Performance Characteristics of Polymer Electrolyte Membrane CO<sub>2</sub> Electrolyzer: Effect of CO<sub>2</sub> Dilution, Flow Rate and Pressure
Bibliographic record
Abstract
CO 2 electrolyzer designed to operate on dilute CO 2 feed and low stoichiometric ratio would alleviate the separation costs for CO 2 purification and electrolyzer exit gas processing, respectively. The effect of CO 2 concentration, CO 2 flow rate, and CO 2 pressure on current density and faradaic efficiency of a solid polymer electrolyte membrane CO 2 electrolyzer was quantified. An approach for estimating voltage breakdown into activation overpotential for CO 2 reduction reaction as well as oxygen evolution reaction, ohmic losses, and concentration overpotential is introduced. No enhancement in current density (∼160 mA cm −2 ) was observed above stoichiometry ratio of 4 whereas reducing the stoichiometric ratio to 2.7 still yielded a current density of ∼100 mA cm −2 . Dilution of CO 2 in the feed from 100 mol% to 30 mol%, at ∼90kPa of cell pressure, resulted in a monotonically decreasing current density. A square root dependency on CO2 partial pressure was observed under these conditions. Operation with pure CO 2 at different total pressure yielded only a minor increase in current density indicating some form of saturation-limited behavior. Long-term potentiostatic operation over 85 h revealed continuous drop in current density and a corresponding increase in electrode resistance, observed in electrochemical impedance response.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".