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A low‐thermal‐budget fabrication approach is developed to realize high‐performance fluorine‐doped indium oxide (In2O3:F) thin‐film transistors (TFTs) with remarkable bias‐stress stability. The ultrathin transistor channel layer is prepared by a re‐developed atomic layer deposition (ALD) process of using cyclopentadienyl indium(I) (InCp) and O2 plasma to deposit a crystalline In2O3 film, followed by a new fluorine doping strategy to use CF4 plasma to afford the In2O3:F layer. As revealed by the density functional theory (DFT) analysis, the fluorine doping can stabilize the lattice oxygen and electrically passivate the problematic VO defects in In2O3 by forming the FOFi spectator defects. Therefore, the fabricated In2O3:F TFTs show simultaneously excellent electrical performance and remarkable bias‐stress stability, with high µFE of 35.9 cm2 V−1 s−1, positive Vth of 0.36 V, steep SS of 94.3 mV dec−1, small hysteresis of 33 mV, and small ΔVth of −111 and 49 mV under NBS and PBS, respectively. This work demonstrates the high promise of the fluorinated ALD In2O3:F TFTs for the CMOS back‐end‐of‐line (BEOL) compatible technologies toward advanced monolithic 3D integration. [ABSTRACT FROM AUTHOR]

The electroreduction of carbon dioxide (CO2) to multi‐carbon (C2+) compounds offers a viable approach for the up‐conversion of greenhouse gases into valuable fuels and feedstocks. Nevertheless, current industrial applications face limitations due to unsatisfactory conversion efficiency and high overpotential. Herein, a facile and scalable plasma fluorination method is reported. Concurrently, self‐evolution during CO2 electroreduction is employed to control the active sites of Cu catalysts. The copper catalyst modified with fluorine exhibits an impressive C2+ Faradaic efficiency (FE) of 81.8% at a low potential of −0.56 V (vs a reversible hydrogen electrode) in an alkaline flow cell. The presence of modified fluorine leads to the exposure and stabilization of high‐activity Cu+ species, enhancing the adsorption of *CO intermediates and the generation of *CHO, facilitating the subsequent dimerization. This results in a notably improved conversion efficiency of 13.1% and a significant reduction in the overpotential (≈100 mV) for the C2+ products. Furthermore, a superior C2+ FE of 81.6% at 250 mA cm−2, coupled with an energy efficiency of 31.0%, can be achieved in a two‐electrode membrane electrode assembly electrolyzer utilizing the fluorine‐modified copper catalyst. The strategy provides novel insights into the controllable electronic modification and surface reconstruction of electrocatalysts with practical potential. [ABSTRACT FROM AUTHOR]

The correct individual tree segmentation of the forest is necessary for extracting the additional information of trees, such as tree height, crown width, and other tree parameters. With the development of LiDAR technology, the research method of individual tree segmentation based on point cloud data has become a focus of the research community. In this work, the research area is located in an underground coal mine in Shenmu City, Shaanxi Province, China. Vegetation information with and without leaves in this coal mining area are obtained with airborne LiDAR to conduct the research. In this study, we propose hybrid clustering technique by combining DBSCAN and K-means for segmenting individual trees based on airborne LiDAR point cloud data. First, the point cloud data are processed for denoising and filtering. Then, the pre-processed data are projected to the XOY plane for DBSCAN clustering. The number and coordinates of clustering centers are obtained, which are used as an input for K-means clustering algorithm. Finally, the results of individual tree segmentation of the forest in the mining area are obtained. The simulation results and analysis show that the new method proposed in this paper outperforms other methods in forest segmentation in mining area. This provides effective technical support and data reference for the study of forest in mining areas.

Under the background of the ecological civilization era, rapidly obtaining coal mining information, timely assessing the ecological environmental impacts, and drafting different management and protection measures in advance to enhance the capacity of green mine construction have become the urgent technical problems to be solved at present. Simulating and analyzing mining subsidence is the foundation for a land reclamation plan. The Cellular Automata (CA) model provides a new tool for simulating the evolution of mining subsidence. This paper takes a mine in East China as a research area, analyses the methods and measures for developing a model of mining subsidence based on the theories of CA and mining technology, then discusses the results of simulation from different aspects. Through comparative analysis, it can be found that the predicted result is well consonant with the observation data. The CA model can simulate complex systems. The system of mining subsidence evolution CA is developed with the support of ArcGIS and Python, which can help to realize data management, visualization, and spatial analysis. The dynamic evolution of subsidence provides a basis for constructing a reclamation program. The research results show that the research methods and techniques adopted in this paper are feasible for the dynamic mining subsidence, and the work will continue to do in the future to help the construction of ecological civilization in mining areas.

The effects of post‐annealing on amorphous InGaZnO (a‐IGZO) TFTs with ultrathin atomic layer deposited (ALD) AlOxgate insulator (GI) were investigated. The non‐annealed devices exhibited uncontrollable gate leakage current while postannealing in either oxygen (O2) or nitrogen (N2) exhibited noticeable improvements. Optimizing O2‐annealed devices demonstrated the most optimal performance, including a low subthreshold swing of 61.6 mV/dec and a high on/off current ratio over 109. Capacitance‐voltage and X‐ray photoelectron spectroscopy analyses further revealed the underlying mechanism of defect elimination at the AlOx/a‐IGZO interface. [ABSTRACT FROM AUTHOR]

The development of machine vision demands accurate image capture under different lighting conditions, which is crucial for perceiving the environment correctly. In this paper, we present a human-eye-inspired sensor based on quasi-two-dimensional perovskite and indium gallium zinc oxide phototransistor array. The sensor exhibits a light detection limit as low as 6.1 nW/cm2 with a responsivity of 5 × 105 A/W, capable of perceiving light in visible spectrum range. It demonstrates light adaptation under both dim and illuminated conditions, enhancing the contrast between images and ambient light, while achieving a dynamic range of 162 dB. [ABSTRACT FROM AUTHOR]