Removal of hexavalent chromium from aqueous solutions using almond green hull adsorbent magnetized by Fe3O4: isotherm, kinetic and thermodynamic studies
Bibliographic record
Abstract
ABSTRACT In this study, the efficiency of almond green hull magnetized by Fe 3 O 4 in the removal of hexava-lent chromium from aqueous solutions was investigated. Structural characteristics of this adsorbent were determined by Fourier Transform Infrared Spectroscopy (FTIR), scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), vibrating-sample magnetometer (VSM) and Brunauer–Emmett–Teller (BET). The parameters examined for the removal of Cr(VI) included pH (2–12), initial concentration of hexavalent chromium (10–100 mg/L), adsorbent dose (0.1–0.8 g/L), contact time (1–60 min), and temperature (5–50°C). Finally, the isotherm and kinetics of the adsorption process were investigated. The result of this study showed that removal of Cr(VI) was higher in acidic pH. By increasing the adsorbent dose, contact time, temperature and reducing the initial concentration of the pollutant, the removal efficiency increased. In optimal conditions, the maximum removal efficiency of Cr(VI) by almond green hull magnetized by Fe 3 O 4 was equal to 100% and maximum adsorption capacity was 25 mg/g, (optimal conditions: pH = 2, adsorbent dose: 0.8 g/L, initial concentration of Cr(VI): 20 mg/L, time: 60 min, temperature: 50°C). The results showed that the adsorption process is more consistent with Langmuir isotherm and pseudo-second order kinetics. The thermodynamic results of the adsorption process showed that this process was endothermic and spontaneous. In summary, the adsorption process on almond green hull magnetized by Fe 3 O 4 can be used as a new and efficient method in the removal of Cr(VI) from aqueous solutions.
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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) | 0.000 | 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".