Boosting Electrochemical Conversion of CO<sub>2</sub> to CO in a Membrane Electrode Assembly Using Nickel–Nitrogen/Carbon Supported Nickel–Zinc Carbide Particle Catalyst
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide The development of efficient catalysts for CO 2 electroreduction to value added products is required to enable electrochemical CO 2 conversion technologies that will help mitigate emissions and the devastating climate change related impacts. Atomically dispersed nickel–nitrogen–carbon (Ni–N–C) catalysts are a promising alternative to precious metal (Au and Ag) catalysts for converting CO 2 to CO. However, in CO 2 electrolyzers, the performance of Ni–N–C catalysts is still lower than that of precious metal catalysts, likely due to the low concentration of catalytically active Ni–Nx/C sites that requires high catalyst loadings that lead to CO 2 mass transport limitations. Herein, a new catalyst design is developed based on a structure that comprises Ni–Nx/C active sites along with highly dense nickel zinc carbide (Ni 3 ZnC) particles─that selectively convert CO 2 into CO. In a membrane electrode assembly (MEA) based CO 2 electrolyzer, the developed catalyst demonstrated a current density of 448 mA/cm 2 and a CO 2 to CO Faradaic efficiency of >95% at 3.1 V. This promising MEA performance opens up the opportunity towards the employment of non-precious cathode materials in CO 2 electrolyzers as a competitive alternative to precious metals.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".