Insertion of MXene‐Based Materials into Cu–Pd 3D Aerogels for Electroreduction of CO<sub>2</sub> to Formate
Bibliographic record
Abstract
Abstract The electrochemical CO 2 reduction reaction (CO 2 RR) is an attractive method to produce renewable fuel and chemical feedstock using clean energy sources. Formate production represents one of the most economical target products from CO 2 RR but is primarily produced using post‐transition metal catalysts that require comparatively high overpotentials. Here a composition of bimetallic Cu–Pd is formulated on 2D Ti 3 C 2 T x (MXene) nanosheets that are lyophilized into a highly porous 3D aerogel, resulting in formate production much more efficient than post‐transition metals. Using a membrane electrode assembly (MEA), formate selectivities >90% are achieved with a current density of 150 mA cm −2 resulting in the highest ever reported overall energy efficiency of 47% (cell potentials of −2.8 V), over 5 h of operation. A comparable Cu‐Pd aerogel achieves near‐unity CO production without the MXene templating. This simple strategy represents an important step toward the experimental demonstration of 3D‐MXenes‐based electrocatalysts for CO 2 RR application and opens a new platform for the fabrication of macroscale aerogel MXene‐based electrocatalysts.
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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) | 0.000 | 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 | 0.000 |
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 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".