Comparison of PGSE NMR and ESI-MS Measurements on Methylaluminoxane
Bibliographic record
Abstract
PGSE NMR and ESI-MS studies of different grades of hydrolytic MAO demonstrate that the average dimensions and anion distribution of MAO are correlated with one another, as revealed through studies of aging and gelation of a commercial formulation of MAO. Formulations featuring an anion distribution skewed to higher m/z ratios have significantly higher activator contents as measured by 1H NMR spectroscopy in otherwise very similar formulations. PSGE NMR studies in toluene vs. chlorobenzene media demonstrate that the average dimensions of MAO are largely unaffected by solvent polarity, though aggregation behavior is more pronounced in the more polar solvent. As for catalyst activation and ion-pair speciation, the situation in polar solvents is complicated by the formation of solvated cations (and anions) in chlorobenzene which dramatically lower dimensions. DFT studies of model aluminoxane structures in the size range for MAO featuring a variety of architectures, molar mass and Me3Al content reveal that a linear correlation between Dt, as measured by PGSE NMR, can be related to molar mass using simple relationships and estimates of molecular volume if suitable high molecular weight standards are available. There is a reasonable agreement in molar mass with available ESI-MS data, recognizing that MAO is not monodisperse.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".