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H doping can enhance the performance of ZnO thin-film transistors (TFTs) to a certain extent, and the design of double active layers is an effective way to further improve a device’s performance. However, there are few studies on the combination of these two strategies. We fabricated TFTs with ZnO:H (4 nm)/ZnO (20 nm) double active layers by magnetron sputtering at room temperature, and studied the effect of the hydrogen flow ratio on the devices’ performance. ZnO:H/ZnO-TFT has the best overall performance when H2/(Ar + H2) = 0.13% with a mobility of 12.10 cm2/Vs, an on/off current ratio of 2.32 × 107, a subthreshold swing of 0.67 V/Dec, and a threshold voltage of 1.68 V, which is significantly better than the performance of single active layer ZnO:H-TFTs. This exhibits that the transport mechanism of carriers in double active layer devices is more complicated. On one hand, increasing the hydrogen flow ratio can more effectively suppress the oxygen-related defect states, thus reducing the carrier scattering and increasing the carrier concentration. On the other hand, the energy band analysis shows that electrons accumulate at the interface of the ZnO layer close to the ZnO:H layer, providing an additional path for carrier transport. Our research exhibits that the combination of a simple hydrogen doping process and double active layer construction can achieve the fabrication of high-performance ZnO-based TFTs, and that the whole room temperature process also provides important reference value for the subsequent development of flexible devices.

We demonstrate the growth of ultra-thin (~5 nm) indium ytterbium oxide (In-Yb-O) thin film using a simple vacuum-free aqueous solution approach for the first time. The influences of Yb addition on the microstructural, chemical, optical, and electrical properties of In2O3 are well investigated. The analyses indicate that Yb dopant could suppress oxygen vacancy defects effectively owing to the lower standard electrode potential, lower electronegativity, and stronger metal-oxide bond strength than that of In. The optimized In-Yb-O thin-film transistors (TFTs) exhibit excellent electrical performance (mobility of 8 cm2/Vs and on/off ratio of ~108) and enhanced stability. The triumph of In-Yb-O TFTs is owing to the high quality In2O3 matrix, the remarkable suppressor of Yb, and the nanometer-thin and atomically smooth nature (RMS: ~0.26 nm) of channel layer. Therefore, the eco-friendly water-induced ultra-thin In-Yb-O channel provides an excellent opportunity for future large-scale and cost-effective electronic applications.

Thin-film transistors (TFTs) made of solution-processable transparent metal oxide semiconductors show great potential for use in emerging large-scale optoelectronics. However, current solution-processed metal oxide TFTs still suffer from relatively poor device performance, hindering their further advancement. In this work, we create a novel ultrathin crystalline indium–boron–oxide (In-B-O) channel layer for high-performance TFTs. We show that high-quality ultrathin (~10 nm) crystalline In-B-O with an atomically smooth nature (RMS: ~0.15 nm) could be grown from an aqueous solution via facile one-step spin-coating. The impacts of B doping on the physical, chemical and electrical properties of the In2O3 film are systematically investigated. The results show that B has large metal–oxide bond dissociation energy and high Lewis acid strength, which can suppress oxygen vacancy-/hydroxyl-related defects and alleviate dopant-induced carrier scattering, resulting in electrical performance improvement. The optimized In-B-O (10% B) TFTs based on SiO2/Si substrate demonstrate a mobility of ~8 cm2/(V s), an on/off current ratio of ~106 and a subthreshold swing of 0.86 V/dec. Furthermore, by introducing the water-processed high-K ZrO2 dielectric, the fully aqueous solution-grown In-B-O/ZrO2 TFTs exhibit excellent device performance, with a mobility of ~11 cm2/(V s), an on/off current of ~105, a subthreshold swing of 0.19 V/dec, a low operating voltage of 5 V and superior bias stress stability. Our research opens up new avenues for low-cost, large-area green oxide electronic devices with superior performance.

Black phosphorus (BP), a single elemental two-dimensional (2D) material with a sizable band gap, meets several critical material requirements in the development of future nanoelectronic applications. This work reports the ambipolar characteristics of few-layer BP, induced using 2D transparent hexagonal boron nitride (h-BN) capping. The 2D h-BN capping have several advantages over conventional Al2O3 capping in flexible and transparent 2D device applications. The h-BN capping technique was used to achieve an electron mobility in the BP devices of 73 cm2V−1s−1, thereby demonstrating n-type behavior. The ambipolar BP devices exhibited ultrafast photodetector behavior with a very high photoresponsivity of 1980 mA/W over the ultraviolet (UV), visible, and infrared (IR) spectral ranges. The h-BN capping process offers a feasible approach to fabricating n-type behavior BP semiconductors and high photoresponse BP photodetectors.

Thin-film transistors (TFTs) made of metal oxide semiconductors are now increasingly used in flat-panel displays. Metal oxides are mainly fabricated via vacuum-based technologies, but solution approaches are of great interest due to the advantages of low-cost and high-throughput manufacturing. Unfortunately, solution-processed oxide TFTs suffer from relatively poor electrical performance, hindering further development. Recent studies suggest that this issue could be solved by introducing a novel heterojunction strategy. This article reviews the recent advances in solution-processed heterojunction oxide TFTs, with a specific focus on the latest developments over the past five years. Two of the most prominent advantages of heterostructure oxide TFTs are discussed, namely electrical-property modulation and mobility enhancement by forming 2D electron gas. It is expected that this review will manifest the strong potential of solution-based heterojunction oxide TFTs towards high performance and large-scale electronics.

A high-performance solar-blind photodetector with a metal−semiconductor−metal structure was fabricated based on amorphous In-doped Ga2O3 thin films prepared at room temperature by radio frequency magnetron sputtering. The photodetector shows a high responsivity (18.06 A/W) at 235 nm with a fast rise time (4.9 μs) and a rapid decay time (230 μs). The detection range was broadened compared with an individual Ga2O3 photodetector because of In doping. In addition, the uneven In distribution at different areas in the film results in different resistances, which causes a quasi-Zener tunneling internal gain mechanism. The quasi-Zener tunneling internal gain mechanism has a positive impact on the fast response speed and high responsivity.

Sentinel-2 NDVI and surface reflectance time series have been widely used in various geoscience research, but the data is deteriorated or missing due to the cloud contamination, so it is necessary to reconstruct the Sentinel-2 NDVI and surface reflectance time series. At present, there are few studies on reconstructing the Sentinel-2 NDVI or surface reflectance time series, and these existing reconstruction methods have some shortcomings. We proposed a new method to reconstruct the Sentinel-2 NDVI and surface reflectance time series using the penalized least-square regression based on discrete cosine transform (DCT-PLS) method. This method iteratively identifies cloud-contaminated NDVI over NDVI time series from the Sentinel-2 surface reflectance data by adjusting the weights. The NDVI and surface reflectance time series are then reconstructed from cloud-free NDVI and surface reflectance using the adjusted weights as constraints. We have made some improvements to the DCT-PLS method. First, the traditional discrete cosine transformation (DCT) in the DCT-PLS method is matrix generated from discrete and equally spaced data, we reconfigured the DCT formulas to adapt for irregular interval time series, and optimized the control parameters N and s according to the typical vegetation samples in China. Second, the DCT-PLS method was deployed in the Google Earth Engine (GEE) platform for the efficiency and convenience of data users. We used the DCT-PLS method to reconstruct the Sentinel-2 NDVI time series and surface reflectance time series in the blue, green, red, and near infrared (NIR) bands in typical vegetation samples and the Zhangjiakou and Hangzhou study area. We found that this method performed better than the SG filter method in reconstructing the NDVI time series, and can identify and reconstruct the contaminated NDVI as well as surface reflectance with low root mean square error (RMSE) and high coefficient of determination (R2). However, in cases of a long range of cloud contamination, or above water surface, it may be necessary to increase the control parameter s for a more stable performance. The GEE code is freely available online and the link is in the conclusions of this article, researchers are welcome to use this method to generate cloudless Sentinel-2 NDVI and surface reflectance time series with 10 m spatial resolution, which is convenient for landcover classification and many other types of research.

As an important part of the Earth’s environmental system, sandy soils are particularly sensitive to changes in the climatic environment. As one of the four major desert regions in China, the MuUs desert has transformed from a desert to an oasis after more than half a century of ecological management. In this paper, we analyzed the spatial and temporal patterns of surface albedo, evapotranspiration, and fraction vegetation cover in the MuUs desert based on the Global Land Surface Satellite (GLASS) product with high spatial and temporal resolution and assessed the relationships between their variability and snow cover, air temperature, and precipitation. It is of great significance to understand the effect of desertification control and climate change after the conversion of land surface types in the MuUs region. The results show that the desertification control in the MuUs area has achieved remarkable results since 1982. The fraction vegetation coverage of the MuUs desert showed a significant increasing trend, with an interannual change rate of 1.32% each decade−1. The surface albedo of MuUs desert decreased significantly. Affected by vegetation and snow cover, it was lower in summer and higher in winter. The evapotranspiration showed a significant upward trend, higher in summer and lower in winter, which is significantly correlated with the changes in surface albedo, air temperature, and vegetation. In addition, the local-scale biophysical effects caused by vegetation change have influenced the climate of the MuUs region, manifested as the increase in precipitation and air temperature. In general, with the support of relevant policies and human construction projects, the overall ecological environment in the MuUs desert is developing in a good way.

Land surface temperature (LST) is a vital physical parameter in geoscience research and plays a prominent role in surface and atmosphere interaction. Due to technical restrictions, the spatiotemporal resolution of satellite remote sensing LST data is relatively low, which limits the potential applications of these data. An LST downscaling algorithm can effectively alleviate this problem and endow the LST data with more spatial details. Considering the spatial nonstationarity, downscaling algorithms have been gradually developed from least square models to geographical models. The current geographical LST downscaling models only consider the linear relationship between LST and auxiliary parameters, whereas non-linear relationships are neglected. Our study addressed this issue by proposing an LST downscaling algorithm based on a non-linear geographically weighted regressive (NL-GWR) model and selected the optimal combination of parameters to downscale the spatial resolution of a moderate resolution imaging spectroradiometer (MODIS) LST from 1000 m to 100 m. We selected Jinan city in north China and Wuhan city in south China from different seasons as study areas and used Landsat 8 images as reference data to verify the downscaling LST. The results indicated that the NL-GWR model performed well in all the study areas with lower root mean square error (RMSE) and mean absolute error (MAE), rather than the linear model.