Proton-donating cations enable efficient and stable acidic CO2 reduction in membrane electrode assemblies
Why this work is in the frame
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Bibliographic record
Abstract
ABSTRACT Electrochemical CO2 reduction (CO2R) in acidic membrane electrode assemblies (MEAs) represents a promising pathway for sustainable chemical production, but achieving high selectivity, low cell voltage and long-term stability remains challenging. Current approaches using alkali cations can promote selectivity through cationic effects, but relying on H2O as a weak proton donor results in high overpotential and severe precipitation, causing elevated cell voltage and poor operational stability. Here, we introduce NH4+ as a proton-donating cation that simultaneously addresses these challenges in acidic MEAs. As a cation, it electromigrates to the catalyst surface, stabilizing *CO2 intermediates and reducing localized H+ concentration for high selectivity. As a proton donor, it provides superior proton-donating ability compared to H2O when H+ mass transport is limited, which decreases the protonation barrier and reduces CO2R overpotential on CoPc@CNT, resulting in a lower cell voltage. Furthermore, NH4+ effectively donates protons to bicarbonate, promoting its decomposition at significantly lower temperatures compared to KHCO3, thereby enabling easy removal of precipitates through mild heating and maintaining an NH3/NH4+ recirculation system for operational stability. As a result, this approach achieves an average CO2-to-CO selectivity of 86% in acidic MEAs at 100 mA cm−2 and 60°C using CoPc@CNT–NH2 catalyst, with stable performance over 110 h at an average cell voltage of 2.84 V, corresponding to a 40.6% energy efficiency. This strategy advances acidic MEA-based CO2R toward practical implementation by simultaneously achieving high selectivity, low overpotential and stable operation.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| 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) | 0.000 | 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 it