Synthesis, Oxygen-Sensing Properties, and Photodegradation of PCN-224-Type Metal–Organic Frameworks Based on Partly Fluorinated Tetrakis(4-carboxyphenyl)porphyrins
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Porphyrin-based metal–organic frameworks (MOFs) are promising candidates for applications involving photoexcitation, such as optical oxygen sensing and photocatalysis. The introduction of electron-withdrawing substituents into the chromophore is an effective way to enhance and improve the photostability of conventional oxygen-sensing materials, but this approach has not yet been studied for MOFs. Herein, we report the synthesis of organic linkers based on meso -tetrakis(4-carboxyphenyl)porphyrin (TCPP), which contains eight fluorine atoms in the meso - or β-positions, and their incorporation into Zr-based MOFs. Similar to TCPP, fluorinated metal-free porphyrins and their Pt(II) complexes form PCN-224-type MOFs. These MOFs show room-temperature fluorescence (in case of nonmetalated linkers) and phosphorescence (with platinated linkers), which is quenched by molecular oxygen. The photophysical and oxygen-sensing properties of MOFs composed of fluorinated and unfluorinated porphyrinic linkers are similar, and no enhancement of photostability is observed. Exposure of MOFs to dimethylformamide vapor strongly accelerates their photobleaching, indicating that this solvent, which is considered essential for the synthesis of Zr-based MOFs, plays a pivotal role in their photodegradation. Studying the photodegradation of linkers in solution revealed much faster bleaching of linkers with free carboxylic acid groups than that of the corresponding methyl esters, suggesting that defects in MOFs resulting in noncoordinated COOH groups may also contribute to photobleaching.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 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 teacher head, 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".