Diffusion of sulfuric acid solutions in Nylon 6,6 monitored by neutron activation analysis
Bibliographic record
Abstract
Abstract Nylon 6,6 is an excellent material for the study of the diffusion mechanism and associated mechanical performance of polymers saturated with aqueous solutions of varying pH at different temperatures. The diffusion profile was studied for samples saturated at temperatures ranging from 20 to 90°C in solutions decreasing in pH from distilled water to 1.0M sulfuric acid. The presence of sulfuric acid molecules within the diffusing solutions acts to promote hydrolysis of the polyamide molecules. The degree of hydrolysis is dependent on saturation temperature and solution pH. The extent of degradation was evaluated via changes to mechanical performance and inherent viscosity and often results in a reduction of the stress at yield, flexural modulus, and inherent viscosity on increasing temperature and decreasing pH. The use of neutron activation analysis allowed for an evaluation of the sulfur content within the samples as a function of diffusing time. This demonstrated that although the mechanical performance decreases rapidly on initial exposure to the aqueous medium, this is likely due to plasticization. As diffusion time progresses, the sulfur content within the sample continues to rise to a level where the acid/water molar ratio is much higher in the sample than that of the bulk. This results in an enhancement of the degradation process as time progresses. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci 97: 2476–2487, 2005
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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".