Materials and Mechanisms of Photo‐Assisted Chemical Reactions under Light and Dark Conditions: Can Day–Night Photocatalysis Be Achieved?
Bibliographic record
Abstract
-assisted photochemical reactions has led to several unique applications, such as degradation of pollutants in water and air, hydrogen production through water splitting, fuel conversion, cancer treatment, antibacterial activity, self-cleaning glasses, and concrete. These multifaceted applications of this phenomenon can be enriched and expanded further if this process is equipped with more tools and functions. The term "photoassisted" catalytic reactions clearly emphasizes that photons are required to activate the catalyst; this can be transcended even into the dark if electrons are stored in the material for the later use to continue the catalytic reactions in the absence of light. This can be achieved by equipping the photocatalyst with an electron-storage material to overcome current limitations in photoassisted catalytic reactions. In this context, this article sheds lights on the materials and mechanisms of photocatalytic reactions under light and dark conditions. The manifestation of such systems could be an unparalleled technology in the near future that could influence all spheres of the catalytic sciences.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".