Lindane removal by membrane nanofiltration
Bibliographic record
Abstract
Lindane is the γ-isomer of 1,2,3,4,5,6-hexachlorocyclohexane (HCH) and it has been widely used in the pesticide industry due to its insecticide properties. In the production of lindane, significant quantities of other HCH isomers are generated as byproducts. All these compounds are typically stored in landfills, often with poor management practices. Polyamide membranes, two commercial membranes from Alfa Laval (NF99HF and NF99) and homemade thin film composite membranes prepared by interfacial polymerization on a porous polyimide support, were evaluated for water nanofiltration (NF) of HCH isomers, including lindane. Homemade membranes, with a lindane rejection of 91.3 % and a permeance of 2.7 L·m−2·h−1·bar−1, offered the highest performance in terms of both permeance and rejection. NF99 and homemade membranes were proven to be equally effective in removing α-HCH and β-HCH, showing similar results. Homemade membranes achieved 99.5 and 99.8 % rejections for α-HCH and β-HCH, respectively. Long-term experiments were carried out with NF99 and homemade membranes to assess their stability during filtrations with lindane solutions for up to 214 h. Homemade TFC membrane maintained its initial rejection (ca. 93.5 %) after 214 h, although its permeance decreased over time, ending in 2.5 L·m−2·h−1·bar−1.
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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) | 0.000 | 0.001 |
| 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 | 0.001 | 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".