Optical sensors for the validation of electromagnetic field distributions in biological phantoms

Author(s):  
Franjo Cecelja ◽  
Bala Balachandran ◽  
Michael Berwick ◽  
Manook Soghomonian ◽  
Srboljub R. Cvetkovic
2013 ◽  
Vol 38 (12) ◽  
pp. 2065 ◽  
Author(s):  
Rosario Martínez-Herrero ◽  
Ignasi Juvells ◽  
Artur Carnicer

Sensors ◽  
2019 ◽  
Vol 19 (13) ◽  
pp. 2860 ◽  
Author(s):  
Jun Peng ◽  
Shuhai Jia ◽  
Jiaming Bian ◽  
Shuo Zhang ◽  
Jianben Liu ◽  
...  

Electromagnetic field sensors are widely used in various areas. In recent years, great progress has been made in the optical sensing technique for electromagnetic field measurement, and varieties of corresponding sensors have been proposed. Types of magnetic field optical sensors were presented, including probes-based Faraday effect, magnetostrictive materials, and magnetic fluid. The sensing system-based Faraday effect is complex, and the sensors are mostly used in intensive magnetic field measurement. Magnetic field optical sensors based on magnetic fluid have high sensitivity compared to that based on magnetostrictive materials. Three types of electric field optical sensors are presented, including the sensor probes based on electric-optic crystal, piezoelectric materials, and electrostatic attraction. The majority of sensors are developed using the sensing scheme of combining the LiNbO3 crystal and optical fiber interferometer due to the good electro-optic properties of the crystal. The piezoelectric materials-based electric field sensors have simple structure and easy fabrication, but it is not suitable for weak electric field measurement. The sensing principle based on electrostatic attraction is less commonly-used sensing methods. This review aims at presenting the advances in optical sensing technology for electromagnetic field measurement, analyzing the principles of different types of sensors and discussing each advantage and disadvantage, as well as the future outlook on the performance improvement of sensors.


2021 ◽  
Author(s):  
Mingkun Chen ◽  
Robert Lupoiu ◽  
Chenkai Mao ◽  
Der-Han Huang ◽  
Jiaqi Jiang ◽  
...  

Abstract The calculation of electromagnetic field distributions within structured media is central to the optimization and validation of photonic devices. We introduce WaveY-Net, a hybrid data- and physics-augmented convolutional neural network that can predict electromagnetic field distributions with ultra fast speeds and high accuracy for entire classes of dielectric photonic structures. This accuracy is achieved by training the neural network to learn only the magnetic near-field distributions of a system and to use a discrete formalism of Maxwell's equations in two ways: as physical constraints in the loss function and as a means to calculate the electric fields from the magnetic fields. As a model system, we construct a surrogate simulator for periodic silicon nanostructure arrays and show that the high speed simulator can be directly and effectively used in the local and global freeform optimization of metagratings. We anticipate that physics-augmented networks will serve as a viable Maxwell simulator replacement for many classes of photonic systems, transforming the way they are designed.


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