Nano-twinned Ag Thin Films on Graphene/ Si Photoelectrochemical Cell for CO<sub>2</sub> Reduction and Hydrogen Production
Bibliographic record
Abstract
This study proposes a novel approach for applying the nanotwinned Ag thin films in CO2 reduction.We focus on optimizing the sputter deposition process of nanocrystalline Ag structures on n+Si chips and preparing nanotwinned silver catalysts with good structure, adhesion, and stability.The effects of twinned structure catalysts on the photocatalytic performance were investigated.In this research, the n+Si/Gr/sputtered Ag structure was used as the photoelectrode for photoelectrochemical (PEC) CO2 reduction reaction (CO2RR) since the utilization of graphene can expedite carrier transport, thereby improving device stability and performance in electrolytes.Nanotwinned Ag films were successfully synthesized on graphene transferred n+Si substrates with DC magnetron sputtering.Focused ion beam analyses demonstrated that the addition of graphene did not diminish the nanotwin density; rather, it improved the quality of the sputtered Ag thin films, which leads the framework to a potential structure for PEC CO2RR.
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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".