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The uniformity and compactness of the surface of a viscoelastic sensitive film are among the most important factors that influence the characteristics of a surface acoustic wave (SAW) gas sensor, directly affecting the detection sensitivity of a SAW sensor on a target gas. In this paper, poly(epichlorohydrin) (PECH) with viscoelastic properties was used as sensitive film for the detection of 2-chloroethyl ethyl sulfide (CEES), a common simulant of the chemical agent mustard gas. Nanoscale films were prepared using a spin coating technology on a SAW delay line of 200 MHz. Films were evaluated using polarizing microscopy and atomic force microscopy and observed with uniform surface states and particle diameter in the cluster region of 4.52-5.22 μm. The interface parameters, including contact angle, surface tension, Gibbs free energy, work of adhesion, work of immersion, and spreading coefficient values were 9.31° to 39.63°, 22.475 to 29.945 mN m

A surface acoustic wave (SAW) temperature sensor with high accuracy was developed and wirelessly characterized in this work. The sensing chip with reflective delay line pattern was simulated using typical coupling of modes (COM) model and prepared by the standard photolithographic technique. Sharp reflection peaks with high signal-to-noise (SNR) were observed from the developed sensing chip operating at 433 MHz. Referring to the frequency-stepped continuous wave (FSCW)-based transceiver, planar antennas, and the developed SAW chip, the wireless and passive temperature sensor system was built. Adaptive Least Mean Square (LMS) algorithm was used for the first time in the SAW sensor signal processing to significantly improve the system SNR, and the corresponding phase fluctuation is down to only 3°. High temperature sensitivity of 36.5 °C and very high accuracy of ±0.2 °C in the range of −30 °C∼100 °C were achieved successfully by wireless measurement.

Baseline drift caused by slowly changing environment and other instability factors affects significantly the performance of gas sensors, resulting in reduced accuracy of gas classification and quantification of the electronic nose. In this work, a two-stage method is proposed for real-time sensor baseline drift compensation based on estimation theory and piecewise linear approximation. In the first stage, the linear information from the baseline before exposure is extracted for prediction. The second stage continuously predicts changing linear parameters during exposure by combining temperature change information and time series information, and then the baseline drift is compensated by subtracting the predicted baseline from the real sensor response. The proposed method is compared to three efficient algorithms and the experiments are conducted towards two simulated datasets and two surface acoustic wave sensor datasets. The experimental results prove the effectiveness of the proposed algorithm. Moreover, the proposed method can recover the true response signal under different ambient temperatures in real-time, which can guide the future design of low-power and low-cost rapid detection systems.

A Pd/Ni nanowires (NWs) film-coated surface acoustic wave (SAW) device is proposed for sensing hydrogen with fast response. The gas adsorption in Pd/Ni NW film modulates the conductivity, and perturbs the SAW velocity, and the corresponding changes in phase can be collected as the sensing signal. 200 MHz SAW device with delay line pattern is prepared by using the lithographic technique on Y35oX quartz substrate. The larger specific surface of Pd/Ni NW contributes well to improvement of the response time. By using anode-aluminum-oxide (AAO) template-confined electrodeposition, the Pd/Ni NWs have been prepared, then dissolved in ethanol and finally deposited on the surface of the SAW device by drop coating method to build the SAW hydrogen sensor. The developed SAW sensor is integrated in a phase discriminating circuit, and experimentally characterized. Fast response less than 2 s, high sensitivity of 1.65 mV/% (0.3–3.5 v/v % in nitrogen gas), and low detection limit of 7 ppm have been achieved at room temperature (25 ℃). Further, the developed sensors show excellent selectivity and stability. Also, the film thickness - and humidity - dependent sensing performance was studied.