A Combined Quantum Mechanical and Statistical Mechanical Study of the Equilibrium of Trimethylaluminum (TMA) and Oligomers of (AlOCH<sub>3</sub>)<i><sub>n</sub></i> Found in Methylaluminoxane (MAO) Solution
Bibliographic record
Abstract
Density Functional Theory (DFT) has been used to calculate the energies of over 30 different structures with the general formula (AlOMe)(n).(AlMe(3))(m) where n ranges from 6 to 13 and m ranges between 1 and 4, depending upon the structure of the parent (AlOMe)(n) cage. The way in which TMA (trimethylaluminum) bonds to MAO (methylaluminoxane) has been determined as well as the location of the acidic sites present in MAO caged structures. Topological arguments have been used to show that TMA does not bind to MAO cages where n = 12 or n > or = 14. The ADF energies in conjunction with frequency calculations based on molecular mechanics have been used to estimate the finite temperature enthalpies, entropies, and free energies of the TMA containing MAO structures. Using the Gibbs free energies found for pure MAO structures calculated in a previous work, in conjunction with the free energies of TMA containing MAO structures obtained in the present study, it was possible to determine the percent abundance of each TMA containing MAO within the temperature range of 198.15 K-598.15 K. We have found that very little TMA is actually bound to MAO. The Me/Al ratio on the MAO cages is determined as being approximately 1.00, 1.01, 1.02, and 1.03 at 198, 298, 398, and 598 K, respectively. Moreover, the percentage of Al found as TMA has been calculated as being 0.21%, 0.62%, 1.05%, and 1.76% and the average unit formulas of (AlOMe)(18.08).(TMA)(0.04), (AlOMe)(17.04).(TMA)(0.11), (AlOMe)(15.72).(TMA)(0.17), and (AlOMe)(14.62).(TMA)(0.26) have been determined at the aforementioned temperatures.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".