Micro-Ring Resonator-Based Sensors for Detection of Different Chemicals

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Amna Bedi ◽  
Sonika Singh ◽  
Santosh Kumar ◽  
Brajesh Kumar Kaushik

AbstractThe sensing of different liquids is investigated with micro-ring resonator (MRR) sensor by changing refractive index (RI) of chemical solutions. Aniline, carbon disulphide, chlorobenzene, chloroform, ethanol, glycerin, and methanol are detected using the proposed MRR. The developed structures are simulated using finite difference-time domain (FDTD) by using DFT analyzer of optical field. The normalized amplitude vs. wavelength is measured by changing RI of inner ring waveguide that obtain liquid sensor with high sensitivity.

2014 ◽  
Vol 2014 ◽  
pp. 1-6 ◽  
Author(s):  
Sheng Hsiung Chang ◽  
Kuen-Feng Lin ◽  
Chien-Hung Chiang ◽  
Sheng-Hui Chen ◽  
Chun-Guey Wu

The refractive index and extinction coefficient of a triiodide perovskite absorber (TPA) were obtained by fitting the transmittance spectra of TPA/PEDOT:PSS/ITO/glass using the transfer matrix method. Cu nanoplasmonic structures were designed to enhance the exciton generation in the TPA and to simultaneously reduce the film thickness of the TPA. Excitons were effectively generated at the interface between TPA and Cu nanoparticles, as observed through the 3D finite-difference time-domain method. The exciton distribution is advantageous for the exciton dissociation and carrier transport.


2019 ◽  
Vol 33 (03) ◽  
pp. 1950017 ◽  
Author(s):  
Fang Chen ◽  
Jijun Li

In this paper, a refractive index and temperature sensor based on Fano resonance is realized. The proposed structure is composed of a MIM waveguide and a defect cavity which is filled with sealed ethanol. The Fano spectra and field distribution is numerically investigated by the two-dimensional finite-difference time-domain (FDTD) method. Due to the symmetry breaking, the sharp and asymmetric transmission spectra can be used as a sensor with high sensitivity. The sensitivity of the proposed structure can be up to 652 nm/RIU and [Formula: see text]. Because of the high sensitivity, the proposed plasmonic structure may have potential application in nanosensing.


2021 ◽  
Author(s):  
Hossain Zadhoush ◽  
Antonios Giannopoulos ◽  
Iraklis Giannakis

<p>The estimation of the bulk permittivity of heterogeneous mixtures is of great interest for many Ground Penetrating Radar (GPR) and electromagnetic sensing applications [1], [2]. The most used method for estimating the bulk permittivity is the Complex Refractive Index Model (CRIM). The simplicity of this method is one its advantages however, the accuracy of the permittivity estimation has not been tested. Here, the CRIM model’s shape factor is examined and optimised in order to achieve a more accurate concrete bulk permittivity estimation. The concrete components are aggregate particles, cement particles, air-voids and moisture content; and they are randomly distributed with different volume percentages to produce various combinations. These combinations are modelled using the Finite-Difference Time-Domain (FDTD) method as it is an accurate and computationally efficient method [3]. The numerical modelling is then used to predict the bulk permittivity allowing to fine-tune CRIM model’s shape factor. The models are modelled in 3D and a GSSI-like antenna structure is used as the transmitting source [4]. The permittivity estimation uses an accurate time-zero method, which increases the accuracy of the estimated bulk permittivity hence, the shape factor [5], [6]. The results have shown that the optimised CRIM model over-performs the original CRIM model shape factor therefore, a better and more accurate bulk permittivity estimation is achieved for concrete mixtures.</p><p> </p><p><strong>References </strong></p><p>[1] Daniels, D. J., (2004), Ground Penetrating Radar, 2nd ed. London, U.K., Institution of Engineering and Technology.</p><p>[2] Annan, A. P., (2005), Ground Penetrating Radar,  in Investigations in Geophysics, Society of Exploration Geophysicists, pp. 357-438.</p><p>[3] Taflove, A., Hagness, S. C., (2005), Computational electromagnetic: The Finite-Difference Time-Domain Method, Artech House, Norwood.</p><p>[4] Warren, C., & Giannopoulos, A., (2011), Creating Finite-Difference Time-Domain Models of Commercial Ground Penetrating Radar Antenna Using Taguchi’s Optimization Method, Geophysics, 76(2), G37-G47.</p><p>[5] Zadhoush, H., Giannopoulos, A., Giannakis, I., (2020), Optimising GPR time-zero adjustment and two-way travel time wavelet measurement using a realistic 3D numerical model, Near Surface Geophysics, Under review (Minor revisions).</p><p>[6] Zadhoush, H., (2020), Numerical Modelling of Ground Penetrating Radar for Optimization of the Time-zero Adjustment and Complex Refractive Index Model, PhD Thesis Submitted at The University of Edinburgh.</p>


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