Functionalization of the Interlayer Surfaces of Kaolinite by Alkylammonium Groups From Ionic Liquids
Bibliographic record
Abstract
Abstract The objective of this study was to design new, functional, nanostructured materials from the abundant clay mineral kaolinite, in spite of development problems with the interlayer chemistry of kaolinite because of its non-swelling properties. A particular goal of this work was to graft, in a controlled way, alkylammonium groups onto the aluminol interlayer surfaces of kaolinite. This was successfully achieved by soft-chemical approaches, more specifically by the melting intercalation process of alkylammonium ionic liquids which were synthesized for this purpose. The resulting nanohybrid materials were characterized chemically and structurally by X-ray diffraction analysis, thermal analysis (TG/DTA), 13C cross polarization magic angle spinning nuclear magnetic resonance spectroscopy, and Fourier-transform infrared spectroscopy. The amount of grafted organic material was quantified from TGA results. Alkylammonium salts with a short alkyl chain were grafted directly using a melting reaction at 180°C under N2 involving the in situ displacement of dimethylsulfoxide (DMSO) from a DMSO-kaolinite pre-intercalate; for longer alkyl chains, the grafting was done in two steps. In the first step, the corresponding amino-alcohol was grafted into the kaolinite by displacement of DMSO from the interlayer space. The second step consisted of quaternarization of the grafted material by reaction with iodomethane or iodoethane.
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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".