Finite Element Analysis Model of Electronic Skin Based on Surface Acoustic Wave Sensor

A sensitivity-enhanced plasmonic sensing platform modified with Co(OH)2 nanosheets

In the detection of biomolecules, surface plasmon resonance (SPR) sensors require high sensitivity. In this study, we propose a sensitivity-enhanced functionalized plasmonic interface based on Ag-TiO2-Co(OH)2 nanosheets structure. Compared to unmodified SPR sensors, the sensitivity of the sensor decorated with TiO2 and Co(OH)2 nanosheets is increased by 130.84%, reaching 5764.27 nm/RIU. This enhancement is attributed to the high refractive index of the coating, as well as the high specific surface area and abundant active sites provided by the synthesized Co(OH)2 nanosheets with a multi-grooved structure. Additionally, employing a double-antibody sandwich method, the antibody-functionalized plasmonic interface enables specific detection of human serum albumin (HSA). The linear response of this sensor was in the wide range of 0.4-150 μM, and the LOD reached 154.89 nM(KD is approximately 1.73 × 10-6 M). This novel SPR sensor offers a new strategy for biochemical sensing and provides a highly sensitive platform for immunoassays.

GO/CNT-OH/Nafion Nanocomposite Humidity Sensor Based on the LC Wireless Method

In recent years, LC resonant sensors have gained widespread attention for their extensive applications in industries such as pharmaceutical storage and food transportation. A wireless passive sensor with a good sensing performance is proposed based on a GO/CNT-OH/Nafion nanocomposite. The sensor was fabricated via inkjet printing technology, and the surface morphology of the GO/CNT-OH/Nafion nanocomposite was characterized by SEM measurement. It is found that the MWCNTs support the GO layer and the hydrophobic chains of Nafion interact with the hydrophobic layer of GO, resulting in a larger cavity and hydrophilic surface of the entire material. This structure well reflects the fact that the mixing of MWCNTs and Nafion provides the entire material with a stronger water absorption. The experimental study shows that the proposed humidity sensor has a frequency variation of 103 kHz/%RH at low humidity (30-60% RH) and a sensitivity of 931 kHz/%RH at high humidity (60-95% RH), while the sensitivity value from 30-95% RH is 547 kHz/% RH. The response time and recovery time are 110 s and 115 s, respectively. In addition, the tests showed that the GO/CNT-OH/Nafion nanocomposite applied to the humidity sensor had a maximum humidity hysteresis of about 3% RH at 30-95% RH, the resonant frequency remained basically unchanged after 50 h of testing, and the whole sensor possessed a good stability. After conducting several repeated experiments, it was found that the resonant frequency error of the whole sensor was low and did not affect the overall sensing test, which proved the reproducible preparation of the sensor. Finally, the humidity-sensing mechanism of the proposed sensor was analyzed in this paper, and it was found that GO enhanced the hygroscopic properties of GO/CNT-OH/Nafion nanocomposite when it was supported by MWCNT-OH and included uniformly dispersed Nafion. Therefore, our proposed humidity sensor is suitable for humidity detection above 30% RH in both sealed and open environments.

Temperature Performance Study of SAW Sensors Based on AlN and AlScN

In this paper, the temperature performance of AlN-SAW resonators and AlScN-SAW resonators is studied. They are simulated by COMSOL Multiphysics, and their modes and the S11 curve are analyzed. The two devices were fabricated using MEMS technology and tested using VNA, and the test results were consistent with the simulation results. Temperature experiments were carried out with temperature control equipment. With the change in temperature, the changes in S11 parameters, TCF coefficient, phase velocity, and quality factor Q were analyzed. The results show that the temperature performance of the AlN-SAW resonator and the AlScN-SAW resonator is very good, and both have good linearity. At the same time, the sensitivity of the AlScN-SAW resonator is greater by 9.5%, the linearity is greater by 15%, and the TCF coefficient is greater by 11.1%. The temperature performance is excellent, and it is more suitable as a temperature sensor.

Development and Validation of an ANN-Based Approach for Temperature-Dependent Equivalent Circuit Modeling of SAW Resonators

In this paper, a novel approach is proposed for modeling the temperature-dependent behavior of a surface acoustic wave (SAW) resonator, by using a combination of a lumped-element equivalent circuit model and artificial neural networks (ANNs). More specifically, the temperature dependence of the equivalent circuit parameters/elements (ECPs) is modeled using ANNs, making the equivalent circuit model temperature-dependent. The developed model is validated by using scattering parameter measurements performed on a SAW device with a nominal resonant frequency of 423.22 MHz and under different temperature conditions (i.e., from 0 °C to 100 °C). The extracted ANN-based model can be used for simulation of the SAW resonator RF characteristics in the considered temperature range without the need for further measurements or equivalent circuit extraction procedures. The accuracy of the developed ANN-based model is comparable to that of the original equivalent circuit model.