Disorder and Linker Deficiency in Porphyrinic Zr-MOFs: Resolving the Zr8O6 Cluster Conundrum in PCN-221
Bibliographic record
Abstract
Porphyrin-based metal-organic frameworks (MOFs), exemplified by the prototypical representatives MOF-525, PCN-221, and PCN-224 are among the most promising MOF systems for catalysis, optoelectronics, and solar energy conversion. However, subtle differences between synthetic protocols for these three MOFs give rise to vast discrepancies in purported product outcomes and description of framework topologies. Here, we reveal the type and disorder of the Zr-clusters based on a comprehensive synthetic and structural analysis spanning local and long-range length scales. Our analysis on PCN-221 reveals Zr6O4(OH)4 clusters in four distinct orientations within the unit cell, rather than Zr8O6 clusters as originally published, accompanied by random linker vacancies around 50%. We propose disordered PCN-224 (dPCN-224) as a unified model to understand PCN-221, MOF-525, and PCN-224 by varying the degree of orientational cluster disorder, linker conformation and vacancies, and cluster—linker binding. Our work thus introduces a new perspective on network topology and disorder in Zr-MOFs and pinpoints the structural variables that direct their functional properties.
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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".