Chemical oxidation of <scp>high‐density</scp> polyethylene: Surface energy, functionality, and adhesion to liquid epoxy
Bibliographic record
Abstract
Abstract The application of polyolefins has increased significantly over the past few decades. However, their chemical inertness and low surface energy limits their application in many industries where high adhesion to polar materials is required, such as for composites and protective coatings. Herein, six different acids are used to create polar functional groups on High‐Density Polyethylene's (HDPE) surface and to increase its adhesion to liquid epoxy (LE). Contact angle measurements, Fourier Transform Infrared Spectroscopy (FTIR), X‐ray Photoelectron Spectroscopy (XPS), and pull‐off strength measurements are used to analyze the surface energy and functionality of HDPE and to measure its adhesion to LE. The results show that each acid increases both the polar and disperse surface energies of HDPE to a different extent, but that this is not necessarily a function of acid strength. Chlorosulfonic acid and chromic acid increase the oxygen to carbon ratio by a factor of 8 and increase HDPE's adhesion to LE by more than 400%. Furthermore, a comparison between predicted work of adhesion values from the OWRK model and experimental results shows that the latter are significantly higher than what is predicted, especially with increasing surface polarity.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".