Silicon-based Mid Infrared On-Chip Gas Sensor Using Fano Resonance of Coupled Plasmonic Microcavities

Sherif, Sherif M.; Swillam, Mohamed A.

doi:10.21203/rs.3.rs-2049865/v1

Cited by 4 publications

(6 citation statements)

References 23 publications

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“…The reflection spectrum will exhibit a very sharp drop for this specific wavelength. The resonance wavelength is very sensitive to changes of the effective index, which is very sensitive to changes of the refractive index of the surrounding medium [15][16][17][18][19][20][21][22][23] .…”

Section: Methodsmentioning

confidence: 99%

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High sensitivity meta-surface plasmonic sensor

Mahmoud,

Maher,

Ghanim

et al. 2024

Silicon Photonics XIX

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Surface Plasmon Polariton resonant sensors (SPPs) have found wide-ranging applications, particularly for nanoscale sensing. The SPP dispersion is determined by the properties of a limited number of suitable metals and cannot be arbitrarily tuned. The proposed gas sensor is based on surface plasmon polariton manipulated in the metamaterial surface. The plasmonic sensor utilizes a metal-air interface to detect and analyze various substances and phenomena in the mid-infrared range. The utilization of the Mid-infrared (MIR) wavelength range offers numerous benefits across a wide range of applications, including chemical and biological detection. This paper introduces a metasurface composed of highly doped silicon that demonstrates a plasmonic effect in the mid-infrared wavelength range. Silicon has several benefits, including compatibility with CMOS technology and easy manufacturing utilizing traditional silicon fabrication techniques. In addition, operating in the mid-infrared (mid-IR) range and using doped silicon material enables the development of integrated plasmonic devices at the microscale. In this paper, a meta surface plasmonic grating is proposed for sensing and detecting the refractive index changes. In order to test the performance of the plasmonic sensor, a commercial Lumerical software based on finite difference time domain (FDTD) has been used. The suggested design shows high sensitivity at λ = 13.9807 μm and it can be used for gas sensing applications.

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Section: Methodsmentioning

confidence: 99%

“…In this paper, we demonstrate the response of light with our design in the mid-infrared wavelength range (10 μm-16 μm) by optimization of the reflected wave. The metasurface is based on doped silicon which acts like a metal in mid-infrared [9][10][11][12][13][14][15] .…”

Section: Introductionmentioning

confidence: 99%

High sensitivity meta-surface plasmonic sensor

Mahmoud,

Maher,

Ghanim

et al. 2024

Silicon Photonics XIX

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“…At resonance, the undamped oscillator shows an abrupt π phase shift, while the strongly damped oscillator shows a slow phase change introducing a broad spectral line. Fano spectral resonance has been realized in various con gurations such as photonic crystals 34,25 , microcavities 35 , dielectric cylinders 36 , dielectric spheres 37 , and metasurfaces 31 . The periodic con gurations such as the photonic crystals and metasurfaces demonstrate narrower spectral lines compared to the single resonators.…”

Section: ∼ 400cmentioning

confidence: 99%

Silicon based Double Fano resonances photonic integrated gas sensor

Salama,

Alexeree,

Obayya

et al. 2024

Preprint

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The telecommunication wavelengths play a crucial role in the development of photonic integrated circuit (PIC). The absorption fingerprints of many gases lie within these spectral ranges, offering the potential to create miniaturized gas sensor for (PIC). In this work, we present novel double Fano resonances within the telecommunication wavelength range, based on silicon metasurface for selective gas sensing applications. Our proposed design comprises periodically coupled nanodisk and nano-bar resonators mounted on a quartz substrate. We show that the Fano resonances can be precisely tuned across the wavelength range from (𝜆=1.52𝜇m) to (𝜆=1.7𝜇m) by adjusting various geometrical parameters. Furthermore, we optimize the sensor for double detection of carbon monoxide (CO), with an absorption fingerprint at ~ 1.566 𝜇m, and nitrous oxide (N2O), with an absorption fingerprint at ~ 1.67𝜇m. The sensor exhibits exceptional refractometric sensitivity to CO of 1,735 nm/RIU with an outstanding FOM of 11,570. In addition, the sensor shows a sensitivity to N2O of 194 accompanied by a FOM of 510. The structure reveals absorption losses of 7% for CO and 3% for N2O. The outstanding FOM and absorption losses provide selectivity for the sensing material. Our proposed design holds significant promise for the development of highly sensitive double detection refractometric photonic integrated gas sensor.

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“…The utilization of the silicon-on-insulator (SOI) platform is extensive in the field of photonics due to its remarkable waveguiding proficiencies facilitated by the high refractive index of silicon (Si) in contrast to the low refractive index of silicon dioxide (SiO2) 12 . 3 Moreover, SOI is highly recommended for its compatibility with complementary metal-oxide-semiconductor (CMOS) technology and its ease of fabrication. Integrated photonics has garnered significant interest thanks to its versatile applications in various domains.…”

Section: Introductionmentioning

confidence: 99%

Convolutional neural networks for temperature robust medium chemical concentration detection with micro-ring resonators

Mikhail,

Shafaay,

Swillam

2024

Smart Photonic and Optoelectronic Integrated Circuits 2024

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An approach to measuring chemical concentrations using a micro-ring resonator (MRR) is proposed which is robust to thermo-optic noise and spectral shifts caused by temperature changes. The method uses a modified ResNet50 with varied kernel size and achieved a mean-square error (MSE) of 4.548E-4, and performance is compared to other machine learning methods including VGG20 and XGBoost. The model was trained to read the transmission spectra of a slotted MRR etched into heavily doped silicon and output the concentrations of chemicals in the surrounding analyte. The chemicals tested on were water, ethanol, methanol, and propanol, with concentrations ranging from 0-100%, with a dataset containing . This occurs over the mid-infrared wavelengths and within the temperature range of 290-310 K. Transfer learning was also utilized to retrain the models on several other datasets, consisting of 528 transmissions each. These datasets operated over different temperature ranges (310-320), and the other with a different set of chemicals, (water, ethanol, methanol and butanol). Similar results were achieved, with both networks achieving similar MSE. We then perform the same process on another design with the same chemicals, also operating over the infrared range, demonstrating the robustness of the method. All datasets used in the study were obtained through simulation, although we hope to test on real data.

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Silicon-based Mid Infrared On-Chip Gas Sensor Using Fano Resonance of Coupled Plasmonic Microcavities

Cited by 4 publications

References 23 publications

High sensitivity meta-surface plasmonic sensor

High sensitivity meta-surface plasmonic sensor

Silicon based Double Fano resonances photonic integrated gas sensor

Convolutional neural networks for temperature robust medium chemical concentration detection with micro-ring resonators

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