Observations of Mass Transport Losses in Two-Phase CO<sub>2 </sub>electroreduction
Bibliographic record
Abstract
The need for capturing CO2 has become urgent with a record-breaking concentration of CO2 in our atmosphere (average of 407.4 ppm in 2018 [1]). CO2 electrolyzers are a promising technology capable of achieving a net-negative CO2 cycle when coupled with renewable energy sources. Aqueous electrolyte-based alkaline CO2 electrolyzers have recently been demonstrated to exhibit high selectivity for CO2 reduction to CO [2]. While the selectivity and enhanced performance of the aqueous alkaline environment are desired, the mass transport limitations introduced with this design have largely been overlooked. In this study, we investigated the transport mechanisms near the electrolyte-catalyst interface over a range of current densities via sub-second in-operando X-ray synchrotron radiography. For the first time, we report fluctuations in cell overpotential driven by the dynamic accumulation and removal of gas at the electrolyte-catalyst interface region. Moreover, this fluctuation in potential due to the gas accumulation and removal in the liquid electrolyte layer was also observed to occur at a periodic rate that became increasingly frequent with increasing current density. The transient gas behavior observed from this study must be accounted for to further enhance the performance of alkaline CO2 electrolyzers with a liquid electrolyte. References: [1] Lindsey, R. “Climate Change: Atmospheric Carbon Dioxide”, NOAA Climate.gov, 2019. [2] A. Martín, G. Larrazábal and J. Pérez-Ramírez, "Towards sustainable fuels and chemicals through the electrochemical reduction of CO2: lessons from water electrolysis", Green Chemistry, vol. 17, no. 12, pp. 5114-5130, 2015.
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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 | 0.001 |
| 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".