Interrogating the Lewis Acidity of Metal Sites in Beta Zeolites with <sup>15</sup>N Pyridine Adsorption Coupled with MAS NMR Spectroscopy
Bibliographic record
Abstract
The Lewis acidity of isolated framework metal sites in Beta zeolites was characterized with 15 N isotopically labeled pyridine adsorption coupled with magic-angle spinning nuclear magnetic resonance (MAS NMR) spectroscopy. The 15 N chemical shift of adsorbed pyridine was found to scale with the acid character of both Lewis (Ti, Hf, Zr, Nb, Ta, and Sn) and Brønsted (B, Ga, and Al) acidic heteroatoms. The 15 N chemical shift showed a linear correlation with Mulliken electronegativity of the metal center in the order Ti < Hf < Zr < Nb < Ta < Sn < H + . Theoretical calculations using density functional theory (DFT) showed a strong correlation between experimental 15 N chemical shift and the calculated metal–nitrogen bond dissociation energy, and revealed the importance of active site reorganization when determining adsorption strength. The relationships found between 15 N pyridine chemical shift and intrinsic chemical descriptors of metal framework sites complement adsorption equilibrium data and provide a robust method to characterize, and ultimately optimize, metal-reactant binding and activation for Lewis acid zeolites. Direct 15 N MAS NMR detection protocols applied to the Lewis acid–base adducts allowed the differentiation and quantification of framework metal sites in the presence of extraframework oxides, including highly quadrupolar nuclei that are not amenable for quantification with conventional NMR methods.
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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) | 0.000 | 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".