Battery-Free, Artificial Neural Network-Assisted Microwave Resonator Array for Ice Detection

Niksan, Omid; Colegrave, Keatin; Zarifi, Mohammad H.

doi:10.1109/tmtt.2022.3222194

Cited by 21 publications

(5 citation statements)

References 55 publications

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“…Split-ring resonators (SRRs) are a class of microwave devices that have contributed significantly to the development of contactless, inexpensive, reusable, and real-time microwave sensors. − SRRs consist of metal traces that support electromagnetic waves with a specific resonant frequency. − Materials can be detected, characterized, and classified by translating their electromagnetic interaction with the microwave signal into changes in the sensor’s electrical parameters, such as resonant amplitude, resonant frequency, and quality factor (Q-factor). ,− Recently, microwave sensors have gained significant attention for sensing frost and ice due to the large difference between the dielectric properties of ice and water. , Planar SRRs integrated with microfluidic channels have also enabled read-time noncontact and nonintrusive detection of microbial growth, blood glucose level, and liquid mixtures at low sample volumes, with applications in microbiology, pharmaceutical, and wastewater treatment facilities . Furthermore, implementation of radio and microwave frequency devices as sensors helps enable their use in the digital world via wireless operation, smart sensing, and Internet of Things (IoT) integration. , …”

Section: Introductionmentioning

confidence: 99%

Gigahertz-Based Visible Light Detection Enabled via CdS-Coated TiO₂ Nanotube Layers

Wiltshire

Alijani

Sopha

et al. 2023

ACS Appl. Mater. Interfaces

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Detection of visible light is a key component in material characterization techniques and often a key component of quality or purity control analyses for health and safety applications. Here in this work, to enable visible light detection at gigahertz frequencies, a planar microwave resonator is integrated with high aspect ratio TiO2 nanotube (TNT) layer-sensitized CdS coating using the atomic layer deposition (ALD) technique. This unique method of visible light detection with microwave-based sensing improves integration of the light detection devices with digital technology. The designed planar microwave resonator sensor was implemented and tested with resonant frequency between 8.2 and 8.4 GHz and a resonant amplitude between −15 and −25 dB, depending on the wavelength of the illuminated light illumination on the nanotubes. The ALD CdS coating sensitized the nanotubes in visible light up to ∼650 nm wavelengths, as characterized by visible spectroscopy. Furthermore, CdS-coated TNT layer integration with the planar resonator sensor allowed for development of a robust microwave sensing platform with improved sensitivity to green and red light (60 and 1300%, respectively) compared to the blank TNT layers. Moreover, the CdS coating of the TNT layer enhanced the sensor’s response to light exposure and resulted in shorter recovery times once the light source was removed. Despite having a CdS coating, the sensor was capable of detecting blue and UV light; however, refining the sensitizing layer could potentially enhance its sensitivity to specific wavelengths of light in certain applications.

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Section: Introductionmentioning

confidence: 99%

Gigahertz-Based Visible Light Detection Enabled via CdS-Coated TiO₂ Nanotube Layers

Wiltshire

Alijani

Sopha

et al. 2023

ACS Appl. Mater. Interfaces

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“…Over the course of the last two decades, the use of microwave sensors has been witnessing a steady expansion in a diverse array of fields. These include but are not limited to biosensing [15][16][17][18][19][20], food quality monitoring [21], material characterization [22][23][24][25], environmental monitoring [26][27][28][29], as well as the monitoring of mechanical motion and strain [30]. The functioning of microwave-resonator-based sensors hinges on the environmental influences on the resonance profile of the sensor.…”

Section: Introductionmentioning

confidence: 99%

AI-Assisted Ultra-High-Sensitivity/Resolution Active-Coupled CSRR-Based Sensor with Embedded Selectivity

Abdolrazzaghi

Kazemi

Nayyeri

et al. 2023

Sensors

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This research explores the application of an artificial intelligence (AI)-assisted approach to enhance the selectivity of microwave sensors used for liquid mixture sensing. We utilized a planar microwave sensor comprising two coupled rectangular complementary split-ring resonators operating at 2.45 GHz to establish a highly sensitive capacitive region. The sensor’s quality factor was markedly improved from 70 to approximately 2700 through the incorporation of a regenerative amplifier to compensate for losses. A deep neural network (DNN) technique is employed to characterize mixtures of methanol, ethanol, and water, using the frequency, amplitude, and quality factor as inputs. However, the DNN approach is found to be effective solely for binary mixtures, with a maximum concentration error of 4.3%. To improve selectivity for ternary mixtures, we employed a more sophisticated machine learning algorithm, the convolutional neural network (CNN), using the entire transmission response as the 1-D input. This resulted in a significant improvement in selectivity, limiting the maximum percentage error to just 0.7% (≈6-fold accuracy enhancement).

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“…Various techniques have been developed to monitor moisture condensation and the formation of frost, snow, and ice, among which ice monitoring is the most studied. − Most techniques for monitoring ice/frost formation are based on in situ measurements of parameter changes for the properties of a specific sensor due to mass loading and changes of the dielectric constants, capacitance, inductance, optical properties, or vibrant frequencies (i.e., using an ultrasonic method or acoustic waves). These methods all have their merits and limitations, − as presented in Table .…”

Section: Introductionmentioning

confidence: 99%

Fundamentals of Monitoring Condensation and Frost/Ice Formation in Cold Environments Using Thin-Film Surface-Acoustic-Wave Technology

Zeng

Ong

Haworth

et al. 2023

ACS Appl. Mater. Interfaces

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Moisture condensation, fogging, and frost or ice formation on structural surfaces cause severe hazards in many industrial components such as aircraft wings, electric power lines, and wind-turbine blades. Surface-acoustic-wave (SAW) technology, which is based on generating and monitoring acoustic waves propagating along structural surfaces, is one of the most promising techniques for monitoring, predicting, and also eliminating these hazards occurring on these surfaces in a cold environment. Monitoring condensation and frost/ice formation using SAW devices is challenging in practical scenarios including sleet, snow, cold rain, strong wind, and low pressure, and such a detection in various ambient conditions can be complex and requires consideration of various key influencing factors. Herein, the influences of various individual factors such as temperature, humidity, and water vapor pressure, as well as combined or multienvironmental dynamic factors, are investigated, all of which lead to either adsorption of water molecules, condensation, and/or frost/ice in a cold environment on the SAW devices. The influences of these parameters on the frequency shifts of the resonant SAW devices are systematically analyzed. Complemented with experimental studies and data from the literature, relationships among the frequency shifts and changes of temperature and other key factors influencing the dynamic phase transitions of water vapor on SAW devices are investigated to provide important guidance for icing detection and monitoring.

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Battery-Free, Artificial Neural Network-Assisted Microwave Resonator Array for Ice Detection

Cited by 21 publications

References 55 publications

Gigahertz-Based Visible Light Detection Enabled via CdS-Coated TiO₂ Nanotube Layers

Gigahertz-Based Visible Light Detection Enabled via CdS-Coated TiO₂ Nanotube Layers

AI-Assisted Ultra-High-Sensitivity/Resolution Active-Coupled CSRR-Based Sensor with Embedded Selectivity

Fundamentals of Monitoring Condensation and Frost/Ice Formation in Cold Environments Using Thin-Film Surface-Acoustic-Wave Technology

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Battery-Free, Artificial Neural Network-Assisted Microwave Resonator Array for Ice Detection

Cited by 21 publications

References 55 publications

Gigahertz-Based Visible Light Detection Enabled via CdS-Coated TiO2 Nanotube Layers

Gigahertz-Based Visible Light Detection Enabled via CdS-Coated TiO2 Nanotube Layers

AI-Assisted Ultra-High-Sensitivity/Resolution Active-Coupled CSRR-Based Sensor with Embedded Selectivity

Fundamentals of Monitoring Condensation and Frost/Ice Formation in Cold Environments Using Thin-Film Surface-Acoustic-Wave Technology

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Product

Resources

About

Gigahertz-Based Visible Light Detection Enabled via CdS-Coated TiO₂ Nanotube Layers

Gigahertz-Based Visible Light Detection Enabled via CdS-Coated TiO₂ Nanotube Layers