Stabilizing Copper for CO<sub>2</sub> Reduction in Low-Grade Electrolyte
Bibliographic record
Abstract
We demonstrate herein a CO 2 reduction electrocatalyst regeneration strategy based on the manipulation of the Cu(0)/Cu 2+ equilibrium with high concentrations of ethylenediaminetetraacetic acid (EDTA). This strategy enables the sustained performance of copper catalysts in distilled and tap water electrolytes for over 12 h. The deposition of common electrolyte impurities such as iron, nickel, and zinc is blocked because EDTA can effectively bind the metal ions and negatively shift the electrode potential of M/M n + . The Cu/Cu 2+ redox couple is >600 mV more positive than the other metal ions and therefore participates in an equilibrium of dissolution and redeposition from and to the electrode in high concentrations of EDTA. These dynamic equilibria serve to further regenerate the surface copper catalyst to prevent the deactivation of catalytic sites. On the basis of this strategy, we show that >95% of initial hydrocarbon production activity can be maintained for 12 h in KHCO 3 (99% purity) enriched distilled water and 6 h in KHCO 3 (99% purity) enriched tap water.
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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) | 0.001 | 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 | 0.001 |
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".