Resonance Sensor Research Articles

All Optic-Fiber Waveguide-Coupled SPR Sensor for CRP Sensing Based on Dielectric Layer and Poly-Dopamine

We developed an all optic-fiber waveguide-coupled surface plasmon resonance (SPR) sensor using zirconium disulfide (ZrS2) and poly-dopamine (PDA) as the dielectric layer and biological cross-linker, respectively. This sensor can be employed to monitor the entire process of the C-reactive protein (CRP) sensing, including antibody modification and antigen detection. The design and the optimization of the optical fiber waveguide-coupled SPR sensor were realized, based on the transfer matrix method and first-principles calculations. The sensor was fabricated and characterized according to the optimized parameters. The experimental setup was implemented to measure the entire process of antibody modification and antigen detection for CRP with the detection limit of 3.21 pmol·mL−1, and the specificity tests were also carried out.

An amplitude-based temperature compensated MEMS resonant pressure sensor with single resonator

Temperature compensation is a common concern of MEMS sensors. This paper presents an amplitude-based temperature compensated MEMS resonant pressure sensor. An AGC (automatic gain control) closed-loop circuit with a constant-amplitude drive was designed, enabling the real-time sampling of resonant frequencies and amplitudes. Under the constant-amplitude drive, the amplitude of the resonator changes monotonously with temperature. Thus, pressure and temperature can be decoupled using a single resonator, achieving high accuracy in pressure measurements. Experimental results demonstrated that the fabricated microsensor achieved high performance with the amplitude-based temperature compensation. Within a pressure range of 10 kPa to 100 kPa and a temperature range of −20℃ to 60℃, the pressure accuracy of the microsensor reached ± 0.012 %FS (full scale), with a repeatability error of 0.009 %FS and a pressure hysteresis error of 0.007 %FS. Based on single resonator, the developed microsensor is expected to reduce device sizes, simplify design and fabrication processes, and decrease the power consumption of the system.

Evaluation of reflective fiber-optic surface plasmon resonance sensor for monitoring scale deposition.

A reflective surface plasmon resonance (SPR) sensor was evaluated for real-time monitoring of scale deposition. The sensor consists of an optical fiber, only 5mm at the gold-coated tip of the sensing area. The effect of silica growth on the sensor response was evaluated using a Na2SiO3 solution. The sensitivity of the sensor to silica was 1.6 ± 0.3nm per one immersion in the solution of 1000mg/L (as SiO2) at 85°Cand subsequnt air drying, as indicated by theSPR peak shift. The amount of silica deposited on the gold surface was measured by the quartz crystal microbalancemethod, and the SPR sensitivity of 0.089nm/ng to silica mass was obtained. The detection limit (3σ) of the SPR sensor was 17ng, correspondingto a thickness of 2.5nm for amorphous silica. The SPR sensor wastested in geothermal brine sampled at the Sumikawa Geothermal Power Plant, where a clear SPR shift was observed, suggesting the effectiveness of the SPR sensor for scale monitoring.

Gratings for enhanced sensitivity: advancing D-shaped optical fiber surface plasmon resonance sensors with Ag-Fe2O3 structures

This research delves into enhancing biosensing sensitivity by optimizing D-shaped optical fiber surface plasmon resonance (SPR) sensors employing Ag-Fe2O3 structures. By investigating the influence of different grating structures—rectangular, triangular, and elliptical—on sensor performance, a comprehensive analysis was conducted to ascertain the impact of these structural variations on sensitivity and detection precision. The study revealed that while the rectangular structure exhibited a sensitivity of 6.4 µm/RIU, the triangular structure outperformed with an impressive sensitivity of 7.2 µm/RIU. Moreover, the detection accuracy, quantified by the detection angle (DA), reached 15.7(µm)−1 for the triangular grating, surpassing the rectangular grating’s detection angle of 14.8(µm)−1. These results underscore the crucial role of structural design in enhancing sensor performance, with the triangular grating demonstrating superior sensitivity and detection precision in the context of plasmonic resonance. The extended detection range of refractive indices around 1.39 further expands the sensor’s applicability in diverse chemical and biomedical analyses. Notably, the sensor’s capability to detect various chemical solutions and diseases—including plasma, tuberculosis, white blood cells, and breast cancer cells—underscores its versatility and efficacy in dual-parameter detection. Through meticulous simulations and analysis, this study provides valuable insights into optimizing sensor sensitivity, detection accuracy, and application versatility, paving the way for advanced developments in biosensing technology with far-reaching implications for chemical and biomedical research.

Cascaded dual-parameter SPR fiber sensor for RI and pH simultaneous detection based on Ag film and an Ag/self-assembled nanofilm structure

To achieve more accurate analysis and detection of changes in liquid parameters, we propose a dual-parameter surface plasmon resonance (SPR) sensor that can measure refractive index (RI) and pH simultaneously. In this paper, we compare and analyze the transmission spectrum when the SPR effect is excited by the cladding mode of a photonic crystal fiber (PCF) and the core mode of the no-core fiber. The results show that the SPR effect excited using the cladding mode is stronger and the sensor has better loss peaks, which is more conducive to realizing the detection of the external environment. Therefore, the sensor uses PCF as the substrate and utilizes a cascade composite film structure, and the area where a silver film is deposited on the surface of the PCF is selected as the RI sensing area. Another part of the PCF, after the silver film is deposited, uses a high-sensitivity polyacrylic acid/chitosan self-assembled nanofilm as the pH-sensitive film. Experimental results show that the maximum sensitivity is 4122.44 nm/RIU and -57.82 nm/pH when the RI range is between 1.333 and 1.385 and the pH range is between 3.11 and 8.63, respectively. In addition, we experimentally verified that the sensor had good stability and repeatability. The design of the sensor provides new possibilities for real-time monitoring and precise control, helping to advance scientific research and the development of industry.

Development of PIND system based on resonant sensors and research on material identification methods for redundant particles

Abstract Aiming at the problems of the existing particle impact noise detection (PIND) system, such as low detection accuracy, high rate of misjudgment and missed judgment, and the inability to judge the material of internal redundant particles in real time, a method for automatic detection and material identification of redundant particles based on neural network recognition is proposed, and an automatic detection system for redundant particles of sealed electronic devices is developed. The system is equipped with multi-channel piezoelectric resonant sensors, which convert the redundant particle impact noise signal into a voltage signal, and then transmit the signal to the host using a high-speed data acquisition system. The upper computer uses a short-term energy threshold detection method to extract signal pulses; Then, a variety of time and frequency domain features are extracted and combined with wavelet domain features; Finally, by training the multi output neural network prediction model, it can automatically judge whether there are redundant particles in the tested parts, and automatically give the material information of the redundant particles. Experiments show that the accuracy of the system for material recognition of redundant particles with a mass greater than 0.1 mg can reach 88.6%.

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.

ZnO and antimonene-based surface plasmon resonance sensor for enamel, dentin, and cementum layer detection in human teeth

ZnO and antimonene-based surface plasmon resonance sensor for enamel, dentin, and cementum layer detection in human teeth

Angle-Dependent In-Plane Magnetic Field Detection by MEMS Resonant Sensor

Angle-Dependent In-Plane Magnetic Field Detection by MEMS Resonant Sensor

Detection methods for antibiotics in wastewater: a review.

Antibiotics are widely used as fungicides because of their antibacterial and bactericidal effects. However, it is necessary to control their dosage. If the amount of antbiotics is too much, it cannot be completely metabolized and absorbed, will pollute the environment, and have a great impact on human health. Many antibiotics usually left in factory or aquaculture wastewater pollute the environment, so it is vital to detect the content of antibiotics in wastewater. This article summarizes several common methods of antibiotic detection and pretreatment steps. The detection methods of antibiotics in wastewater mainly include immunoassay, instrumental analysis method, and sensor. Studies have shown that immunoassay can detect deficient concentrations of antibiotics, but it is affected by external factors leading to errors. The detection speed of the instrumental analysis method is fast, but the repeatability is poor, the price is high, and the operation is complicated. The sensor is a method that is currently increasingly studied, including electrochemical sensors, optical sensors, biosensors, photoelectrochemical sensors, and surface plasmon resonance sensors. It has the advantages of fast detection speed, high accuracy, and strong sensitivity. However, the reproducibility and stability of the sensor are poor. At present, there is no method that can comprehensively integrate the advantages. This paper aims to review the enrichment and detection methods of antibiotics in wastewater from 2020 to the present. It also aims to provide some ideas for future research directions in this field.

High-Performance Terahertz Surface Plasmon Resonance Sensor with Graphene-Perovskite Metasurface for Early Cancer Detection

High-Performance Terahertz Surface Plasmon Resonance Sensor with Graphene-Perovskite Metasurface for Early Cancer Detection

Experimental study on the technology optimization of clear ice thickness detection on horizontal cold plate surface by using microwave resonance

The accumulation of snow and ice has the potential to have a negative impact on numerous industries if it is not accurately detected and processed in real-time. Microwave resonators have gained interest as durable and reliable ice detectors. To detect the thickness of clear ice slices on a horizontal cold plate surface, a capacitively coupled split-ring resonant sensor was experimentally investigated. To ascertain the efficacy of the sensor, plexiglass with similar relative permittivity to ice was firstly tested. The effect of the plexiglass plate thickness on the resonance amplitude of the transmission scatter parameter was found to be monotonic in the range of 16.8 mm thickness, thereby demonstrating the ability of the sensor to accurately measure plate thickness. Then, the effect of different thicknesses of clear ice slices within 17.0 mm on the resonance parameters was tested under constant temperature. The resonant amplitude decreased by 46.55% from −4.13 dB to −6.05 dB, as the thickness of the clear ice slice gradually increased from 2.5 mm to 17.0 mm. A model for the detection of ice thickness based on the analysis of theoretical principles and experimental data was developed. The ice thickness could be detected accurately within a range of 17.0 mm at temperatures between −3 and −20 °C, with a maximum deviation of 5.66% in the detection of ice thickness. This study validates the application of the sensor to detect ice thickness, such as on ships, roads and aircraft.

High sensitivity, thermal noise-driven aluminum-based resonant MEMS humidity sensor

The integration of connected devices and the Internet of Things in the era of Industry 4.0 has led to the transformation of various sectors. Sensors, particularly for humidity measurement, play a pivotal role in applications such as respiration and wound monitoring, human–machine interfaces, fuel cells, and circuit failure detection. While conventional humidity sensors dominate the market, gravimetric-based sensing offers promise but faces challenges due to complex fabrication, high cost, and nonlinearity. This study explores gravimetric platforms for humidity sensing and proposes linear and nonlinear schemes to detect humidity. The linear sensors exhibit consistent frequency shifts with humidity changes, while the nonlinear sensors introduce a turn-around point where nonlinear effects counteract mass-loading. We address this limitation by splitting the dynamic range into low and high ranges on either side of this point, thereby creating one-to-one relationships. Both sensor types demonstrate high sensitivity (from 39068 to −23568 ppm/%RH for nonlinear and 5809 ppm/%RH for linear) and repeatability, emphasizing their suitability for real-time humidity monitoring. Moreover, the thermal noise-driven resonators underlying the sensors do not require external input, thereby enhancing their suitability for low-power applications. These findings provide a foundation for innovative real-time sensing applications and offer insights into optimizing sensitivity and stability in humidity sensing and other applications.

A Highly Sensitive D-Shaped PCF-SPR Sensor for Refractive Index and Temperature Detection.

A novel highly sensitive D-shaped photonic crystal fiber-based surface plasmon resonance (PCF-SPR) sensor for dual parameters of refractive index and temperature detecting is proposed. A PCF cladding polishing provides a D-shape design with a gold (Au) film coating for refractive index (RI) sensing (Core 1) and a composite film of silver (Ag) and polydimethylsiloxane (PDMS) for temperature sensing (Core 2). Comsol Multiphysics 5.5 is used to design and simulate the proposed sensor by the finite element method (FEM). The proposed sensor numerically provides results with maximum wavelength sensitivities (WSs) of 51,200 and 56,700 nm/RIU for Core 1 and 2 as RI sensing while amplitude sensitivities are -98.9 and -147.6 RIU-1 with spectral resolution of 1.95 × 10-6 and 1.76 × 10-6 RIU, respectively. Notably, wavelength sensitivity of 17.4 nm/°C is obtained between -20 and -10 °C with resolution of 5.74 × 10-3 °C for Core 2 as temperature sensing. This sensor can efficiently work in the analyte and temperature ranges of 1.33-1.43 RI and -20-100 °C. Due to its high sensitivity and wide detection ranges, both in T and RI sensing, it is a promising candidate for a variety of applications, including chemical, medical, and environmental detection.

Halide perovskite and few-layer silicon-based surface plasmon resonance sensor for the detection of chemical and biochemical sensing

This paper examines the combined effect of perovskite/silicon (Si) material on the performance of a surface plasmon resonance (SPR) sensor using the Kretschmann structure. The proposed sensor incorporates the BAF10/Cu/perovskite materials/Si/sensing medium (SM) layers. This paper incorporates the optimized parameters into the proposed sensor by comparing the results without perovskite material and existing work. The proposed modified Kretschmann structure consists of perovskite material such as CsPbI3, FASnI3, KSnI3, and CsSnI3, with few Si layers. All the performance parameters are calculated at 633 nm wavelength. The sensitivity (S), full width at half maximum (FWHM), detection accuracy (DA), and figure of merit (FoM) of 348.75°/RIU, 3.22°, 0.31/° and 108.11/RIU using perovskite material of KSnI3, are measured, respectively by the proposed sensor. The perovskite material of KSnI3 shows the best performance parameter among CsPbF3, FASnF3, and CSSnF3. These results should greatly impact the biosensing application, especially for chemical and biochemical.

A microstrip-based dielectric sensor with four fluidic channels for complex dielectric constant detection of aqueous alcohols

A cost-effective planar microstrip-based dielectric sensor with four fluidic channels on its ground plane is proposed for estimating the concentration and complex dielectric constants of ethanol/water mixtures. The channels are placed on the long sides of the slot resonators, which are slightly carved from the substrate. The sensor prototype is fabricated, showing good agreement between simulated and measured parameters. The sensor's resonance characteristics, influenced by the binary mixtures, are used to estimate the dielectric constants with an empirical relation. Validation is achieved through good correspondence with literature values. The sensor's resonance can be tailored by adjusting the number of fluidic channels. With a normalized sensitivity of 0.063% using 17.28 µl of material-under-test, the sensor is label-free, reusable, non-destructive, contactless, and suitable for lab-on-chip chemical sensing applications.

Machine learning approach in multi-channel fiber-optic SPR sensors

Fiber-optic surface plasmon resonance (SPR) sensors have been increasingly used due to their advantages such as compact size, stable physical and chemical properties, high sensitivity, and resistant to electromagnetic interference. In this paper, a dual-channel side-polished fiber-optic SPR sensor system is established to detect the refractive index of liquids and the liquid temperature. High sensitivity of ∼2000 nm/RIU (refractive index unit) and linear sensitivity of ∼−2.0 nm/°C is achieved for two-channel SPR sensors, which are integrated for simultaneously RI temperature sensing and easily scaled to multi-channel SPR sensor array. The resonant wavelengths of the two sensors are located in the range of 600–700 nm and 700–800 nm respectively, which could avoid overlapping the resonance dips. Then, we propose an approach using five machine learning algorithms to predict the resonant wavelength of the second channel of SPR temperature sensor using the normalized transmission spectrum data with a wavelength range of 760–889 nm. After error analysis, it is found that the Categorical Boosting (CatBoost) is the best among five algorithms in terms of accuracy and resolution. The results provide clear evidence that accurate SPR resonant wavelength can be obtained with machine learning approach using a more compact spectrometer.

An NMR immunosensor based on streptavidin-biotin signal amplification for rapid detection of Salmonella in milk

Sensitive and accurate detection of harmful pathogenic bacteria in food is of great significance to public health. In this paper, a nuclear magnetic resonance (NMR) sensor based on biological signal amplification was constructed. The carboxymethyl dextran (CMD) was used as both the probe skeleton and the chelating agent to realize the fast chelating adsorption of the signal source gadolinium ion. Finally, the magnetic complex and biotinylated antibody formed an immune probe through the biological bridge to achieve rapid capture of Salmonella. In addition, non-target bacteria such as Proteus vulgaris and Listeria monocytogenes were used to test the specificity of the constructed sensor. The sensor can detect Salmonella within 1.5 h under optimal conditions, the detection limit in milk is 7.4 × 103 CFU mL−1, and the RSD (Relative standard deviation) of reproducibility experiment is 2.35%, which has good reproducibility.

Accuracy improvement of resonant sensor by an additional electrode in the measurement of liquid density and viscosity

Purpose In the measurement of liquid density and viscosity, the change of resonance parameters due to the parasitic parallel capacitance of resonator affects the measurement accuracy. To improve the accuracy, a method was proposed to compensate the parasitic parallel capacitance of resonator by adding an electrode. Design/methodology/approach The new electrode (compensation electrode) was added into resonant sensor to make compensation capacitance. The closer the compensation capacitance was to the parasitic parallel capacitance, the better compensation was. The structural parameters of resonant sensor with the compensation electrode were determined by the simulation and experiment. Findings The effect of this method was examined by the experiment. The relative errors of density and viscosity were less than 0.15, 0.5 % and standard deviations were less than 0.0004 g/cm3 and 0.005 mPas, respectively. Practical implications The experimental results show that this method is valuable for the parasitic parallel capacitance compensation of immersed resonant sensor. Originality/value This paper has not been published in other journals.

Highly selective localized surface plasmon resonance sensor for selenium diagnosis in selenium-rich soybeans

It is a challenge to determine selenium in acid aqueous for environmental monitoring and selenium-rich agricultural diagnosis. Herein, we developed a novel localized surface plasmon resonance (LSPR) sensor to detect Se(IV) ions based on the extraordinary laterals etching of gold nanorods (AuNRs). The etching started from the laterals in the low amount of Se(IV) ions, and accompanied by an apparent red shift of the longitudinal plasmon band (LPB), and then transformed to the tips etching with the upward of Se(IV) ions, the LPB band immediately shifted to the shorter wavelength. The red shift change (Δλ) of LPB band was utilized to quantitative analysis instead of blue shift or absorbance intensity, which gave a high selectivity for the proposed sensor. More importantly, this sensor could be performed in 0.1 mol/L of HCl solution, which achieved the seamlessly jointing with the pretreatment of complex samples, without time-consuming pH adjustment.Successful selenium detection was demonstrated in complex soybean samples that collected from the maturity after spraying organic chelated selenium at full flower period. The sensor provided a promising way to monitor and diagnose selenium in complex environmental samples and selenium-rich crops.