Material integrity of LDPE-based solar water disinfection reactors with improved usability
Bibliographic record
Abstract
ABSTRACT This work investigated the changes in material integrity of solar water disinfection (SODIS) reactors, which had been developed to overcome usability-related short comings of previous designs, for usages in rural areas. During a 12-week period of usage of the new reactors in actual environments, the degradation of the materials was investigated weekly, with respect to surface morphologies, compositions, optical transmissions, tensile strengths, and leaching of organic compounds from the reactors into the treated water. The results showed that there were no scratches on the low-density polyethylene (LDPE) bags (the water-containing components of the reactors), which were problematic in the previous design. The maximum reduction of tensile strength was 28.5%. The optical transmittances in the UVA region of the LDPE and PVC components of the reactors decreased by 11% and 53%, respectively. The composition results indicated that the LDPE bags photo-degraded via an oxidation reaction. 2,4 di-tert-butyl phenol, a known degradation product from antioxidants of polyethylene, was found in some samples of treated water, but at levels close to the method of detection’s limit as well as those in the control samples. In addition, the optical transmittances in the UVA region of the LDPE and PVC components of the reactors decreased by 11% and 53%, respectively. While the LDPE bags could be used for up to 12 weeks of SODIS without too much reduction in UVA transmittance, the PVC boxes should be replaced after 4 weeks, or at most 8 weeks.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".