Effect of Surface Fluorination on Diffusion through a High Density Polyethylene Geomembrane
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The relative improvement of the diffusive barrier function of high density polyethylene (HDPE) geomembranes to volatile organic compounds (VOCs) when subjected to surface fluorination is experimentally examined. The surface fluorination consisted of applying elemental fluorine, which exchanged with hydrogen along polymer chains at the surface of a polyolefin substrate. Sorption and diffusion tests were performed on both traditional “untreated” and “fluorinated” 1.5mm HDPE geomembranes using dilute aqueous organic contaminants commonly found in municipal solid waste leachate. The partitioning coefficient is shown to remain essential the same after the surface fluorination; however, the surface fluorination resulted in a reduction in both the diffusion and the permeation coefficients by factors ranging between 1.5 and 4.5, depending on the hydrocarbon examined. Modeling of VOC diffusion through a geomembrane/compacted clay composite liner indicated that contaminant impacts were about 1.7–2.9 times lower when a fluorinated geomembrane is used. To achieve the same level of protection as provided by the fluorinated geomembrane underlain by 0.60m of compacted clay, one would need an additional 0.4–0.9m of compacted clay in conjunction with a conventional (untreated) geomembrane. The importance of the thickness of the treated layer is highlighted.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it