Insight into Magnesium Coordination Environments in Benzoate and Salicylate Complexes through <sup>25</sup>Mg Solid-State NMR Spectroscopy
Bibliographic record
Abstract
We report on the (25)Mg solid-state nuclear magnetic resonance (NMR) characterization of a series of magnesium complexes featuring Mg(2+) ions in organic coordination environments. Six compounds have been synthesized with benzoate and salicylate ligands, which are typically used as linkers in metal organic frameworks (MOFs). The use of ultrahigh-field solid-state NMR has revealed a relatively large range of values for the (25)Mg quadrupolar coupling constant, CQ((25)Mg), in these compounds. In contrast to some previously studied inorganic Mg(2+) complexes, the values of CQ((25)Mg) in organic Mg(2+) complexes are well rationalized by the degree of octahedral strain of the "MgO6" coordination polyhedra. (13)C and (25)Mg isotropic chemical shifts were also found to be sensitive to the binding mode of the carboxylate ligands. The experimental findings are corroborated by gauge-including projector-augmented-wave (GIPAW) density functional theory (DFT) computations, and these have allowed for an interpretation of the experimentally observed trend in the CQ((25)Mg) values and for the visualization of the EFG tensor principal components with respect to the molecular structure. These new insights may prove to be valuable for the understanding and interpretation of (25)Mg NMR data for Mg(2+) ions in organic binding environments such as those found in MOFs and protein-divalent metal binding sites.
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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".