrodes with time-resolved Raman spectroscopy10.1021/jacs.2c03172 ↗
7. Theoretical considerations on the electroreduction of CO to C 2 species on Cu(100) electrodes10.1002/ange.201301470 ↗
8. Absence of CO2 electroreduction on copper, gold and silver electrodes without metal cations in solution10.1038/s41929-021-00655-5 ↗
9. A unifying mechanism for cation effect modulating C1 and C2 productions from CO2 electroreduction10.1038/s41467-022-33199-8 ↗
10. Cation-induced changes in the inner- and outer-sphere mechanisms of electrocatalytic CO2 reduction10.1038/s41467-023-43300-4 ↗
11. Acetaldehyde as an intermediate in the electroreduction of carbon monoxide to ethanol on oxide-derived copper10.1002/anie.201508851 ↗
12. Key intermediates and Cu active sites for CO2 electroreduction to ethylene and ethanol10.1038/s41560-024-01633-4 ↗
13. The mechanism for acetate formation in electrochemical CO(2) reduction on Cu: selectivity with potential, pH, and nanostructuring10.1039/D2EE01485H ↗
14. Formation of carbon–nitrogen bonds in carbon monoxide electrolysis10.1038/s41557-019-0312-z ↗
15. Accessing organonitrogen compounds via C-N coupling in electrocatalytic CO2Reduction10.1021/jacs.1c10714 ↗
16. Mechanistic insights into electroreductive C-C coupling between CO and acetaldehyde into multicarbon products10.1021/jacs.9b11817 ↗
17. Exploring trends on coupling mechanisms toward C3 product formation in CO(2)R10.1021/acs.jpcc.1c07553 ↗
18. Nitopi · 2019
19. Pathways to enhance electrochemical CO2 reduction identified through direct pore-level modeling10.1039/D3EY00122A ↗
20. Rational design of local reaction environment for electrocatalytic conversion of CO2 into multicarbon products
21. In operando investigations of oscillatory water and carbonate effects in MEA-based CO2 electrolysis devices10.1016/j.joule.2023.01.013 ↗
22. Long-chain hydrocarbons by CO2 electroreduction using polarized nickel catalysts10.1038/s41929-022-00803-5 ↗
23. CO2 electroreduction to long-chain hydrocarbons on cobalt catalysts
24. Activity descriptors for CO2 electroreduction to methane on transition-metal catalysts10.1021/jz201461p ↗
25. Calculations of product selectivity in electrochemical CO2 reduction10.1021/acscatal.7b03308 ↗
26. From electricity to fuels: descriptors for C1 selectivity in electrochemical CO2 reduction10.1016/j.apcatb.2020.119384 ↗
27. Trends in oxygenate/hydrocarbon selectivity for electrochemical CO(2) reduction to C2 products10.1038/s41467-022-29140-8 ↗
28. Electrochemical CO2 reduction: a classification problem10.1002/cphc.201700736 ↗
29. Single site porphyrine-like structures advantages over metals for selective electrochemical CO2 reduction10.1016/j.cattod.2017.02.028 ↗
30. Electrochemical CO2 reduction: classifying Cu facets10.1021/acscatal.9b01899 ↗
31. Fast evaluation of the adsorption energy of organic molecules on metals via graph neural networks10.1038/s43588-023-00437-y ↗
32. Efficient catalyst screening using graph neural networks to predict strain effects on adsorption energy10.1126/sciadv.abq5944 ↗
33. Accelerated discovery of CO2 electrocatalysts using active machine learning10.1038/s41586-020-2242-8 ↗
34. Interpretable machine learning models for practical antimonate electrocatalyst performance10.1002/cphc.202400010 ↗
35. Systematic data-driven modeling of bimetallic catalyst performance for the hydrogenation of 5-ethoxymethylfurfural with variable selection and regularization10.1021/acs.iecr.1c03995 ↗
36. Complex-solid-Solution electrocatalyst discovery by computational prediction and high-throughput experimentation10.1002/anie.202014374 ↗
37. Predicting the performance of oxidation catalysts using descriptor models10.1039/C5CY00932D ↗
38. Electrochemical reduction of carbon dioxide at various series of copper single crystal electrodes10.1016/S1381-1169(03)00016-5 ↗
39. Data-driven discovery of electrocatalysts for CO2 reduction using active motifs-based machine learning10.1038/s41467-023-43118-0 ↗
40. Abed · 2024
41. Combining first-principles kinetics and experimental data to establish guidelines for product selectivity in electrochemical CO2 reduction10.1021/acscatal.3c00228 ↗