Characterization and Potential Use of Kombé Clay Materials in the Adsorption of Chromate and Nitrate Ions
Bibliographic record
Abstract
This work aims to evaluate the ability of Kombé clays, in the Republic of Congo, to adsorb chromate and nitrate ions in water. To do this, we first characterized the clay to obtain information on its physicochemical and mineralogical properties. We then performed chromate and nitrate ion adsorption tests on this material to assess its adsorption capacity. To characterize the Kombé clay, we used several analytical techniques, such as particle size distribution and Atterberg limits, X-ray diffraction (XRD), chemical analysis, cation exchange capacity (CEC), and specific surface area (SS). The results obtained show that the Kombé clay is plastic and composed of 52% clay, 18% silt, and 30% sand, with a predominance of kaolinite and a significant amount of quartz. Its CEC is 3 meq/100 g and its SS is 16 m²/g. Adsorption tests conducted on this clay indicate that it can be used for the adsorption of chromate and nitrate ions. The adsorption results show that Kombé clay removes 2.59% of chromate ions and 15.94% of nitrate ions. In light of these results, this study reveals that Kombé clay can be used in the treatment of polluted water as an adsorbent, as well as in applications for traditional and structural ceramics (bricks, tiles, etc.). However, this adsorption capacity is low and needs to be improved.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".