Indium tin zinc oxide (ITZO) thin-film transistors (TFTs) with different channel structures are investigated. The electrical performance and bias stress stability of bilayer-channel ITZO TFTs are enhanced in comparison with those of single-channel ITZO TFTs. The bilayer channel consists of an oxygen-uncompensated channel layer and an oxygen-compensated capping layer, while the single channel is an oxygen-uncompensated channel layer. The electrical properties of the bilayer-channel films are fine-tuned by adjusting their oxygen stoichiometry using the oxygen-compensated capping layer. The X-ray photoelectron spectroscopy measurements reveal that the bilayer channel shows advantages over the single channel in terms of increased metal oxide concentration and decreased oxygen vacancy and hydroxyl concentration. As a result, the bilayer-channel ITZO TFT exhibits a saturation field-effect mobility of 17.31 cm2/Vs, a sub-threshold swing of 0.24 V/dec, and a good operational bias stress stability in comparison with the single-channel TFT. This work demonstrates that the bilayer-channel ITZO TFTs have great potential for next-generation display applications.

Oxide semiconductor thin‐film transistors (TFTs) with low‐voltage operation, excellent device performance, and bias stability are highly desirable for portable and wearable electronics. Here, the development of low‐voltage indium‐tin‐zinc‐oxide (ITZO) TFTs with excellent device performance and bias stability based on a dual‐channel layer and an anodic‐oxide dielectric layer are reported. An ultra‐thin anodic AlxOy film as a gate dielectric layer is prepared using an anodization process. The dual‐channel layer consists of an oxygen‐uncompensated channel layer and an oxygen‐compensated capping layer. It is confirmed that the dual‐channel structure is effective for enhancing device performance and bias stability in comparison with the single‐channel structure. As a result, the dual‐channel ITZO TFT gated with anodic AlxOy exhibits an effective saturation mobility of 12.56 cm2 Vs−1, a threshold voltage of 0.28 V, a subthreshold swing of 76 mV dec−1, a low‐voltage operation of 1 V, and good operational stability (threshold voltage shift (ΔVTH) < −0.03 V under a negative gate bias stress and ΔVTH < 0.15 under positive gate bias stress of 3600 s). The work shows that the ITZO TFTs, based on a dual‐channel layer and an anodic‐oxide gate dielectric layer, have great potential for low‐power, portable, and wearable electronics.

The potential applications of silicon microwire materials in monitoring gases have not been fully exploited. Uniform silicon vertical microwire arrays (Si VMWA) are fabricated using a metal-assisted chemical etching process after optimizing the conditions. The characteristics and responses of Si VMWA-based sensors with different diameters to ammonia gas (NH3) are investigated in both air and nitrogen environments. The sensing mechanism of the sensor to NH3 is discussed to clarify the response in different environments. The sensor exhibits a linear response to a wide range of NH3 concentrations (4%@2 ppm–122%@500 ppm) at room temperature and even shows a distinct response at 200 ppb of NH3. In addition, it demonstrates great repeatability/reversibility and moderate selectivity to ammonia gas against other gases (nitrogen dioxide, toluene, and isobutane). Furthermore, machine learning-based principal component analysis and random forest algorithms enable us to discriminate NH3 from other possible interfering gases and predict gas concentration with an accuracy of over 95%. Thus, our approach using the Si VMWA-based sensor with machine learning-based data analysis represents a significant step toward the environmental sensing of specific chemical analytes in the household and industries.

A highly sensitive and flexible gas sensor that can detect a wide range of chemicals is crucial for wearable applications. However, conventional single resistance-based flexible sensors face challenges in maintaining chemical sensitivity under mechanical stress and can be affected by interfering gases. This study presents a versatile approach for fabricating a micropyramidal flexible ion gel sensor, which accomplishes sub-ppm sensitivity (<80 ppb) at room temperature and discrimination capability between various analytes, including toluene, isobutylene, ammonia, ethanol, and humidity. The discrimination accuracy of our flexible sensor is as high as 95.86%, enhanced by using machine learning-based algorithms. Moreover, its sensing capability remains stable with only a 2.09% change from the flat state to a 6.5 mm bending radius, further amplifying its universal usage for wearable chemical sensing. Therefore, we envision that a micropyramidal flexible ion gel sensor platform assisted by machine learning-based algorithms will provide a new strategy toward next-generation wearable sensing technology.