Fabrication and Characterisation of Amine‐Rich Organic Thin Films: Focus on Stability
Bibliographic record
Abstract
Abstract Thin films, rich in primary amines (CNH2), were deposited from nitrogen (N2) or ammonia (NH3) and ethylene (C2H4) with different gas mixture ratios, R, using three different methods: atmospheric‐pressure‐ or low‐pressure plasma polymerisation (PP), and vacuum‐ultraviolet photo‐polymerisation. They are designated H‐plasma‐polymerised ethylene (PPE):N, L‐PPE:N and ultraviolet‐polyethylene (UV‐PE):N, respectively. Of interest in cell‐culture and tissue engineering, all three coating‐types were examined with regard to stability in air and solubility in water, compared with other deposits in the literature that were obtained from single precursors such as allylamine (AA) or n‐heptylamine (HA), PP‐AA and PP‐HA, respectively. The three types of deposits, prepared using comparable R values, were characterised by X‐ray photoelectron spectroscopy, Fourier transform infrared spectroscopy, scanning electron microscopy and atomic force microscopy and found to vary significantly among themselves in regard to their [N]‐ and [NH2] concentrations, and their chemical stabilities during long‐term exposures to air or aqueous solvents. UV‐PE:N and L‐PPE:N films were found to compare very favourably with their best PP‐AA and PP‐HA counterparts; we conclude that the additional important fabrication parameter (the gas mixture ratio, R) is a major asset for preparing stable NH2‐rich organic coatings with optimal properties. magnified image
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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".