Solid-state <sup>27</sup>Al nuclear magnetic resonance investigation of three aluminum-centered dyes
Bibliographic record
Abstract
We report the first solid-state 27Al NMR study of three aluminum phthalocyanine dyes: aluminum phthalocyanine chloride, AlPcCl (1); aluminum-1,8,15,22-tetrakis(phenylthio)-29H,31H-phthalocyanine chloride, AlPc(SPh)4Cl (2); and aluminum-2,3-naphthalocyanine chloride, AlNcCl (3). Each of these compounds contains Al3+ ions coordinating to four nitrogen atoms and a chlorine atom. Solid-state 27Al NMR spectra, including multiple-quantum magic-angle spinning (MQMAS) spectra and quadrupolar Carr–Purcell–Meiboom–Gill (QCPMG) spectra of stationary powdered samples have been acquired at multiple high magnetic field strengths (11.7, 14.1, and 21.1 T) to determine their composition and number of aluminum sites, which were analyzed to extract detailed information on the aluminum electric field gradient (EFG) and nuclear magnetic shielding tensors. The quadrupolar parameters for each 27Al site were determined from spectral simulations, with quadrupolar coupling constants (CQ) ranging from 5.40 to 10.0 MHz and asymmetry parameters (η) ranging from 0.10 to 0.50, and compared well with the results of quantum chemical calculations of these tensors. We also report the largest 27Al chemical shielding anisotropy (CSA), with a span of 120 ± 10 ppm, observed directly in a solid material. The combination of MQMAS and computational predictions are used to interpret the presence of multiple aluminum sites in two of the three samples.
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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".