Metal-free photocatalysts for hydrogen evolution
Bibliographic record
Abstract
, h-BN etc.) and their heterojunction, ternary photocatalysts (i.e. BCN) and their heterojunction, and different types of organic photocatalysts (i.e. linear, covalent organic frameworks, microporous polymer, covalent triazine frameworks etc.) and their heterostructures. Following a succinct depiction of the latest progress in hydrogen evolution on these photocatalysts, discussion has been extended to the potential strategies that are deemed necessary to attain high quantum efficiency and high solar-to-hydrogen (STH) conversion efficiency. Issues with reproducibility and the disputes in reporting the hydrogen evolution rate have been also discussed with recommendations to overcome them. A few key factors are highlighted that may facilitate the scalability of the photocatalyst from microscale to macroscale production in meeting the targeted 10% STH. This review is concluded with additional perspectives regarding future research in fundamental materials aspects of high efficiency photocatalysts followed by six open questions that may need to be resolved by forming a global hydrogen taskforce in order to translate bench-top research into large-scale production of hydrogen.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".