Preparation of Electrospun Nanocomposite Nanofibers of Polyaniline/Poly(methyl methacrylate) with Amino-Functionalized Graphene
Bibliographic record
Abstract
In this paper we report upon the preparation and characterization of electrospun nanofibers of doped polyaniline (PANI)/poly(methyl methacrylate) (PMMA)/amino-functionalized graphene (Am-rGO) by electrospinning technique. The successful functionalization of rGO with amino groups is examined by Fourier transforms infrared (FTIR), X-ray photoelectron spectroscopy (XPS) and Raman microspectrometer. The strong electric field enables the liquid jet to be ejected faster and also contributes to the improved thermal and morphological homogeneity of PANI/PMMA/Am-rGO. This results in a decrease in the average diameter of the produced fibers and shows that these fibers can find promising uses in many applications such as sensors, flexible electronics, etc.
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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".