Synthesis and characterization of silver nanowires with high aspect ratio for transparent coating applications
Bibliographic record
Abstract
In this study, the polyol method was used for the synthesis of AgNWs for the preparation of transparent and conductive coatings. The aim is to synthesize silver nanowires with a one-dimensional morphology and a diameter of less than 100 nm and to formulate a conductive ink containing silver nanowires with high stability under environmental conditions and an easy synthesis method. The experimental design and determination of random samples were performed using Design Expert software. In general, three variables of polyvinyl pyrrolidone (PVP) in the range of 0.06–0.8 g, silver nitrate precursor in the range of 0.04-2.64 g, and the molar ratio of PVP to silver nitrate were selected, and the constants were reaction temperature, reaction time, solvent (EG), and mixing rate. random samples, proposed by the software, were examined. The synthesized AgNWs were characterized and evaluated using X-ray diffraction (XRD), field emission scanning electron microscopy (FE-SEM), scanning electron microscopy (SEM), and Fourier transform infrared analysis. (FT-IR), and DRS analysis used the Light transmittance coefficient. According to the results of XRD, FE-SEM, and SEM analyses, among the eight samples, S8 had a minimum diameter of 77.3 nm and an average length of 750 nm, and it was selected for further research. Then, the production of conductive ink was put on the agenda, eight conductive inks were made, and the optimal sample (S8) was identified at 3.75% by weight and the optimal molar ratio for ethanol and ethylene glycol solvents. The optimal ink was characterized and evaluated using visible-ultraviolet (UV-Vis), simultaneous thermal (TGA-DTA), and FE-SEM spectroscopic analyses. Conductive ink was then applied to the glass substrate. In addition, the EMI shielding efficiency in terms of (dB) using the surface electrical resistance of the conductive ink applied to the S5 sample was found to be 75.17 dB in the best case. Finally, the electrical resistance, transparency, and EMI shielding efficiency of the S8 sample were obtained as (2.8 Ω), (77%) and (44.35 dB).
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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) | 0.000 | 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 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".