Microwave plasma activation of a polyvinylidene fluoride surface for protein immobilization
Bibliographic record
Abstract
Polyvinylidene fluoride (PVDF) was modified by CO2, N2 or N2/H2 plasmas, which permitted the attachment of short carboxyl or amino groups. A variation of the discharge parameters was performed, for their optimization, as well as for minimizing degradation in favour of acidic, amphiphilic or basic functionalization, respectively. The optimum parameters of discharge for CO2, N2 or N2/H2 plasmas were P = 50 W, gas flow rate Q = 16 × 10−8 m3 s−1, exposure time t = 30–60 s, d = 0.1 m, pressure 15 Pa. The new surfaces were characterized by wettability measurements, attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR), x-ray photoelectron spectroscopy (XPS) and atomic force microscopy (AFM) methods. In a second step, the proteins (triglycine (TG) and protein A) were adsorbed or chemically grafted onto the carboxyl or amino functionalized surface, after EDC/NHS (1-ethyl-3-(-dimethylaminopropyl) carbodiimide/N-hydroxysuccinimide) activation of proteins. ATR-FTIR, XPS and AFM investigations confirmed the presence of protein on the surface. The XPS C1s core levels at 286.3 eV (C–N), 288 eV (amide bond) and 298 eV (carboxylic acid), together with variation of the O1s and N1s signals, illustrated the immobilization of proteins. It was established that TG was better attached on surfaces activated with N2/H2 plasma, while protein A was more tightly anchored on CO2, N2 plasma-activated surfaces. The former procedure allowed higher surface densities, while the latter permitted a better chemical control. The results proved that plasma-treated PVDF is a good substrate for protein coating, which can be further used for microorganisms' detection, as evidenced by the immunoassay test.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.002 | 0.001 |
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".