A Comparison of Gallium and Indium Alkoxide Complexes as Catalysts for Ring-Opening Polymerization of Lactide
Bibliographic record
Abstract
The impact of the metal size and Lewis acidity on the polymerization activity of group 13 metal complexes was studied, and it was shown that, within the same ligand family, indium complexes are far more reactive and selective than their gallium analogues. To this end, gallium and aluminum complexes supported by a tridentate diaminophenolate ligand, as well as gallium complexes supported by N, N ′-ethylenebis(salicylimine)(salen) ligands, were synthesized and compared to their indium analogues. Using the tridentate ligand set, it was possible to isolate the gallium chloride complexes 3 and (±)- 4 and the aluminum analogues 5 and (±)- 6 . The alkoxygallium complex (±)- 2, supported by a salen ligand, was also prepared and characterized and, along with the three-component system GaCl 3 /BnOH/NEt 3, was tested for the ring-opening polymerization of lactide and ε-caprolactone. The polymerization rates and selectivities of both systems were significantly lower than those for the indium analogues. The reaction of (±)- 2 with 1 equiv of lactide forms the first insertion product, which is stable in solution and can be characterized at room temperature. In order to understand the differences of the reactivity within the group 13 metal complexes, a Lewis acidity study using triethylphosphine oxide (the Gutmann–Beckett method) was undertaken for a series of aluminum, gallium, and indium halide complexes; this study shows that indium halide complexes are less Lewis acidic than their aluminum and gallium analogues. Density functional theory calculations show that the Mulliken charges for the indium complexes are higher than those for the gallium analogues. These data suggest that the impact of ligands on the reactivity is more significant than that of the metal Lewis acidity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".