Resonance Sensor Research Articles

A New 3-D-Printed Nondestructive H-Like Resonant Fiber-Optic Photoacoustic Sensor for High-Sensitivity Remote Gas Sensing

A New 3-D-Printed Nondestructive H-Like Resonant Fiber-Optic Photoacoustic Sensor for High-Sensitivity Remote Gas Sensing

Stress biomarker detection with a grating-coupled surface plasmon resonance sensor

Stress biomarker detection with a grating-coupled surface plasmon resonance sensor

Microwave Coaxial Line Cavity Resonator Sensor for Thickness Measurement of Coatings on Fiber-Reinforced Polymer Composites

Microwave Coaxial Line Cavity Resonator Sensor for Thickness Measurement of Coatings on Fiber-Reinforced Polymer Composites

Design and Optimization of Encoded and Tunable Graphene-Silver Metasurface Surface Plasmon Resonance Sensor for Detection of Low Refractive Index Variation in Terahertz Regime

Design and Optimization of Encoded and Tunable Graphene-Silver Metasurface Surface Plasmon Resonance Sensor for Detection of Low Refractive Index Variation in Terahertz Regime

High-sensitivity lossy mode resonance sensor by deposition of perovskite nanofilms on the eccentric core quasi D-shaped photonic quasi-crystal fiber

High-sensitivity lossy mode resonance sensor by deposition of perovskite nanofilms on the eccentric core quasi D-shaped photonic quasi-crystal fiber

AuNPs enhanced electrochemical and optical dual-mode fiber optic sensor for trace Hg2+ detection

Efficient and low-concentration detection of heavy metal ions is crucial for healthcare and environmental monitoring. Traditional fiber optic surface plasmon resonance (SPR) sensors face challenges in detecting trace heavy metal ions due to limited sensitivity and the need for complex specific modifications. To overcome these challenges, an innovative electrochemical and optical dual-mode fiber optic sensor for in situ, real-time detection of trace mercury ions is proposed in this paper. The sensor utilizes a reflection-type fiber optic probe coated with thin gold (Au)/indium tin oxide (ITO) film and gold nanoparticles (AuNPs), enabling simultaneous electrochemical and optical interrogation. The coupling effect between the SPR of thin film and the localized surface plasmon resonance (LSPR) of AuNPs significantly improves optical sensitivity, with AuNPs also offering additional active sites for the redox reaction of Hg2+. The ITO film not only facilitates the stripping of Hg2+, leading to sharper stripping peaks but also enhances the ability of the sensor to rapidly respond to anomalous potential changes. Experimental results show that the sensor has a wide dynamic detection range from 10−10 M to 10−5 M, with a limit of detection reaching the pM level. The dual-mode functionality allows the simultaneous collection of voltage, current, and optical information, enabling cross-validation of the detection results and improving the accuracy and reliability of detection.

Engineering a Graphene Quantum Dot‐Enhanced Surface Plasmon Resonance Sensor for Ultra‐Sensitive Detection of Hg2⁺ Ions

AbstractThe contamination of soil and water by heavy metals poses a significant environmental and public health concern worldwide. To address this issue, a novel graphene quantum dot (GQD)‐based surface plasmon resonance (SPR) sensor is developed for the detection of mercury ions (Hg2+), a notorious heavy metal pollutant. The thiol and amine‐functionalized GQDs (S,N‐GQDs), synthesized via pyrolysis of citric acid and L‐cysteine, are directly immobilized onto the SPR chip surface without prior pretreatment, demonstrating their potential as efficient sensing materials. The SPR sensor exhibits high sensitivity and selectivity toward Hg2+ ions, as confirmed by kinetic binding analysis and isotherm modeling. The Langmuir isotherm model, which accurately describes the interactions between Hg2+ and S,N‐GQDs, provides insights into the sensor's mechanism of action. Furthermore, the sensor demonstrates robustness and reusability, with recoveries ranging from 98% to 104% over multiple cycles of analysis. Given the presence of contaminants in tap water, the developed sensor system holds significant importance for environmental monitoring and public health protection, offering a rapid, accurate, and cost‐effective solution for detecting Hg2+ ions in such samples. Overall, this study represents a significant advancement in the field of heavy metal detection, with potential implications for addressing environmental pollution and ensuring water quality.

Ultra Enhancement of the Resolution of the Divergence Beam-Based SPR Sensor Using a Wavelet Filter

Surface Plasmon Resonance (SPR) sensors are highly sensitive to refractive index variations, making them ideal for biosensing and chemical detection applications. However, their performance can be constrained by noise, resolution limits, and signal distortions, particularly in divergence beam-based configurations. This research presents an ultra-enhancement of the performance of divergence beam-based SPR sensors by employing advanced wavelet filtering techniques. Wavelets, with their multi-resolution analysis capability, are applied to denoise and refine the sensor signal, significantly improving key performance metrics, including resolution, mean square error (MSE), root mean square error (RMSE), signal-to-noise ratio (SNR), sensitivity matrix (SM), and combined sensitivity factor (CSF).The wavelet filter effectively decomposes the SPR signal into distinct frequency bands, separating noise while retaining high-frequency components required for accurate sensing. This results in a significant reduction in MSE and RMSE of 30 and 92.26%, respectively, while simultaneously improving SNR by 54.08%, maintaining signal quality. The wavelet filter significantly improved the resolution of the SPR sensor by 99.95% (1.3772×10-7 RIU), allowing for more precise detection of refractive index changes and boosting diverge beam-based SPR sensor performance. In addition, a sensitivity matrix (SM) and combined sensitivity factor (CSF) were improved by 42 and 41.94%, respectively, allowing for a more thorough evaluation of the sensor's performance across multiple operational parameters. Simulation and experimentation show that wavelet filtering surpasses standard filtering approaches in terms of noise suppression and signal clarity. This technology has considerable potential for improving the accuracy and reliability of SPR sensors in high-sensitivity applications

Sensitivity enhancement of guided mode resonance sensors under oblique incidence

The sensitivity of guided mode resonance (GMR) sensors is significantly enhanced under oblique incidence. Here in this work, we developed a simplified theoretical model to provide analytical solutions and reveal the mechanism of sensitivity enhancement. We found that the sensitivity under oblique incidence consists of two contributions, the grating sensitivity and waveguide sensitivity, while under normal incidence, only waveguide sensitivity exists. When the two contributions are constructively superposed, as in the case of positive first order diffraction of the grating, the total sensitivity is enhanced. On the other hand, when the two parts are destructively superposed, as in the case of negative first order diffraction, the total sensitivity decreases. The findings are further supported by FDTD numerical calculations and proof-of-concept experiments.

A Review on Resonant MEMS Electric Field Sensors

Electric field sensors (EFSs) are widely used in various fields, particularly in accurately assessing atmospheric electric fields and high-voltage power lines. Precisely detecting electric fields enhances the accuracy of weather forecasting and contributes to the safe operation of power grids. This paper comprehensively reviews the development of micro-electromechanical system (MEMS) resonant EFSs, including theoretical analysis, working principles, and applications. MEMS resonant EFSs have developed into various structures over the past decades. They have been reported to measure electric field strength by detecting changes in the induced charge on the electrodes. Significant advancements include diverse driving and sensing structures, along with improved dynamic range, sensitivity, and resolution. Recently, mode localization has gained attention and has been applied to electric field sensing. This paper reviews the performances and structures of MEMS resonant EFSs over recent decades and highlights recent advances in weakly coupled resonant EFSs, offering comprehensive guidance for researchers.

A microsystem for in vivo wireless monitoring of plastic biliary stents using magnetoelastic sensors.

With an interest in monitoring the patency of stents that are used to treat strictures in the bile duct, this paper reports the investigation of a wireless sensing system to interrogate a microsensor integrated into the stent. The microsensor is comprised of a 28-μm-thick magnetoelastic foil with 8.25-mm length and 1-mm width. Magnetic biasing is provided by permanent magnets attached to the foil. These elements are incorporated into a customized 3D polymeric package. The system electromagnetically excites the magnetoelastic resonant sensor and measures the resulting signal. Through shifts in resonant frequency and quality factor, the sensor is intended to provide an early indication of sludge accumulation in the stent. This work focuses on challenges associated with sensor miniaturization and placement, wireless range, drive signal feedthrough, and clinical use. A swine specimen in vivo experiment is described. Following endoscopic implantation of the sensor enabled plastic stent into the bile duct, at a range of approximately 17 cm, the signal-to-noise ratio of ~106 was observed with an interrogation time of 336 s. These are the first reported signals from a passive wireless magnetoelastic sensor implanted in a live animal.

MEMS Precision Sensors Based on Process Innovation Technology

This article introduces a novel process for achieving micro-scale thermal isolation through solid porous 3D microstructures. It proposes a method to improve existing thermal MEMS devices by utilizing thin-film membrane structures, develops a model for estimating the thermal conductivity of porous microstructures, and constructs porous 3D microstructures made of three different powder materials, studying their applicability for thermal isolation. Breakthroughs have been achieved in process preparation technology, enabling the production of precision MEMS sensors. These sensors are expected to find wide applications in smart cars, intelligent healthcare, electronic resonance sensors, and other fields.

Sensitivity enhancement of nonlinear micromechanical sensors using parametric symmetry breaking

The working mechanism of resonant sensors is based on tracking the frequency shift in the linear vibration range. Contrary to the conventional paradigm, in this paper, we show that by tracking the dramatic frequency shift of the saddle-node bifurcation on the nonlinear parametric isolated branches in response to external forces, we can dramatically boost the sensitivity of MEMS force sensors. Specifically, we first theoretically and experimentally investigate the double hysteresis phenomena of a parametrically driven micromechanical resonator under the interaction of intrinsic nonlinearities and direct external drive. We demonstrate that the double hysteresis is caused by symmetry breaking in the phase states. The frequency response undergoes an additional amplitude jump from the symmetry-breaking-induced parametric isolated branch to the main branch, resulting in double hysteresis in the frequency domain. We further demonstrate that significant force sensitivity enhancement can be achieved by monitoring the dramatic frequency shift of the saddle-node bifurcations on the parametric isolated branches before the bifurcations annihilate. Based on the sensitivity enhancement effect, we propose a new sensing scheme which employs the frequency of the top saddle-node bifurcation in the parametric isolated branches as an output metric to quantify external forces. The concept is verified on a resonant MEMS charge sensor. A sensitivity of up to 39.5 ppm/fC is achieved, significantly surpassing the state-of-the-art resonant charge sensors. This work provides a new mechanism for developing force sensors of high sensitivity.

Flexible Hair‐Like Piezoelectric Acoustic Particle Velocity Sensor with Enhanced Sensitivity for Speaker Recognition

AbstractFlexible resonant acoustic sensors exhibit enhanced sensitivity near their resonant frequencies and have attracted increasing interest as essential components for next‐generation human‐machine speech interactions. However, membrane‐based resonant acoustic sensors are bulky owing to the inherently high bending stiffness of the sensing membrane. Inspired by the tiny hair‐based sensitive acoustic receptors of spiders, this study reports a hair‐like piezoelectric resonant acoustic particle velocity sensor (HP‐APVS) that enables highly sensitive sound sensing with a significantly reduced size. The HP‐APVS device is essentially a polyimide cantilever array fabricated using Nb0.02‐Pb(Zr0.6Ti0.4)O3 (PZT) on polyimide and self‐bending processes. The experimental results demonstrate that the HP‐APVS shows a linear response to acoustic particle velocity instead of acoustic pressure, with enhanced sensitivity in the resonance mode. Additionally, the proposed HP‐APVS exhibits an outstanding speaker recognition rate of 95.3% with an error rate reduction of 75% compared with that of a reference commercial microphone, indicating many potential applications in the realms of biometric authentication, voice user interfaces, and other intelligent acoustic electronics.

Detection of Serratia marcescens and Mierococcus lysodeikticus Bacterial Cells Using Cerium Oxide/Transition Metal Dichalcogenides Heterostructure‐Based Surface Plasmon Resonance Sensor

This article explores a novel surface plasmon resonance sensor for detecting the Serratia marcescens and Mierococcus lysodeikticus bacteria cells employing the cerium oxide (CeO2) and transition metal dichalcogenides heterostructure. The proposed sensor is designed based on the Kretschmann configuration, where silver (Ag) is deposited over a prism's surface to excite the surface plasmons. The transfer matrix method and angular interrogation technique are exploited for analyzing the sensor's performance at a wavelength of 633 nm. Firstly, the optimization of the prism and metal film is analyzed by selecting the minimum reflectance, better sensitivity, and quality factor. Secondly, the influence of the proposed structure in the sensor is executed by the performances of different structures, which are made with defined layers. Thirdly, different sensing parameters are analyzed for the considered bacterial cells, resulting in the maximum attained parameters being a sensitivity of 369.40° RIU−1, QF of 151.35 RIU−1, and detection accuracy of 7.57. Finally, the comparative study also shows the noteworthy enhancement using the proposed sensor compared with existing work. Therefore, the proposed sensor can be used as a carrier for detecting the bacterial cells and establishing a new platform for biomolecular and biomedical applications.

Temperature and RI sensing based on micro-structured optical fiber surface plasmon resonance

In this paper, we propose a surface plasmon resonance sensor based on micro-structured optical fiber capable of simultaneous sensing of a liquid refractive index and temperature. The fiber structure comprises four large air holes, with side polishing and rectangular groove processing on one side without air holes. Ag film and α-Fe2O3 film are coated inside the rectangular groove for refractive index sensing. Au film is coated on the inner walls of the two side air holes and filled with polydimethylsiloxane (PDMS) for temperature sensing. The results show that the sensor can achieve sensing of two parameters in two polarization directions. With a refractive index ranging from 1.35 to 1.42 and temperature ranging from 10°C to 100°C, the maximum refractive index sensitivity reaches 28225.7 nm/RIU and the maximum temperature sensitivity reaches −3.64nm/∘C. The sensor features simple structure, easy implementation, and high sensitivity, making it applicable in fields such as biosensing, chemical sensing, and environmental monitoring.

Real‐Time Nuclear Magnetic Resonance Detection Using Maximum Likelihood Estimation with Single‐Shallow‐Nitrogen‐Vacancy Centers in Quantum Heterodyne Measurements

Single‐nitrogen‐vacancy (NV) centers in diamond are highly promising quantum nuclear magnetic resonance (NMR) sensors. However, their exposure to many sources of noise, such as surface impurities, shot noise from avalanche photodiode overlaps, and spin‐state projection errors inherent in quantum systems, limits their usefulness. Often, long measurement durations are required to accumulate sufficient data for NMR signal detection via fast Fourier transform spectrometry. For practical reasons, methods to shorten the necessary accumulation time for NMR signal detection are greatly desired. In this article, an on‐line formulation of maximum likelihood estimation (MLE) signal processing for quantum heterodyne NMR measurements is presented as a step toward this goal. This MLE method reduces the required data accumulation time by orders of magnitude and provides good estimates of target frequency locales in real time. These results are significant to practitioners of NMR detection with single‐NV centers in diamond who require a quick litmus test for potential signals when probing a wide area.

Designing of High-Sensitivity Optical Surface Plasmon Resonance Sensor (OSPRS) for Fast and Accurate Diagnosis of Dengue Virus (DeVs)

Designing of High-Sensitivity Optical Surface Plasmon Resonance Sensor (OSPRS) for Fast and Accurate Diagnosis of Dengue Virus (DeVs)

Blood Biomarker Detection Using Integrated Microfluidics with Optical Label-Free Biosensor.

In this study, we developed an optofluidic chip consisting of a guided-mode resonance (GMR) sensor incorporated into a microfluidic chip to achieve simultaneous blood plasma separation and label-free albumin detection. A sedimentation chamber is integrated into the microfluidic chip to achieve plasma separation through differences in density. After a blood sample is loaded into the optofluidic chip in two stages with controlled flow rates, the blood cells are kept in the sedimentation chamber, enabling only the plasma to reach the GMR sensor for albumin detection. This GMR sensor, fabricated using plastic replica molding, achieved a bulk sensitivity of 175.66 nm/RIU. With surface-bound antibodies, the GMR sensor exhibited a limit of detection of 0.16 μg/mL for recombinant albumin in buffer solution. Overall, our findings demonstrate the potential of our integrated chip for use in clinical samples for biomarker detection in point-of-care applications.

Integrative approach to fluorescence-based oxygen sensing in polymer optical fibers with surface plasmon resonance

This study demonstrates a technique to enhance oxygen (O2) concentration measurement by combining surface plasmon resonance (SPR) and fluorescence-based sensor on polymer optical fiber (POF). The SPR was generated using silver (Ag) and the fluorescence was generated by organic dye. Three fluorescence dyes were used, Tris (4, 7-diphenyl-1, 10-phenanthroline) ruthenium (II) dichloride ([Ru(dpp)3]2+), platinum octaethylporphyrin (PtOEP) and 5,10,15,20-tetrakis (pentafluorophenyl) 21 H,23H-porphine palladium (II) (PdTFPP). The sensor was tested in a gas chamber with different concentration level of O2. Sensitivity values for the fluorescence dyes for [Ru(dpp)₃]²⁺, PtOEP, and PdTFPP were 0.0099 a.u/%, 0.0343 a.u/% and 0.05 a.u/% respectively. When SPR was implemented, the sensitivity values for Ag/[Ru(dpp)₃]²⁺, Ag/PtOEP, and Ag/PdTFPP were 0.0589 nm/%, 0.0345 nm/%, and 0.118 nm/% respectively. PdTFPP and Ag/PdTFPP exhibit highest sensitivity in each experiment. Therefore, the further analysis for the sensing performance of PdTFPP and Ag/PdTFPP were held. As a result, Ag/PdTFPP exhibits lower limit of detection (LOD), and limit of quantification (LOQ) with 3.054 % and 9.254 %, respectively, with higher R2 of 0.9971 and lower mean standard deviation of 0.174, compared to PdTFPP 16.496 % and 49.988 % respectively, with R2 of 0.9211 and higher mean standard deviation of 2.003. This improvement can benefit researchers and professionals in medical diagnostics, environmental monitoring, and industrial process control by providing a more sensitive and accurate method for measuring O2 levels.