Investigation of Silver-Containing Layered Materials and Their Interactions with Primary Amines Using Solid-State <sup>109</sup>Ag and <sup>15</sup>N NMR Spectroscopy and First Principles Calculations
Bibliographic record
Abstract
Silver-containing layered networks of the form [Ag(L)] (L = 4-pyridinesulfonate or p-toluenesulfonate) were treated with primary amines in different ratios. The structures of the parent supramolecular networks are well-known; however, their interactions with primary amines lead to the formation of new layered materials for which single-crystal X-ray structures cannot be obtained. Solid-state (109)Ag, (15)N, and (13)C cross-polarization magic-angle spinning (CP/MAS) NMR experiments, in combination with powder X-ray diffraction experiments and ab initio calculations, are utilized to investigate the interactions between the primary amines and the parent materials, and to propose structural models for the new materials. (109)Ag chemical shift (CS) tensor parameters are extremely sensitive to changes in silver environments; hence, (1)H-(109)Ag CP/MAS NMR experiments are used to distinguish and characterize silver sites. The combination of (109)Ag and (15)N NMR experiments on starting materials and samples prepared with both (15)N-labeled and unlabeled amines permits the accurate measurements of indirect (1)J((109)Ag,(15)N) and (1)J((109)Ag,(14)N) spin-spin coupling constants, providing further information on structure and bonding in these systems. First principles calculations of silver CS tensors and (1)J((109)Ag,(14)N) coupling constants in model complexes aid in formulating the proposed structural models for the new materials, which are largely comprised of layers of silver-diamine cations.
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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".