X‐ray photoelectron spectroscopy and time‐of‐flight secondary ion mass spectrometry characterization of aging effects on the mineral fibers treated with aminopropylsilane and quaternary ammonium compounds
Bibliographic record
Abstract
X‐ray photoelectron spectroscopy (XPS) and time‐of‐flight secondary ion mass spectrometry were used to investigate the aging effects on the aminopropylsilane (APS) and quaternary ammonium surfactant‐treated mineral fibers. APS‐coated mineral fiber samples were treated with cationic surfactant and mineral oil and aged at 70 °C temperature and 95% humidity. From quantitative XPS measurements, an increase in the atomic composition of oxygen, nitrogen, and silicon is observed after aging. An increase in the protonated amino groups in the N1s high‐resolution spectra and C–N group in the C1s high‐resolution spectra is also observed. These results indicate that the concentration of hydrocarbon groups decreases after aging due to the partial removal of the long hydrocarbon chains of the surfactant and mineral oil and/or hydrolysis and segregation of APS to the fiber surface. The principal component analysis (PCA) was applied to the time‐of‐flight secondary ion mass spectrometry spectra, and an increase in the intensities of APS characteristic peaks were observed after aging. The observed increase in the signals of APS originates from underlying silanized fibers after the removal of the surfactant and mineral oil from the surface. Copyright © 2012 John Wiley & Sons, Ltd.
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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".