Despite the popularity of capacitive sensors, limited research exists on their behavior underwater, which can be significantly different than those in air. This letter aims to address this gap by exploring the relationship between capacitance and lift-off distances. Through a combination of experimental investigations and numerical modeling, we identified a novel sensor phenomenon wherein capacitance exhibits a local maximum in response to incremental changes in distance. This resulted in a region with high capacitive sensitivity to distance. We modeled this phenomenon as dielectric losses in water and provided insights into its underlying mechanisms by analyzing capacitance in terms of its real and imaginary terms. We hope our study provides useful insights for future research and engineering applications for capacitive sensors underwater.

This letter presents a simulation report on a modern, power-efficient, steep subthreshold slope (SS) electron-hole bilayer tunnel field-effect transistor (EHB-TFET) as an ion sensor. The effect of variation in channel thickness and work function engineering (of both top and bottom gates) on the transversal electron tunneling rate and I _DS –V _GS characteristics is also discussed. At optimized values, the EHB-TFET results in low I _off (=10 ⁻¹⁸ A/μm) and SS of 13 mV/dec. The Gouy–Chapman–Stern and the site-binding model form the basis for assessing EHB-TFET's sensing mechanism. The top gate is assumed to be the controlling gate, and as the bottom gate insulator, along with SiO ₂ , the sensitivity response of ZrO ₂ and Ta ₂ O ₅ is also examined. The sensitivity behavior is evaluated in terms of threshold voltage, and it was observed that sensitivity is directly proportional to the surface potential. The highest sensitivity obtained is for ZrO ₂ followed by SiO ₂ and Ta ₂ O ₅ . Due to the evident advantages of EHB-TFET in the near future, it can be used as a low-power, quick-responsive, reliable ion sensor and can be used to replace conventional industrial sensors.

In oceanic environments, compact underwater drones must determine their positional information, including water depth, to move autonomously because wireless communication underwater is challenging. However, current bathymetric sensors often lack high accuracy, energy efficiency, and cost-effectiveness. We propose a spherical bathymetric sensor that uses multiple absolute pressure sensor elements, allowing precise water depth measurement without being affected by dynamic pressure caused by waterflow as well as offering low energy consumption and cost-effectiveness. This sensor has a spherical design with 12 absolute pressure sensor elements arranged in a regular dodecahedron, connected by a flexible Kiri-origami circuit. The water depth is determined by compensating for waterflow-induced error using sensor data and linear regression. We evaluated our method using both simulations and experiments. The sensor reduced waterflow-induced errors to within 7.5 mm in simulations and 5 mm in a water tunnel at a speed of 2.0 m/s. By comparison, conventional methods without error compensation showed errors exceeding 100 mm under the same conditions. The sensor was also validated to predict depth at different depths, resulting in a 6.5 mm error. These results suggest that our proposed sensor can effectively measure water depth for compact underwater drones.

This letter demonstrates the fabrication of a temperature optical sensor by printing the corresponding sensitive optical waveguide directly onto a flexible flat substrate. The printed waveguide was carried out using a coaxial needle and an electrohydrodynamic (EHD) machine. The fluorescent organic compound, rhodamine B, was used for doping the core of the printed waveguide as temperature sensible dye. The optical sensitive waveguide manufactured is compact, ensuring coupling with the input and output optical fibers. The response of the printed optical sensor was evaluated to temperature variations by measurement of both, the peak intensity and the wavelength of the fluorescence spectra. The experimental characteristic and sensitivity of the sensor were obtained.

Nonthermal atmospheric-pressure discharge plasma is considered important for sterilization. Reactive species, such as active oxygen species, radicals, and nitrate ions, generated by the discharge plasma damage the target bacterial cell wall/membrane and DNA. Several plasma sterilization methods have been proposed, including dielectric barrier discharge (DBD). To achieve effective sterilization, it is necessary to evaluate their characteristics using many parameters. This letter aims to demonstrate a proof-of-concept of a novel biological indicator for plasma sterilization. A biological indicator is used to verify sterilization outcomes. We employ DNA-labeled microbeads as biological indicators for the rapid visualization of plasma sterilization. This is based on our recently developed method for visual detection of DNA molecules. If plasma-derived factors cause the degradation of the DNA attached to the microbeads, this can be confirmed by visualization. Herein, we present the correlation between sterilization and visualization in the case of DBD. This method offers a rapid evaluation of plasma sterilization because it easily and quickly determines the sterilization capability of the plasma.

This letter presents a dual-mode continuous and discrete time-gain compensation (TCG) ultrasound receive system implemented in a 180 nm CMOS process. In this system, when the received ultrasound signal exhibits sufficient strength, the bypass switch activates, effectively shorting the variable gain amplifier (VGA) stage. Simultaneously, the analog-to-digital converter (ADC) reconfigures the capacitive digital-to-analog converter (CDAC) array to compensate for the SNR. Conversely, when the received ultrasound signal exceeds the compensation range of the ADC, the bypass switch deactivates, and the continuous VGA stage takes over for signal compensation. Measurement results demonstrate that this ultrasound receive system achieves a total dynamic range of 92.2 dB and offers a time-gain compensation range of 38.18 dB with a supply voltage of 1.8 V. The system's power consumption is 16.24 mW.

To realize the selection and accuracy simulation deduction of inertial devices in rotational inertial navigation systems, a simulation method of stochastic characteristics of inertial devices based on Allan variance matching was proposed. To enhance the global matching performance of the Allan variance curve, a parameter optimization scheme based on improved genetic algorithm and an adaptive variable weight evaluation method is employed. Finally, compared with the data generated by the optimal parameters of the traditional empirical stochastic model, the root-mean-square error of the Allan variance curve of the data generated by proposed method and the Allan variance curve of the actual device data are increased from 0.0101 to 0.0018, while the correlation coefficient is increased from 0.91 to 0.9905. The Monte Carlo simulation analysis and the comparison of the measured data demonstrate the feasibility of the method for the evolution of navigation performance and device selection of the rotational inertial navigation system.

This research addresses the intricate challenge of self-noise cancellation (SNC) in towed array SONAR, particularly when confronting adverse conditions where both the target and self-noise exhibit broadband characteristics containing the same frequencies. Further earlier efforts in SNC (Kumar and Nathwani 2023), (Kumar et al., 2023) predominantly focused on narrowband targets and self-noise with the different frequencies. To tackle this issue, we employ a 1-D convolutional autoencoder in both supervised and semisupervised modes for SNC. In the supervised approach, we map the noisy data to the clean data; however, obtaining clean data in real-world environments is challenging. Therefore, we suggest a semisupervised approach that maps the noisy data with the recovered data derived from the null-space projection method, utilizing singular value decomposition. Our experimental results are presented in terms of the output signal-to-interference noise ratio, quantifying the difference between the power at the target bearing and the self-noise bearing following the application of SNC. The evaluation involves variations in the standard deviation of ambient noise in training and test data.