Project Operator National Chung Hsing University
Project Host 薛富盛
"We develop a silicon dioxide hollow material/polyimide composite film with a low dielectric constant of 2.8~3.0reduce the weight by 30. After the metallization of the composite film, the mechanical properties are highly stablethe transmission loss of circuit can be reduced by 30 at 2838 GHz, which is beneficial to the applications of 5G technology.
 Besides the 5G demands, we also develope a body kinetic energy recoveryenvironmental electromagnetic wave recovery device, which can self-chargesupply power. By Using machine learning predictionclustering techniques to assist the experimental process, we can find the best parameters. In addition, we use distributed computing to speed up the computing process."
Scientific Breakthrough
The agglomeration of nanometer-scale inorganic additives is addressed, while the silica hollow spheresthe silica hollow tubes are well-dispersed in the as-fabricated polyimide composite film. Importantly, its inherent low dielectric constant can be well-reserved. The surface process keeps the film adhesion stable beforeafter thermal testing. Composite elements can recover body kinetic energy, environmental electromagnetic radiation,sense pressure. Its characteristics such as lightness, thinness,high sensitivity have advantages in development. By using experimental data to train a machine learning model, the model uses known data to estimate simulation results.
Industrial Applicability
Inspired by the toucan beak, the composite films with low densitieslow dielectric can serve as potential candidates for a wide range of 5Gcloud computing technological applications. The surface process provides high adhesion stability of the filmimproves product life. The two energy-harvesting technologies can convert biomechanical energyambient EM energy to available electricity for the use in self-powered flexible electronicsIOT devices, offering the potential for self-sufficiency, as are the advantages of low costlarge-area fabrication. The predictionclustering technology can assist material mixing problems to estimate the parameters.
Keyword Biomimetic Material Porous Nanocomposite Polyimide Composite Low Dielectric Constant Material Low Transmission Loss Material 5G Flexible Substrate Self-generated Energy Storage Device Wearable Device Machine Learning Distributed Computing
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  • Tzong-Ming Wu
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