Synthesis of 3D Porous Cu Nanostructures on Ag Thin Film Using Dynamic Hydrogen Bubble Template for Electrochemical Conversion of CO2 to Ethanol
Bibliographic record
Abstract
Cu-based nanomaterials have been widely considered to be promising electrocatalysts for the direct conversion of CO2 to high-value hydrocarbons. However, poor selectivity and slow kinetics have hindered the use of Cu-based catalysts for large-scale industrial applications. In this work, we report on a tunable Cu-based synthesis strategy using a dynamic hydrogen bubble template (DHBT) coupled with a sputtered Ag thin film for the electrochemical reduction of CO2 to ethanol. Remarkably, the introduction of Ag into the base of the three-dimensional (3D) Cu nanostructure induced changes in the CO2 reduction reaction (CO2RR) pathway, which resulted in the generation of ethanol with high Faradaic Efficiency (FE). This observation was further investigated through Tafel and electrochemical impedance spectroscopic analyses. The rational design of the electrocatalyst was shown to promote the spillover of formed CO intermediates from the Ag sites to the 3D porous Cu nanostructure for further reduction to C2 products. Finally, challenges toward the development of multi-metallic electrocatalysts for the direct catalysis of CO2 to hydrocarbons were elucidated, and future perspectives were highlighted.
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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 | 0.000 |
| 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) | 0.000 | 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".