Mechanochemistry for Metal–Organic Frameworks and Covalent–Organic Frameworks (MOFs, COFs): Methods, Materials, and Mechanisms
Bibliographic record
Abstract
The mechanochemistry of metal-organic frameworks (MOFs) is a well-established field whose development has advanced the understanding and the design of both MOF materials and mechanochemical reactions. This review outlines the close and mutually beneficial interplay of these two fields over the past two decades, including the description of mechanochemical strategies to access MOFs as well as the response of these materials to mechanical treatment and/or stress. Furthermore, we highlight how the use of MOFs as model targets for mechanochemical synthesis simultaneously improves the accessibility and understanding of this class of materials and, conversely, advances the experimental and fundamental understanding of mechanochemical reactions. Similarly, we show the reciprocal benefits of comparing the mechanochemistry of organic molecular solids to that of MOFs. Finally, this review also portrays the rapid emergence of mechanochemistry of covalent-organic frameworks, a young area that promises to deliver new, rapid, efficient, solventless, and room-temperature access to these materials.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".