Catalyst-Proximal Plastrons for Enhancing Electrocatalytic Reduction of CO<sub>2</sub> on Copper in Aqueous-Phase Systems
Bibliographic record
Abstract
Electrocatalytic reduction of CO2 (CO2RR) is an attractive method of converting CO2 to solar fuels. Much research in this field has been focused on developing novel catalysts to enhance the activity and product distribution (selectivity). Copper has been studied widely as it can produce both one carbon (C1) products such as methane and formate, and products with two or more carbons (C2+) such as ethylene, ethanol, and n-propanol1. Copper is not immune from the competing hydrogen evolution reaction: the poor solubility of CO2 in water (~34 mM at ambient conditions) limits the CO2RR current density, and hydrogen generation is favored if the aqueous CO2 concentration becomes locally undersaturated close to the catalyst during CO2RR2. This limitation is even more pronounced for nanotextured copper, because the increased active surface area leads to faster depletion of local CO2 thereby promoting hydrogen evolution over CO2RR. Hence, overcoming these CO2 availability limitations can enable higher CO2RR activity while reducing co-evolution of hydrogen. In this work, we develop a gasphilic CO2 trap that increases gas-liquid mass transfer and maintains supersaturated CO2 concentration around the catalyst during CO2RR. Gasphilic surfaces need a special combination of surface chemistry and texture to capture bubbles and form a sheet of gas underwater which is called a plastron3. By creating pyramidal textures, CO2 bubbles are efficiently captured within the textures and form a CO2 plastron. When this plastron is placed proximal to both smooth and nanostructured copper catalysts during CO2RR, the current density is enhanced and maintained throughout the reaction, when compared to two commonly used methods of CO2 delivery: headspace and bubbling in the bulk electrolyte. The plastron allows for quick replenishment of CO2 during the CO2RR reaction in the vicinity of the catalyst. As a result, the H2 Faradaic efficiency is reduced from 33% to 13% on smooth copper, and from 62% to 33% on nanostructured copper. This is accompanied by an increased production of C2+ products including ethylene, ethanol and propanol, as well as acetone and acetate at Faradaic efficiencies exceeding 1%. We highlight the importance of this catalyst-proximal plastron approach by comparing against recent aqueous-phase CO2RR studies, and discuss how this approach can inform optimal design of continuous CO2RR systems such as gas-diffusion electrodes. [1] Nitopi, S., Bertheussen, E., Scott, S. B., Liu, X., Engstfeld, A. K., Horch, S., Seger, B., Stephens, I. E. L., Chan, K., Hahn, C., Nørskov, J. K., Jaramillo, T. F. & Chorkendorff, I. Progress and Perspectives of Electrochemical CO2 Reduction on Copper in Aqueous Electrolyte. Chem. Rev. 119, 7610–7672 (2019). [2] Lobaccaro, P., R. Singh, M., Lee Clark, E., Kwon, Y., T. Bell, A. & W. Ager, J. Effects of temperature and gas–liquid mass transfer on the operation of small electrochemical cells for the quantitative evaluation of CO2 reduction electrocatalysts. Physical Chemistry Chemical Physics 18, 26777–26785 (2016). [3] Panchanathan, D., Rajappan, A., Varanasi, K. K. & McKinley, G. H. Plastron Regeneration on Submerged Superhydrophobic Surfaces Using In Situ Gas Generation by Chemical Reaction. ACS Appl. Mater. Interfaces 10, 33684–33692 (2018).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".