Production of low-price carbon for removal of aluminium ions in potable water
Bibliographic record
Abstract
Drinking-water plants often use aluminium (Al) salts as coagulant agents in the water-treatment process, which cause increasing aluminum residue levels in water. Aluminum accumulation in the human body has been related to neurological disorders such as Alzheimer’s disease, senile dementia and breast cancer. This work utilises the available industrial waste as a cheap source of carbon (C) that can be used in aluminium ion elimination from water supplies. The employed sugarcane bagasse activated carbon (SCB-AC) was derived from the waste of a Qus sugar factory in Qena City, Egypt. The activity of SCB-AC was compared with that of commercial activated carbon (Com-AC), and their physico-chemical properties were characterised by various techniques (energy-dispersive X-ray spectroscopy, scanning electron microscopy and Fourier transform infrared spectroscopy). The findings demonstrate that SCB-AC has high performance for aluminium (III) (Al 3+ ) removal like Com-AC, which reached 80% at a high initial concentration (10 mg/l). The thermodynamic constants revealed that the adsorption process has an exothermic nature. Briefly, SCB-AC is an inexpensive eco-friendly carbon with an excellent adsorptive ability like that of Com-AC for elimination of aluminium (III) in drinking water. The cost of manufacturing SBC-AC would be about US$40/t.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".