Influence of thermal and acidic treatments on the morphology of a natural kaolinitic clay mineral
Bibliographic record
Abstract
In this work, a natural kaolinitic clay mineral from Kribi in Cameroon is modified by thermal and acidic treatments. The influence of these treatments on the physicochemical properties of the clays is studied using X-ray diffraction, Fourier transform infrared spectroscopy, nitrogen adsorption–desorption measurements, scanning electron microscopy, inductively coupled plasma–atomic emission spectroscopy and thermal analysis. Three calcination temperatures are explored: 600, 700 and 800 °C. The XRD pattern of the untreated clay showed that the natural clay mineral was mostly composed of kaolinite. Calcination at high temperatures allowed the amorphization of the natural kaolinitic clay mineral to obtain metakaolinite. This heat treatment of the natural clay mineral produced disintegration by rupture of the strong hydrogen bonds between the layers of the clay mineral. Heat treatment did not increase the specific surface area of the clay, which stayed around 20-30 m2/g. The acid treatment produced a high material texture modification giving microporous materials with a large surface area up to 315 m2/g with the sample previously calcined at 800 °C. The microporosity and mesoporosity increase is greater when the clay is calcined at high temperature. The morphology of the samples observed by SEM are modified by the acidic treatment. The initial two-dimensional stacking of particles evolves towards a narrower three-dimensional porous structure. These treatments open the way to produce highly porous clay materials that could be used as adsorbent materials for pollutant removal from water.
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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".