Probing the Surface Chemistry of a Hydrated Segmented Polyurethane and a Comparison with Its Dry Surface Chemical Structure
Bibliographic record
Abstract
A biochemical approach has been used to analyze the surface chemistry of a hydrated polyester−urea−urethane. Using an enzyme-catalyzed hydrolysis reaction, the surface chemistry of the polyurethane was probed by having the enzyme remove the polymer chain components making up the surface. The surface-derived products were analyzed using high performance liquid chromatography (HPLC), and product identification was carried out by mass spectrometry. The qualitative and quantitative analysis of the removed surface-derived products provided the necessary information required to reconstruct the chemistry of the hydrated polymer surface. The results indicated that urethane and urea linkages were present on the hydrated surface. However, their concentrations were lower than in the bulk polymer. In addition, the ratio of urea to urethane groups was substantially reduced at the hydrated surface relative to the bulk polymer stoichiometry. The data obtained for the hydrated surface were also compared to the analysis of the dry surface, carried out using X-ray photoelectron spectroscopy (XPS). The hydrated polymers contained higher urethane and ester groups than that shown on the dry surface. While XPS was able to identify the presence of urethane linkages on the dry surface, these could not be accurately quantified. Furthermore, the content of urea linkages could not be specifically determined by XPS because they were masked by the ester groups.
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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".