PH sensors based on a nanostructured ion-sensitive field-effect transistor have characteristics such as fast response, high sensitivity and miniaturization, and they have been widely used in biomedicine, food detection and disease monitoring. However, their performance is affected by many factors, such as gate dielectric material, channel material and channel thickness. In order to obtain a pH sensor with high sensitivity and fast response, it is necessary to determine the appropriate equipment parameters, which have high processing cost and long production time. In this study, a nanostructured ion-sensitive field-effect transistor was developed based on the SILVACO technology computer-aided design (TCAD) simulator. Through experiments, we analyzed the effects of the gate dielectric material, channel material and channel thickness on the electrical characteristics of the nanostructured field-effect transistor. Based on simulation results, silicon nitride was selected as the gate dielectric layer, while indium oxide was chosen as the channel layer. The structure and parameters of the dual channel ion-sensitive field-effect transistor were determined and discussed in detail. Finally, according to the simulation results, a pH sensor based on the nanostructured ion-sensitive field-effect transistor was fabricated. The accuracy of simulation results was verified by measuring the output, transfer and pH characteristics of the device. The fabricated pH sensor had a subthreshold swing as low as 143.19 mV/dec and obtained an actual sensitivity of 88.125 mV/pH. In addition, we also tested the oxidation reaction of hydrogen peroxide catalyzed by horseradish peroxidase, and the sensitivity was up to 144.26 pA mol⁻¹ L⁻¹, verifying that the ion-sensitive field-effect transistor (ISFET) can be used to detect the pH of micro solution, and then combine the enzyme-linked assay to detect the concentration of protein, DNA, biochemical substances, biomarkers, etc.

Paint coated corrosion detection and evaluation is a big challenge for steel performance and structure health. Eddy current pulsed thermography (ECPT) technique is investigated because it can reflect the corrosion physical properties through paint coating by the infrared signal. This paper proposes skewness method, which presents the feature of temperature curve’s shape automatically, and compares it with principal component analysis (PCA), phase analysis, and kurtosis feature extraction methods for paint coated corrosion characterization and evaluation. The averaged skewness shows the best sensitivity for 0–6 months corrosion. The normalized second principal component (PC) presents good sensitivity and the best measurement scale for corroded time. Furthermore, the temperature curve analysis proves that the electrical conductivity dominates the induced heating and heat distribution. The corrosion height is utilized to explain why ECPT technique is valid within 10 months corroded time. ECPT technique is proved as a smart sensor system for paint coated corrosion detection and characterization.

Online glucose monitoring during the fermentation process is critical for evaluating the microbial metabolism state and reaction course, achieving precise process control for industrial efficiency enhancement. However, the fast, wide-range and highly accurate test technique always presents a challenge for state-of-the-art analytical instruments. In this work, we proposed an online glucose analysis system based on a homemade screen-printed enzymatic biosensor chip composed of Prussian blue nanocubes with a high sensitivity of 83.404 mA mM ^-1 cm ^-2 . To match the detection behavior of this chip, a specific signal conversion system was designed to realize the highly precise acquisition and treatment of nA-level currents by integrating hardware acquisition circuits and Kalman filtering algorithms. Focusing on the continuous change in glucose concentration during fermentation, an adaptive injection strategy for the sampling volume was proposed to achieve an ultrawide linear range from 1 g/L to 180 g/L. The results show that the online analytical system exhibits excellent detection performance with high accuracy and low relative error of detection (<2%) during the fermentation of sophorolipid and ethanol compared to high performance liquid chromatography and commercial analyzers.