Adsorption of benzene, toluene, and xylene (BTX) from binary aqueous solutions using commercial organoclay
Bibliographic record
Abstract
Abstract Organoclays are promising alternative adsorbents for the removal of organic pollutants. The aromatic hydrocarbons benzene, toluene, and xylene (BTX) are typical petroleum contaminants found simultaneously in natural leaking. Therefore, investigations on multi‐component adsorption become essential to study this issue. Based on that, in the present study, a commercial organoclay from Brazil has been tested for its adsorption potential for binary aqueous mixtures of BTX. Kinetic and equilibrium batch adsorption experiments were performed to elucidate the differences in the affinities between the BTX contaminants and the organoclay. The kinetic study indicated that for benzene‐toluene, benzene‐xylene, and toluene‐xylene systems the contaminants preferentially adsorbed were toluene, p‐xylene, and p‐xylene (in the beginning of the assays), respectively. The affinity for the organoclay might be related to physicochemical properties of BTX. In the adsorption equilibrium studies, the obtained BTX isotherms were all linear, characterized by constant adsorption affinities. The observed differences between BTX adsorption capacities at equilibrium for mono and bi‐component systems confirmed the competition for adsorption sites of the organoclay.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".