ToF‐SIMS multivariate characterization of surface modification of polymers by N <sub>2</sub> H <sub>2</sub> atmospheric pressure dielectric barrier discharge
Bibliographic record
Abstract
Abstract Time of flight secondary ion mass spectrometry (ToF‐SIMS) is a powerful tool for the surface characterization of plasma‐modified surface. However, the SIMS fragmentation patterns of the resulting surface are quite complex and a full interpretation may be prohibitive. As a result, many studies are turning to multivariate statistical methods to simplify the interpretation. In this study, a principal component analysis (PCA) was used to obtain a more detailed interpretation of the surface modification of polymers by an atmospheric pressure plasma. The dataset was obtained from three polymers with different chemical compositions [namely, polyethylene, polyvinylidene fluoride, and poly(tetrafluoroethylene)], where each material was treated with an atmospheric pressure dielectric barrier discharge (DBD) in an atmosphere composed of different N 2 /H 2 ratios. The results are discussed in terms of the suitability of ToF‐SIMS analysis combined with PCA for the discrimination between the three polymers and the possibility to create a predictive model that would describe the plasma surface modification, independent of the polymer substrate chemical composition. Copyright © 2010 John Wiley & Sons, Ltd.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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".