Enhanced Charge Carrier Dynamics on Sb<sub>2</sub>Se<sub>3</sub> Photocathodes for Efficient Photoelectrochemical Nitrate Reduction to Ammonia
Bibliographic record
Abstract
Abstract Ammonia (NH3) is recognized as a transportable carrier for renewable energy fuels. Photoelectrochemical nitrate reduction reaction (PEC NO3RR) offers a sustainable solution for nitrate‐rich wastewater treatment by directly converting solar energy to ammonia. In this study, we demonstrate the highly selective PEC ammonia production from NO3RR by constructing a CoCu/TiO2/Sb2Se3 photocathode. The constructed CoCu/TiO2/Sb2Se3 photocathode achieves an ammonia Faraday efficiency (FE) of 88.01 % at −0.2 VRHE and an ammonia yield as high as 15.91 μmol h−1 cm−2 at −0.3 VRHE with an excellent onset potential of 0.43 VRHE. Dynamics experiments and theoretical calculations have demonstrated that the CoCu/TiO2/Sb2Se3 photocathode possesses high light absorption capacity, excellent carrier transfer capability, and high charge separation and transfer efficiencies. The photocathode can effectively adsorb the reactant NO3− and intermediate, and the CoCu co‐catalyst increases the maximum Gibbs free energy difference between NO3RR and HER. Meanwhile, the Co species enhances the spin density of Cu, and increases the density of states near the Fermi level in pdos, which results in a high PEC NO3RR activity on CoCu/TiO2/Sb2Se3. This work provides a new avenue for the feasibility of efficient PEC ammonia synthesis from nitrate‐rich wastewater.
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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".