A High Efficiency Si Photoanode Protected by Few‐Layer MoSe<sub>2</sub>
Bibliographic record
Abstract
To date, the performance of semiconductor photoanodes has been severely limited by oxidation and photo‐corrosion. Here, a report is given on the use of earth‐abundant MoSe2 as a surface protection layer for Si‐based photoanodes. Large area MoSe2 film was grown on p+‐n Si substrate by molecular beam epitaxy. It is observed that the incorporation of few‐layer (≈3 nm) epitaxial MoSe2 can significantly enhance the performance and stability of Si photoanode. The resulting MoSe2/p+‐n Si photoanode produces a light‐limited current density of 30 mA cm−2 in 1 M HBr under AM 1.5G one sun illumination, with a current‐onset potential of 0.3 V versus reversible hydrogen electrode (RHE). The applied bias photon‐to‐current efficiency (ABPE) reaches up to 13.8%, compared to the negligible ABPE values (<0.1%) for a bare Si photoanode under otherwise identical experimental conditions. The photoanode further produced stable voltage of ≈0.38 V versus RHE at a photocurrent density of ≈2 mA cm−2 for ≈14 h under AM 1.5G one sun illumination. This work shows the extraordinary potential of two‐dimensional transitional metal dichalcogenides in photoelectrochemical application and will contribute to the development of low cost, high efficiency, and highly stable Si‐based photoelectrodes for solar hydrogen production.
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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".