Red mud (aluminum industrial waste): An eco‐friendly treatment of electroplating effluent
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract In this work, aluminum industrial waste, red mud (RM), was activated to verify its potential in the management of electroplating wastewater containing hexavalent chromium (Cr(VI)). A comparison between the adsorption capabilities of RM and activated red mud (ARM) towards Cr(VI) from aqueous solutions was made. The effects of several parameters were evaluated. The adsorbents were characterized by field emission scanning electron microscopy (FESEM), Fourier transmission infrared spectroscopy (FTIR), x‐ray diffraction (XRD), zeta potential, and thermogravimetric analysis (TGA). The particle size was observed as 23.59 nm. The ARM demonstrated an acceptable adsorption capacity of 25.641 mg/g at a pH of 2, adsorbent dosage of 2 g/L, initial Cr(VI) concentration of 100 mg/L, at 25°C. The experimental data is in good agreement with Langmuir adsorption isotherm. The kinetic study was performed to verify that the adsorption follows pseudo‐second‐order kinetics. In addition, the ARM showed decent recyclability for adsorbing Cr(VI) as even after three adsorption cycles, and the adsorption capacity was reduced by ~30%. The results recommend ARM to be an efficient and cost‐effective adsorbent for Cr(VI) removal from industrial wastewater.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 it