Vertically Aligned Multiwalled Carbon Nanotube/Cu Catalysts for CO<sub>2</sub> Electroreduction
Bibliographic record
Abstract
Enhancing the selectivity of hydrocarbon products remains a key challenge to achieving artificial energy sustainability via closing the carbon cycle. While copper-based electrodes uniquely yield hydrocarbon products, the improvement of their product selectivity through physical morphology regulation shows great potential and requires further investigation. Here, we show the distinct morphological influences of the Cu electrode on the reaction selectivity. We synthesize binder-free, vertically aligned, nanoid forest-like copper electrocatalysts for superior improved methane conversion selectivity with respect to planar Cu. These Cu nanocomposites are fabricated through the conformal coating of vertically aligned multiwalled carbon nanotube array electrodes, which have matured to a cost-effective and scalable technology over the past two decades. Simulations reveal that carbon intermediates and protons can be confined in the gaps of the nanoid copper forest, which are formed in situ and in turn cover the catalytic sites and facilitate the simultaneous transfer of coupled electrons and protons. Such forest-like antenna morphology benefits from a threefold improvement of the CO2 electroreduction performance through a decreased reaction onset potential, an increased current density, and enhanced hydrocarbon selectivity.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 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".