Some Observations on the Development of Superior Photocatalytic Systems for Application to Water Purification by the “Adsorb and Shuttle” or the Interphase Charge Transfer Mechanisms
Bibliographic record
Abstract
Adsorb and shuttle (A/S) and interfacial charge transfer are the two major strategies for overcoming recombination in photocatalysis in this era of nanoparticle composites. Their relationships are considered here. A review of key literature is accompanied by a presentation of three new experiments within the overall aim of assessing the relation of these strategies. The cases presented include: A/S by a high silica zeolite/TiO2 composite, charge transfer (CT) between phases in a TiO2/WO3 composite and both A/S and CT by composites of TiO2 with powered activated carbon (AC) and single-walled carbon nanotubes (SWCNT). The opportunities presented by the two strategies for moving toward photocatalysts that could support applications for the removal of contaminants from drinking water or that lead to a practical adsorbent for organics that could be regenerated photocatalytically link this discussion to ongoing research here.
Stored with the screening record, where it is evidence for the labels above.
How this classification was reachedexpand
The three-model screen
all 5,600 screened works →All three models called this out of scope.
Photocatalysis experiments and review for water purification; chemistry.
This reviews and tests photocatalytic systems for water purification, not evidence-synthesis methodology.
Photocatalysis materials science for water purification.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".