An overview of zeolites synthesised from coal fly ash and their potential for extracting heavy metals from industrial wastewater
Bibliographic record
Abstract
Zeolites are aluminosilicate minerals widely used in industrial applications including as commercial adsorbents and catalysts. This overview focuses on zeolites synthesised from coal fly ash (CFA). Human activities and industrial developments generate large volumes of polluted water, which have a significant ecological impact. Industrial wastewater may consist of different pollutant types, but of specific interest to this work are heavy metals, which. Heavy metal ions are among the most dangerous pollutants due to their toxicity and carcinogenicity. This overview covers the recent scientific literature, focused on using CFA-derived zeolites to remove Ni, Hg, Mn, Cu, Zn, Cd, Pb, Cr, Co both from synthetic solutions replicating industrial wastewater and actual wastewater streams. The results described in many papers cited in this review look promising for industrial wastewater treatment operations. Furthermore, the large variety of possible synthetic zeolites provides a route for energy-efficient, pollutant-specific remediation of industrial heavy metals.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".