Low-Dimensional Magnetism in Multivariate Copper/Zinc MOF-74 Materials Formed via Different Mechanochemical Methods
Bibliographic record
Abstract
MOF-74 is an archetypal magnetic metal–organic framework (MOF) family, with metal nodes bridged by 2,5-dioxido-1,4-benzenedicarboxylic acid (H 4 dobdc) and arranged into one of the simplest representations of the 1D Ising magnetic model. Recently, a novel mechano-synthetic approach opened a pathway toward a series of bimetallic multivariate (1:1) M1M2-MOF-74 materials, with the uniform distribution of metal cations in the oxometallic chains, offering a unique opportunity to investigate low-dimensional magnetism in these heterometallic MOFs. We explore here how different mechanochemical procedures affect the interaction between the metal nodes of the model system of three multivariate copper(II)/zinc(II)-MOF-74 materials, two of which were obtained through a template-controlled procedure, and the third one was obtained by recently developed mechanical MOF-alloying combined with subsequent accelerated aging. While the three Cu/Zn-MOF-74 products have almost identical powder X-ray diffraction (PXRD) diffractograms and Fourier transform infrared spectra, they differ significantly in their magnetic properties, as revealed through detailed magnetization and X-band and multifrequency high-field electron spin resonance measurements. The magnetic results of the three multivariate Cu/Zn-MOF-74s were compared to the properties of the monometallic Cu-MOF-74, which shows antiferromagnetic intrachain and weaker ferromagnetic interchain interactions. Energy-dispersive X-ray spectroscopy/scanning electron microscopy and solid-state nuclear magnetic resonance spectroscopy helped rationalize the observed differences in magnetization, and in situ synchrotron PXRD monitoring of template-controlled MOF formation revealed different reaction pathways when using the zinc or copper intermediates, involving even the fleeting occurrence of a rare MOF-74 polymorph.
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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".