Supramolecular concepts and new techniques in mechanochemistry: cocrystals, cages, rotaxanes, open metal–organic frameworks
Bibliographic record
Abstract
Mechanochemical reactions effected by milling or grinding are an attractive means to conduct chemical reactions dependent on molecular recognition and to systematically explore different modes of molecular self-assembly. The natural relationship between milling mechanochemistry and supramolecular chemistry arises primarily from the ability to avoid bulk solvent, which simultaneously avoids limitations of solution-based chemistry, such as solubility, solvent complexation, or solvolysis, and makes the resulting process highly environmentally friendly. This tutorial review highlights the use of mechanochemistry for the synthesis of supramolecular targets in the solid state, such as molecular hydrogen- or halogen-bonded complexes, molecular and supramolecular cages, open frameworks and interlocked architectures. It is also demonstrated that the molecular self-assembly phenomena that are well-established in solution chemistry, such as reversible binding through covalent or non-covalent bonds, thermodynamic equilibration and structure templating, are also accessible in milling mechanochemistry through recently developed highly efficient methodologies such as liquid-assisted grinding (LAG) or ion- and liquid-assisted grinding (ILAG). Also highlighted are the new opportunities arising from the marriage of concepts of supramolecular and mechanochemical synthesis, including organocatalysis, deracemisation and discovery of new molecular recognition motifs.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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".