Kaolinite–ionic liquid nanohybrid materials as electrochemical sensors for size-selective detection of anions
Bibliographic record
Abstract
Functionalized nanohybrid materials based on clay minerals were obtained by grafting ionic liquids (trihydroxyethylmethylammonium iodide (AE1), 1-(2-hydroxyethyl)-3-methylimidazolium chloride (AE2) and 1-benzyl-3-(2-hydroxyethyl) imidazolium chloride (AE3) of different sizes in the interlayer spaces of kaolinite. The grafting was confirmed by several characterization techniques (XRD, 13C CP/MAS NMR and thermal analysis). The interlayer distances of the grafted materials were 4.1 Å, 6.0 Å and 8.7 Å for AE1, AE2 and AE3, respectively. These materials have an anion exchange capacity related to the mobility of the counter anions of grafted cations. In aqueous medium, the anion exchange capacity does not allow a variation of the interlayer distance of kaolinite, as confirmed by XRD measurements. The interlayer distance of the nanohybrid materials is controlled by the grafted cations. These properties of anion exchangers have been used to achieve the voltammperometric detection of some anions with different sizes (thiocyanate, sulphite and ferricyanide ions), using glassy carbon electrodes coated with a thin film of the modified kaolinite. There is a good correlation between the size of the analyzed anion and the basal spacing of the material used for the electrode modification: depending on the system, the presence of the thin film induces an increase of the current intensities when the anion can easily diffuse through the interlayer space or acts as a barrier when the basal spacing does not allow its insertion. This work shows that derivatives of kaolinite can be used for the selective detection of anions in aqueous solution, using their size as a differentiating factor.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".