We investigated the influence of low-concentration indium (In) doping on the chemical and structural properties of solution-processed zinc oxide (ZnO) films and the electrical characteristics of bottom-gate/top-contact In-doped ZnO thin-film transistors (TFTs). The thermogravimetry and differential scanning calorimetry analysis results showed that thermal annealing at 400 °C for 40 min produces In-doped ZnO films. As the In content of ZnO films was increased from 1% to 9%, the metal-oxygen bonding increased from 5.56% to 71.33%, while the metal-hydroxyl bonding decreased from 72.03% to 9.63%. The X-ray diffraction peaks and field-emission scanning microscope images of the ZnO films with different In concentrations revealed a better crystalline quality and reduced grain size of the solution-processed ZnO thin films. The thickness of the In-doped ZnO films also increased when the In content was increased up to 5%; however, the thickness decreased on further increasing the In content. The field-effect mobility and on/off current ratio of In-doped ZnO TFTs were notably affected by any change in the In concentration. Considering the overall TFT performance, the optimal In doping concentration in the solution-processed ZnO semiconductor was determined to be 5% in this study. These results suggest that low-concentration In incorporation is crucial for modulating the morphological characteristics of solution-processed ZnO thin films and the TFT performance.

We investigated the effects of gallium (Ga) and tin (Sn) compositions on the structural and chemical properties of Ga–Sn-mixed (Ga:Sn) oxide films and the electrical properties of Ga:Sn oxide thin-film transistors (TFTs). The thermogravimetric analysis results indicate that solution-processed oxide films can be produced via thermal annealing at 500 °C. The oxygen deficiency ratio in the Ga:Sn oxide film increased from 0.18 (Ga oxide) and 0.30 (Sn oxide) to 0.36, while the X-ray diffraction peaks corresponding to Sn oxide significantly reduced. The Ga:Sn oxide film exhibited smaller grains compared to the nanocrystalline Sn oxide film, while the Ga oxide film exhibited an amorphous morphology. We found that the electrical properties of TFTs significantly improve by mixing Ga and Sn. Here, the optimum weight ratio of the constituents in the mixture of Ga and Sn precursor sols was determined to be 1.0:0.9 (Ga precursor sol:Sn precursor sol) for application in the solution-processed Ga:Sn oxide TFTs. In addition, when the Ga(1.0):Sn(0.9) oxide film was thermally annealed at 900 °C, the field-effect mobility of the TFT was notably enhanced from 0.02 to 1.03 cm²/Vs. Therefore, the mixing concentration ratio and annealing temperature are crucial for the chemical and morphological properties of solution-processed Ga:Sn oxide films and for the TFT performance.

Metal-oxide thin-film transistors (TFTs) have been developed as promising candidates for use in various electronic and optoelectronic applications. In this study, we fabricated bilayer zinc oxide (ZnO)/indium oxide (In₂O₃) TFTs by using the sol-gel solution process, and investigated the structural and chemical properties of the bilayer ZnO/In₂O₃ semiconductor and the electrical properties of these transistors. The thermogravimetric analysis results showed that ZnO and In₂O₃ films can be produced by the thermal annealing process at 350 °C. The grazing incidence X-ray diffraction patterns and X-ray photoemission spectroscopy results revealed that the intensity and position of characteristic peaks related to In₂O₃ in the bilayer structure were not affected by the underlying ZnO film. On the other hand, the electrical properties, such as drain current, threshold voltage, and field-effect mobility of the bilayer ZnO/In₂O₃ TFTs obviously improved, compared with those of the single-layer In₂O₃ TFTs. Considering the energy bands of ZnO and In₂O₃, the enhancement in the TFT performance is explained through the electron transport between ZnO and In₂O₃ and the formation of an internal electric field in the bilayer structure. In the negative gate-bias stress experiments, it was found that the internal electric field contributes to the electrical stability of the bilayer ZnO/In₂O₃ TFT by reducing the negative gate-bias-induced field and suppressing the trapping of holes in the TFT channel. Consequently, we suggest that the bilayer structure of solution-processed metal-oxide semiconductors is a viable means of enhancing the TFT performance.

This paper presents a failure prediction model using iterative feature selection, which aims to accurately predict the failure occurrences in industrial Internet of Things (IIoT) environments. In general, vast amounts of data are collected from various sensors in an IIoT environment, and they are analyzed to prevent failures by predicting their occurrence. However, the collected data may include data irrelevant to failures and thereby decrease the prediction accuracy. To address this problem, we propose a failure prediction model using iterative feature selection. To build the model, the relevancy between each feature (i.e., each sensor) and the failure was analyzed using the random forest algorithm, to obtain the importance of the features. Then, feature selection and model building were conducted iteratively. In each iteration, a new feature was selected considering the importance and added to the selected feature set. The failure prediction model was built for each iteration via the support vector machine (SVM). Finally, the failure prediction model having the highest prediction accuracy was selected. The experimental implementation was conducted using open-source R. The results showed that the proposed failure prediction model achieved high prediction accuracy.