Decoupling Strategy for Enhanced Syngas Generation from Photoelectrochemical CO2 Reduction
Bibliographic record
Abstract
Photoelectrochemical CO 2 reduction into syngas (a mixture of CO and H 2 ) provides a promising route to mitigate greenhouse gas emissions and store intermittent solar energy into value-added chemicals. Design of photoelectrode with high energy conversion efficiency and controllable syngas composition is of central importance but remains challenging. Herein, we report a decoupling strategy using dual cocatalysts to tackle the challenge based on joint computational and experimental investigations. Density functional theory calculations indicate the optimization of syngas generation using a combination of fundamentally distinctive catalytic sites. Experimentally, by integrating spatially separated dual cocatalysts of a CO-generating catalyst and a H 2 -generating catalyst with GaN nanowires on planar Si photocathode, we report a record high applied bias photon-to-current efficiency of 1.88% and controllable syngas products with tunable CO/H 2 ratios (0–10) under one-sun illumination. Moreover, unassisted solar CO 2 reduction with a solar-to-syngas efficiency of 0.63% is demonstrated in a tandem photoelectrochemical cell.
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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".