In-Situ Monitoring of Mechanochemical MOF Formation by NMR Relaxation Time Correlation
Bibliographic record
Abstract
In this paper, we present a new approach to monitoring mechanochemical transformations, based on a magnetic resonance method in which relaxation time correlation maps are used to track the formation of the popular metal-organic framework (MOF) materials Zn-MOF-74 and ZIF-8. The two-dimensional (2D) relaxation correlation measurement employed yields a T1-T2* spectrum which visually and analytically identifies different 1H environments in the sample of interest. The measurement is well-suited to analyzing solid mixtures, and liquids, in complex systems. Application in this work to monitoring MOF formation shows changes in signal amplitudes, and their MR lifetime coordinates, within the 2D plots as the reaction progresses, confirming reaction completion. This new measurement provides a simple way to analyse solid-state reactions without dissolution, and there is a logical pathway to benchtop measurement with a new generation of permanent magnet-based MR instruments. The methodology described permits measurement in an MR compatible milling container, which may be directly transferred from the shaker assembly to the MR magnet for in-situ measurement of the entire reaction mixture.
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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".