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Related Concept Videos

Susceptibility, Permittivity and Dielectric Constant01:26

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When placed in an external electric field, a dielectric material gets polarized. The charge density in the dielectric material is given by the sum of the bound and free charge densities, while the total charge density can also be written in terms of the total electric field. The bound charge density can be measured in terms of polarization, leading to the relationship between electric displacement and polarization.
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Shock Waves01:16

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While deriving the Doppler formula for the observed frequency of a sound wave, it is assumed that the speed of sound in the medium is greater than the source's speed through it. When this condition is breached, a shock wave occurs.
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The presence of a dielectric medium in a capacitor not only changes the voltage and capacitance but also affects the electric field. In general, dielectrics can be of two types: polar and nonpolar. In a polar dielectric, the positive and negative charges in the molecules are separated by a distance and hence have a permanent dipole moment. In contrast, no such charge separation exists in a nonpolar dielectric, however the nonpolar molecules get polarized in the presence of an external electric...
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Parallel plate capacitors consist of two conducting plates separated by a certain distance. However, it is mechanically difficult to hold the large plates parallel to each other without actual contact. Hence, a dielectric layer is commonly placed between the plates, which provides an easy solution for holding the plates together with a small gap and increases the capacitance of the capacitor.
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When an electric field passes from one homogeneous medium to another, crossing the boundary between the two mediums imparts a discontinuity in the electric field. This results in electrostatic boundary conditions that depend on the type of mediums the field propagates through.
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Electromagnetic Waves in Matter01:30

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Electromagnetic waves can travel in the vacuum as well as in matter. For example light, which is an electromagnetic wave, can travel through air, water, or glass.
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Updated: Jul 23, 2025

Using Microwave and Macroscopic Samples of Dielectric Solids to Study the Photonic Properties of Disordered Photonic Bandgap Materials
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Shock Properties Characterization of Dielectric Materials Using Millimeter-Wave Interferometry and Convolutional

Jérémi Mapas1, Alexandre Lefrançois1, Hervé Aubert2

  • 1CEA-DAM, GRAMAT, BP80200, F-46500 Gramat, France.

Sensors (Basel, Switzerland)
|July 11, 2023
PubMed
Summary

A neural network improves shock wave and particle velocity estimation in dielectric materials using millimeter-wave interferometry. This method offers more accurate results, particularly for short-duration waveforms.

Keywords:
convolutional neural networkmetrologymm-wave interferometryparticle velocityshock permittivityshock propertiesshock refractive indexshock velocity

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Area of Science:

  • Electromagnetics
  • Materials Science
  • Wave Propagation

Background:

  • Shock impacts generate waves in dielectric materials, altering their refractive index.
  • Millimeter-wave interferometry can remotely measure shock parameters via Doppler frequencies.
  • Accurate characterization of shock phenomena is crucial for material science applications.

Purpose of the Study:

  • To apply a neural network approach for solving electromagnetic inverse problems.
  • To enhance the estimation accuracy of shock wavefront and particle velocities.
  • To investigate the effectiveness of neural networks for short-duration waveform analysis.

Main Methods:

  • Utilizing a convolutional neural network (CNN) for data analysis.
  • Employing millimeter-wave interferometry to capture waveform data.
  • Training the CNN on characteristic Doppler frequencies from shocked materials.

Main Results:

  • The neural network approach provides more accurate estimations of shock wavefront and particle velocities.
  • The method demonstrates particular effectiveness for short-duration waveforms (microseconds).
  • Improved remote sensing of material response under shock impact.

Conclusions:

  • Convolutional neural networks offer a powerful tool for analyzing complex electromagnetic inverse problems.
  • This technique advances the remote characterization of materials under dynamic shock conditions.
  • The study highlights the potential of AI in high-speed material diagnostics.