The Effect of Ligand-to-Metal Energy Transfer on the Photooxidation Performance of an Isostructural Series of Pyrene-Based Rare-Earth Metal–Organic Frameworks
Bibliographic record
Abstract
The rectangular tetratopic linker, 1,3,6,8-tetrakis(p-benzoic acid)pyrene (H4TBAPy) along with rare-earth (RE) ions is used for the synthesis of 9 isostructures of a metal–organic framework (MOF) with shp topology, named RE-CU-10 (RE = Y(III), Gd(III), Tb(III), Dy(III), Ho(III), Er(III), Tm(III), Yb(III) and Lu(III)). The synthesis of each RE-CU-10 analogue requires different reaction conditions to achieve high quality phase pure products. Single crystal X-ray diffraction indicates the presence of a RE9-cluster in Y- to Tm-CU-10, while a unique RE11-cluster is observed for Yb- and Lu-CU-10. The photooxi-dation performance of the reported RE-CU-10 analogues is evaluated, giving insight into the competitive process of ligand-to-metal energy transfer versus the generation of singlet oxygen by RE-CU-10. The singlet oxygen produced is used to detoxify a mustard gas simulant 2-chloroethylethyl sulfide (2-CEES) to 2-chloroethyl ethyl sulfoxide (2-CEESO), with half-lives ranging from 4.0 to 5.8 min, some of the fastest reported to date using UV-irradiation and <1 mol% catalyst, in methanol under O2 saturation.
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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) | 0.001 | 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".