Resonance-based Sensor Research Articles

Robustly packaged lithium niobate resonator-based temperature sensor

Abstract Whispering gallery mode (WGM) resonators with high optical quality factor (Q) are highly sensitive to environment changes and are used in various sensing applications. We have developed a high-precision temperature sensor using a compactly packaged lithium niobate (LN) WGM resonator. This sensor offers a sensitivity of 34.38pm/℃ and a high resolution of up to 5.6×10-4 ℃. It is portable with high Q, making it suitable for using outside the laboratory. The device is also resilient to changes in humidity, enhancing its practicality.

Enhancing the performance of a resonance-based sensor network for soft robots using binary excitation.

Embedded, flexible, multi-sensor sensing networks have shown the potential to provide soft robots with reliable feedback while navigating unstructured environments. Time delay associated with extracting information from these sensing networks and the complexity of constructing them are significant obstacles to their development. This paper presents a novel enhancement to an existing class of embedded sensor network with the potential to overcome these challenges. In its original version, this sensor network extracts information from multiple reactive sensors on a two-wire electrical circuit simultaneously. This paper proposes to change the excitation signal applied to this sensor network to a binary signal. This change offers two key advantages: it provides the ability to employ small, inexpensive microcontrollers and results in a faster data extraction process. The potential of this enhanced system is demonstrated here with a proof of concept implementation. The self-inductance of all inductance-based sensors within this proof of concept sensor network can be measured at a rate of over 5000 times per second with an average measurement error of less than 2%.

Microwave planar resonator-based sensor for pharmaceutical tablet-moisture characterization based on complementary symmetric meander line-shaped structure

ABSTRACT This paper presents a microwave planar resonator-based sensor for moisture sensing application. The resonator sensor is designed utilising the Complementary Symmetric Meander Line-Shaped Resonator topology and operated in the S-band with the frequency range of 2.6–3.3 GHz. The main design criteria of this sensor are based on low manufacturing complexity and cost, ease of fabrication and integration with existing equipment, despite its high sensitivity and accuracy. When this sensor is loaded/unloaded with four different Material Under Tests with relative permittivity values varying from 2.3 to 4.3, the electromagnetic simulations were validated against experimental measurements according to the resonant notch frequency of transmission coefficient for the sensor’s material-characterisation performance. The simulated and experimental results show good agreements on the resonant frequencies and demonstrate the sensor’s high performance with a normalised sensitivity of 6%. Resonant frequencies are well correlated with material permittivity using a quadratic-polynomial regression with R 2 = 0.999. Moreover, moisture-content percentages of both dry and moist paracetamol tablets, measured by a loss-on-drying moisture analyser between 1.74% and 17.72%, have good correlation with the sensor’s resonant-frequency shift from on-line measurements. This resonator sensor has exhibited the potential for detecting moisture contents in small-sized materials in various industries.

Prototype of Circular Split Ring Resonator-Based Sensor for Estimating Soil Moisture as a Function of Soil Particle Distribution

Prototype of Circular Split Ring Resonator-Based Sensor for Estimating Soil Moisture as a Function of Soil Particle Distribution

3D coupled vibrations of asymmetric nano-particle mass sensors: Two-phase integral nonlocal strain gradient model and MD simulation

Since it is possible for the nano-particle to have any asymmetric shape and may attach to every position of the resonator-based mass sensors, any type of mass eccentricity and subsequently coupled vibrations are possible. So, in the present work, the 3D coupled axial-torsional-flexural vibrations of the mass nano-sensors are investigated considering both in-plane and out-of-plane bending as well as axial and torsional vibrations. In addition, the integral form of the two-phase local/nonlocal strain gradient (LNSG), as the consistent type of the common nonlocal strain gradient (NSG) elasticity theory, is employed for the first time to consider the size effects in the mass nano-sensors. A quasi-3D coupled FE model is constructed with no shear-locking within the complicated environment of the integral LNSG. The impacts of the LNSG elasticity and diverse types of possible coupling in changing the vibrational behavior of the mass nano-sensor are scrutinized and their crucial role in modeling of the nano-sensors is indicated. Furthermore, molecular dynamic (MD) simulations are implemented to identify and analyze the coupled vibrations of a mass nano-sensor consisting of a fixed-free carbon nanotube. Comparison between the MD results with those of the present coupled FE model reveals that considering the coupling effects reduces the modeling error, especially in the cases in which the coupling influences intensify. The present work can help to provide more accurate models of mechanical resonance-based nanosensors to detect nanoparticles with different shapes, larger sizes, and high mass ratios, which can lead to achieving sensors with higher sensitivity.

Neuromorphic alternating current sensing using piezoelectric resonators and physical reservoir computing

Non-contact current sensors are valuable because they can safely measure alternating current without interrupting the circuit. However, current sensors utilizing Hall elements or coils are only available for single wires, and piezoelectric resonator-based sensors have difficulty achieving both high sensitivity and linearity. To address this issue, we propose a novel approach, that is, the use of piezoelectric current sensors as nodes for physical reservoir computing (physical RC), allowing us to utilize nonlinear regions. To improve the sensitivity and short-term memory required by physical RC, a piezoelectric resonator with a quality factor of 75 was realized by employing a tuning fork structure. Nonlinearities were also introduced by analog circuits. The results of the benchmark tests indicate that the device worked as a physical RC and that it successfully predicted unknown current values from the results of training at three levels of current.

Patterned Laser-Induced graphene enabling a High-Performance gas sensing Split-Ring resonator

The outstanding potential of microwave resonator-based energy-efficient gas sensors has been overshadowed by their underperforming gas sensing capabilities, especially insignificant sensitivity to detect low-concentration volatile organic compounds (VOCs). This unmet challenge persists primarily due to predominant metallic resonator structures, which further limit their wearable applications and pose environmental concerns. This work presents a laser-induced graphene (LIG)-enabled split-ring resonator (SRR) sensor on a flexible polyimide substrate for the rapid and sensitive detection of gaseous VOCs. To implement the sensor, the conductive traces of the SRR were created using a computer-controlled CO2 laser at an optimized power level, thus inducing 48 µm thick, conductive (24 S/cm) graphene layers on a polyimide substrate. The SRR gas sensor, in which LIG with three-dimensional networks of porosity serves as conductive and even gas-sensitive traces, benefits from a significantly enhanced interaction between the SRR’s electromagnetic field and VOC gases. As a proof of concept, a prototype of the LIG-enabled SRR was implemented and mounted on a test fixture. The developed gas sensor operated at a resonant frequency of 1.402 GHz, which exhibited rapid (∼17 s) and noticeable shifts when exposed to 200 ppm of different VOCs (acetone, ethanol, methanol, toluene, and isopropyl alcohol). Additionally, the sensor demonstrated a linear correlation between the resonant frequency and acetone gas concentration (1 ppm-200 ppm), with a sensitivity of 188 KHz/ppm. These electromagnetic and gas sensing results suggest that polyimide-derived LIG traces can replace metal microstrip lines in the SRR structure, opening up possibilities for high-performance microwave resonator gas sensors, even suitable for flexible and wearable applications.

Expanding Limit of Detection and Increasing Operating Resonant Frequency via Larger Anchor Widths for Capacitive Micromachined Resonator-Based Mass Sensors

Expanding Limit of Detection and Increasing Operating Resonant Frequency via Larger Anchor Widths for Capacitive Micromachined Resonator-Based Mass Sensors

Design and 3-D Printing-Assisted Fabrication of Microwave Resonator-Based Passive Wireless Sensors for Simultaneous Measuring High Temperatures and Pressures

Design and 3-D Printing-Assisted Fabrication of Microwave Resonator-Based Passive Wireless Sensors for Simultaneous Measuring High Temperatures and Pressures

Hairpin Resonator-Based Microwave Sensor for Detection of Nitrogenous Fertilizers in Soil and Water

Hairpin Resonator-Based Microwave Sensor for Detection of Nitrogenous Fertilizers in Soil and Water

Resonator-based nanoscale plasmonic sensor made of metal–graphene–insulator interfaces

We present a nanoscale refractive index plasmonic sensor based on Fano resonance. We simulate and numerically analyze a novel double T-shaped resonator structure made of conductor–insulator waveguides. Our simulation results show that two Fano resonance peaks can be achieved by the interference between a broadband mode in the straight waveguide and a narrowband mode in the T-shaped resonator. The shifts of Fano resonance peaks by changing the sample refractive index in the resonator structure facilitates the design of a refractive index sensor. To attain a sensor with high sensitivity and figure of merit we employ different geometrical parameters for the resonator structure and analyze the transmission spectra of the sensor. By optimizing the sensor structural parameters we achieve a maximum sensitivity of 523.5 nm/RIU and figure of merit of 2×105 for the sensor made of metal–insulator waveguide. By employing graphene at the core–cladding boundary of the waveguides we attain a high sensitivity of 662.3 nm/RIU and figure of merit of 6.6×105 compared to the literature. We employ samples with refractive indices ranging from 1.0 to 1.05 to analyze the sensor capabilities and employ blood plasma samples to analyze the applications of our sensor structure as a biosensor. Simple fabrication, compactness and high sensitivity are the main advantages of the proposed sensor structure.

Chipless RFID Sensor for Measuring Time-Varying Electric Fields Using a Contactless Air-Filled Substrate-Integrated Waveguide Resonator.

This paper presents a wireless chipless resonator-based sensor for measuring the absolute value of an external time-varying electric field. The sensor is developed using contactless air-filled substrate-integrated waveguide (CLAF-SIW) technology. The sensor employs a low-impedance electromagnetic band gap structure to confine the electric field within the sensor's air cavity. The air cavity is loaded with varactor diodes whose reverse bias voltage is modified by the to-be-measured external electric field. Variation in the external electric field results in a variation of the sensor's resonant frequency. The CLAF-SIW sensor offers a high unloaded quality factor, which is required for a long-distance ringback-based interrogation system. A prototype of the proposed sensor is fabricated and tested. It can measure a time-varying external electric field up to 6.9 kV/m, has a sensitivity of 1.86 (kHz)/(V/m), and can be interrogated from a distance of 80 cm. The feasible maximum bandwidth of the external electric field is 25 kHz. The proposed sensor offers a compact planar multilayer structure that can easily be incorporated with a planar antenna and its size can be reduced by selecting a higher operating frequency without an increase in dielectric loss.

Improving the performance of resonator-based optical sensors using time-lagged correlation and Fourier phase shift analysis

The performance of time-lagged correlation and Fourier phase shift analysis in resonator-based optical sensors was evaluated and compared to centroiding algorithms. 100 emission spectra of an Er3+ oxyfluoride microsphere were recorded and the average of all data was used as a noiseless spectrum. The Whispering Gallery Mode (WGM) signal, superimposed on the Er3+ emission band, was subtracted and shifted to simulate sensor measurements. Additive random Gaussian noise with different values of the variance was added to the original and WGM-shifted spectra, and the WGM shift was estimated using time-lagged correlation, Fourier phase shift analysis and centroiding algorithms. The procedure was repeated 10000 times to evaluate the accuracy and precision of all numerical methods, and different values of the noise level and WGM shift were considered. These pseudo-experimental studies show that the use of time-lagged correlation and Fourier phase shift analysis can improve the accuracy and precision of the sensor when compared to traditional centroiding algorithms. Additionally, signal analysis can be automated without the need for peak identification and matching.

Robust acoustic directional sensing enabled by synergy between resonator-based sensor and deep learning

We demonstrate enhanced acoustic sensing arising from the synergy between resonator-based acoustic sensor and deep learning. We numerically verify that both vibration amplitude and phase are enhanced and preserved at and off the resonance in our compact acoustic sensor housing three cavities. In addition, we experimentally measure the response of our sensor to single-frequency and siren signals, based on which we train convolutional neural networks (CNNs). We observe that the CNN trained by using both amplitude and phase features achieve the best accuracy on predicting the incident direction of both types of signals. This is even though the signals are broadband and affected by noise thought to be difficult for resonators. We attribute the improvement to a complementary effect between the two features enabled by the combination of resonant effect and deep learning. This observation is further supported by comparing to the CNNs trained by the features extracted from signals measured on reference sensor without resonators, whose performances fall far behind. Our results suggest the advantage of this synergetic approach to enhance the sensing performance of compact acoustic sensors on both narrow- and broad-band signals, which paves the way for the development of advanced sensing technology that has potential applications in autonomous driving systems to detect emergency vehicles.

Design and Analysis of a Sub-THz Resonator-Based High-Resolution Permittivity Sensor

Design and Analysis of a Sub-THz Resonator-Based High-Resolution Permittivity Sensor

Dual-Mode Solidly Mounted Resonator-Based Sensor for Temperature and Humidity Detection and Discrimination.

Sensors based on solidly mounted resonators (SMRs) exhibit a good set of properties, such as high sensitivity, fast response, low resolution limit and low production cost, which makes them an appealing technology for sensing applications. However, they can suffer from cross-sensitivity issues, as their response can be altered by undesirable ambient factors, such as temperature and humidity variations. In this work we propose a method to discriminate humidity variations from the general frequency response using an SMR specifically manufactured to operate in a dual-mode (displaying two close resonances). The two modes behave similarly towards humidity changes (-1.94 kHZ/(%RH)) for resonance one and -1.62 kHZ/(%RH) for resonance two), whereas their performance under temperature changes is significantly different, displaying 2.64 kHZ/°C for resonance one and 34.21 kHZ/°C for resonance two. This allows for the decoupling process to be carried out in a straightforward manner. Frequency response is tracked under different humidity conditions, in the -20 °C to room temperature region, proving that this behavior is reproducible in any given environment.

An LC Resonance-Based Sensor for Multicontaminant Detection in Oil Fluids

An <i>LC</i> Resonance-Based Sensor for Multicontaminant Detection in Oil Fluids

Design of double V-groove shape-based PCF sensor for cancer detection using RI technique

After COVID-19 healthcare shareholders are more attentive to the different solutions. One of the critical illnesses cancer becomes more changeling after this situation. There are different techniques are suggested as well as developed for detection of the cancer. People of still looking for low-cost solutions for cancer detection. The Photonic crystal fiber is a versatile device utilized for various bio-sensor applications. The double V-groove design proposed in this research offers significant advantages, including enhanced sensitivity, accurate detection capabilities, and easy fabrication. The surface plasmon resonance-based PCF sensor, with its unique V-shaped structure, not only addresses the limitations of conventional prism-based SPR sensors but also opens new possibilities for remote sensing applications. The proposed article is based on the double V-groove photonic crystal fiber (PCF)-based sensor for cancer detection. The Q factor is 155 and the figure of merit (FOM) is 6000RIU−1and sensitivity of the proposed sensor is 60μmRIU−1has obtained. This sensor provides a wide range of detection based on the refractive index (RI) profile of the infected blood.

Non-destructive methodology for crack detection using machine learning-assisted resonant sensor

Condition monitoring of structures built using metallic supports is a significant issue in structural engineering. Through this work, design, fabrication, and optimization of a dual-scale resonance-based microwave sensor is discussed for monitoring cracks developed over metallic surfaces. These sensors were initially simulated and later fabricated in micro-wave (4.59 GHz) and radio-wave region (418 MHz) for which the power attenuation and frequency shifts were observed. With the structure having crack depth of 2 mm, microwave sensor showed the power shift ∼24 %, while the radio-wave range sensors showed ∼9 %. The corresponding frequency shifts were 2.4 % and 0.85 %, respectively. The microwave sensor (power shift data) showed ∼280 % more sensitivity than the radio-wave sensor. By using dual scale, comprising of both frequency and power shifts, the microwave sensor classification was further improved to 99.72 %, as compared to their individual counterparts. A non-destructive crack detection system in microwave regime is hence demonstrated, which can be further explored for range of crack studies in metallic structures.

Microsphere-Enabled Micropillar Array for Whispering Gallery Mode Virus Detection.

Rapid detection of pathogens and analytes at the point of care offers an opportunity for prompt patient management and public health control. This paper reports an open microfluidic platform coupled with active whispering gallery mode (WGM) microsphere resonators for the rapid detection of influenza viruses. The WGM microsphere resonators, precoated with influenza A polyclonal antibodies, are mechanically trapped in the open micropillar array, where the evaporation-driven flow continuously transports a small volume (∼μL) of sample to the resonators without auxiliaries. Selective chemical modification of the pillar array changes surface wettability and flow pattern, which enhances the detection sensitivity of the WGM resonator-based virus sensor. The optofluidic sensing platform is able to specifically detect influenza A viruses within 15 min using a few microliters of sample and displays a linear response to different virus concentrations.