Synergistic Effect of Fe Doping and Plasmonic Au Nanoparticles\non W<sub>18</sub>O<sub>49</sub> Nanorods for Enhancing Photoelectrochemical\nNitrogen Reduction
Bibliographic record
Abstract
Photoelectrochemical (PEC) nitrogen fixation has opened up new possibilities for the production\nof ammonia from water and air under mild conditions, but this process\nis confronted by the inherent challenges associated with theoretical\nand experimental works, limiting the efficiency of the nitrogen reduction\nreaction. Herein, we report for the first time a novel and efficient\nphotoelectrocatalytic system, which has been prepared by assembling\nplasmonic Au nanoparticles with Fe-doped W<sub>18</sub>O<sub>49</sub> nanorods (denoted as WOF-Au). (i) The introduction of exotic Fe\natoms into nonstoichiometric W<sub>18</sub>O<sub>49</sub> can eliminate\nbulk defects of the W<sub>18</sub>O<sub>49</sub> host, which resulted\nin narrowing bandgap energy and facilitating electron–hole\nseparation and transportation. (ii) Meanwhile, Au nanoparticles combined\nwith a semiconductor induce the localized surface plasmon resonance\nand generate energetic (hot) electrons, increasing electron density\non W<sub>18</sub>O<sub>49</sub> nanorods. Consequently, this plasmonic\nWOF-Au system shows an NH<sub>3</sub> production yield of 9.82 μg\nh<sup>–1</sup> cm<sup>–2</sup> at −0.65 V versus\nAg/AgCl, which is ∼2.5-folds higher than that of the WOF (without\nAu loading), as well as very high stability, and no NH<sub>3</sub> formation was found for the bare W<sub>18</sub>O<sub>49</sub> (WO).\nThis high activity can be associated with the synergistic effects\nbetween the Fe dopant and plasmonic Au NPs on the host semiconductor\nW<sub>18</sub>O<sub>49</sub>. This work can bring some insights into\nthe target-directed design of efficient plasmonic hybrid systems for\nN<sub>2</sub> fixation and artificial photocatalysis.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".