Porphyrin-based MOFs as heterogeneous photocatalysts for the eradication of organic pollutants and toxins
Bibliographic record
Abstract
Water and air pollution are among the major environmental challenges of this era. Waste management, economic sustainable development and renewable energy are unavoidable concomitant considerations. Over the past five years, nanosized metal-organic frameworks (nano-MOFs) have been developed for the elimination of pollutants in wet media and air-born toxins using the highly efficient reactive oxygen species (ROS) of type I (H2O2, •OH, O[Formula: see text] and of type II (1O[Formula: see text]. The ROS are catalytically and efficiently generated through photosensitization, and porphyrins and metalloporphyrins are pigments of choice for this purpose. This short review summarizes the fundamentals of ROS generation by porphyrin-based nano-MOFs (mainly through the formation of ROS type II) and their composites (leading to ROS type I), which includes energy and electron transfer processes, and their applications in these environmental issues.
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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) | 0.000 | 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".