Leachate chemical composition effects on OIT depletion in an HDPE geomembrane
Bibliographic record
Abstract
Results of series of tests examining the effect of different chemical constituents found in municipal solid waste leachate on the degradation of a high-density polyethylene (HDPE) geomembrane are reported. Geomembrane samples were incubated in four synthetic leachates consisting of different combinations of volatile fatty acids, inorganic nutrients, trace metal solution, and surfactant at temperatures of 85°C, 70°C, 55°C, 40°C and 22°C. It is shown that the leachate should be replaced every two weeks to maximise the depletion of antioxidants from the geomembrane. Arrhenius modelling gave activation energies for antioxidant depletion of between 62.5 and 64.0 kJ/mol. The small difference in activation energies implies that the four leachates examined are similar in terms of antioxidant depletion rate. There was no evident effect of the difference in these leachates on crystallinity, MFI, or tensile properties during the testing period. However, the fastest antioxidant depletion was observed for the simplest leachate, comprising trace metals and surfactant in water. Results are also reported for a second series of tests involving 18 different immersion media with different concentrations of trace metals and surfactant. Based on an examination of solutions with pH between 4 and 10, it is found that antioxidant depletion is the fastest for relatively acidic or basic solutions and the slowest for neutral solutions. Antioxidant depletion is the most sensitive to the presence of surfactant. As the surfactant concentration increases to about 1 ml/l the majority of the effect is evident. There was no further increase in effect for any increase in concentration beyond 5 ml/l.
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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) | 0.000 | 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) | 0.001 | 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".