Group IIIA Halometallate Ionic Liquids: Speciation and Applications in Catalysis
Bibliographic record
Abstract
Group IIIA halometallate ionic liquids (ILs) present fascinating properties for the field of catalysis, particularly through the ability to tune their Lewis acidity solely by changing the metal complex speciation. In this Review, we present a critical perspective on the use of Group IIIA halide-derived ILs in catalysis, focusing on the effect of speciation of the metal-containing ions on various acid-catalyzed reactions, some of which are applied industrially. We summarize all applications of Group IIIA halometallates in catalysis (where they are notably well-represented in reactions of importance in petroleum refining and processing), compare the authors’ investigations or assumptions with regard to chemical speciation, and present examples of how the tunability of these materials is used to overcome their initially perceived drawbacks. Further, advances in the field of halometallate ILs such as the role of the cations in the IL, IL analogues, and heterogenization strategies are discussed. High selectivity, reactivity, and stability are the cornerstones of the ideal catalyst, and the journey of catalysis research toward the ideal catalyst will be possible only with rational catalyst design and innovative thinking.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".