Improving Electromagnetic Shielding of Composite Structures with Metallic Nanoparticles Synthesized by Electrochemical Discharges
Bibliographic record
Abstract
The aeronautic industry has started to replace the weighty metallic parts of aircrafts by Polymer Matrix Composites (PMCs) due to cost and environmental issues. However, PMCs have the disadvantage of having a very low electromagnetic (EM) shielding property compared to metals. To increase the EM shielding properties of composites there are both traditional methods (co-cured metallic foil, Electroless, Conductive paint and Vacum metalizing) as well as new alternatives mainly through the use of nanoparticles. Nanoparticles can be applied in a number of different ways within a composite material to increase its EM shielding such as using a thin coating on a fibre, in place of a bundle of fibres, as an inner layer, as well as a coating, or as a part of the polymer resin system have been proposed. Here we propose a new, uncomplicated, inexpensive method of EM shielding with metallic nanoparticles synthesized by electrochemical discharges, which can be potentially integrated easily to the traditional techniques of composite fabrication. Our system contains an electrode, a counter electrode, aqueous electrolyte containing salt of desired nanoparticles and a DC power supply. Over a critical cell terminal voltage the creation of gas film is possible around the working electrode. Electrical discharges occur between the gas film and the surrounding electrolyte. The metallic ions inside the solution are locally reduced to metallic nanoparticles (typically 10-150nm). The formation of the gas film has a key role in the process by preventing the metallic ions from setting down on electrode. The solution containing the particles will be dried and then deposited on carbon mesh which will be used later in traditional composite fabrication. The result of EM shielding (range of 30MHz to 1.5 GHz) with this method is discussed. Also the possibility of creation of carbon nanotubes during the process has been presented.
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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) | 0.000 | 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 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".