Parametric Study of Microwave Absorption in Lossy Dielectric Slabs

Huynen, Isabelle

doi:10.5121/jmicro.2016.1401

Cited by 1 publication

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References 7 publications

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“…The performance of polymer-nanofiller composites to block electromagnetic (EM) radiation is evaluated from measuring a physical electromagnetic absorption index property using S-parameters procedure; these parameters have been extracted from a highly sensitive powerful instrument, namely, a vector network analyzer (VNA). This machine utilizes the concept of measuring the transmitted and reflected waves as a signal passes through a device under test [11]. This measurement method is used on a large scale of recent research; it is considered as a shorthand way to identify the absorption index over large selective frequencies based on S-parameters [12,13].…”

Section: Introductionmentioning

confidence: 99%

Simulation and Optimization of Electromagnetic Absorption of Polycarbonate/CNT Composites Using Machine Learning

et al. 2020

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Electronic devices that transmit, distribute, or utilize electrical energy create electromagnetic interference (EMI) that can lead to malfunctioning and degradation of electronic devices. EMI shielding materials block the unwanted electromagnetic waves from reaching the target material. EMI issues can be solved by using a new family of building blocks constituted of polymer and nanofillers. The electromagnetic absorption index of this material is calculated by measuring the “S-parameters”. In this article, we investigated the use of artificial intelligence (AI) in the EMI shielding field by developing a new system based on a multilayer perceptron neural network designed to predict the electromagnetic absorption of polycarbonate-carbon nanotubes composites films. The proposed system included 15 different multilayer perception (MLP) networks; each network was specialized to predict the absorption value of a specific category sample. The selection of appropriate networks was done automatically, using an independent block. Optimization of the hyper-parameters using hold-out validation was required to ensure the best results. To evaluate the performance of our system, we calculated the similarity error, precision accuracy, and calculation time. The results obtained over our database showed clearly that the system provided a very good result with an average accuracy of 99.7997%, with an overall average calculation time of 0.01295 s. The composite based on polycarbonate−5 wt.% carbon nanotube was found to be the ultimate absorber over microwave range according to Rozanov formalism.

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Section: Introductionmentioning

confidence: 99%