Electronic structure of aqueous two-dimensional photocatalyst
Bibliographic record
Abstract
Abstract The electronic structure, in particular the band edge position, of photocatalyst in presence of water is critical for photocatalytic water splitting. We propose a direct and systematic density functional theory (DFT) scheme to quantitatively predict band edge shifts and their microscopic origins for aqueous 2D photocatalyst, where thousands of atoms or more are able to be involved. This scheme is indispensable to correctly calculate the electronic structure of 2D photocatalyst in the presence of water, which is demonstrated in aqueous MoS2, GaS, InSe, GaSe and InS. It is found that the band edge of 2D photocatalysts are not rigidly shifted due to water as reported in previous studies of aqueous systems. Specifically, the CBM shift is quantitatively explained by geometric deformation, water dipole and charge redistribution effect while the fourth effect, i.e., interfacial chemical contact, is revealed in the VBM shift. Moreover, the revealed upshift of CBM in aqueous MoS2should thermodynamically help carriers to participate in hydrogen evolution reaction (HER), which underpin the reported experimental findings that MoS2is an efficient HER photocatalyst. Our work paves the way to design 2D materials in general as low-cost and high-efficiency photocatalysts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".