Rationalizing the Unexpected Inefficiencies of 3D Porphyrin‐MOFs as Singlet Oxygen Photosensitizers Against <i>Botrytis cinerea</i>
Bibliographic record
Abstract
Abstract Porphyrin‐based MOFs (PMOFs) are known to be efficient photocatalysts and singlet oxygen (1O2) photosensitizers (PS) in solution, but their application in agriculture and food protection is practically unknown. In vitro tests on Botrytis cinerea using the renowned PCN‐222 and PCN‐224 reveal modest photo‐antifungal activities at the solid–gas interface when compared to their standalone tetrakis(4‐carboxyphenyl)porphyrin (TCPP) linker. This in‐depth study examines the direct detection of 1O2(g) phosphorescence at the solid–air interface, binding of the PMOFs with the spores of B. cinerea by fluorescence microscopy, fluorescence quenching of the PMOFs by oxygen, and rates of exciton migration evaluated through the singlet‐singlet annihilation process. The conclusion is that a significant proportion of 1O2 is unable to escape the porous materials before deactivation, or does so too late to then be able to reach, and that excitation migration is not efficient enough to generate significant amounts of 1O2 directly at the MOF surface. Given that TCPP is its own interface with the gas phase, it is not hindered by these factors, which explains its higher efficiency under these circumstances.
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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".