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2D layered semiconductors with excellent light−matter interaction and atomic‐scale thickness have been envisioned as promising candidates for more than Moore and beyond Moore technologies. Here, for the first time, a multi‐functional platform is reported that is fabricated entirely from wrinkle‐free 2D ferroelectric semiconductor α‐In2Se3 integrated with a photodetector, reconfigurable logic switching, and visual perception processing functions. The intensity‐ and wavelength‐dependent resistance is used to demodulate broadband optical information into electrical signals and perform reconfigurable logic switching. Moreover, the platform offers dynamically modulated photosensitive visual sensing in different working modes at the pixel level. Using photo‐assisted piezoresponse force microscopy, the optical‐engineered ferroelectric polarization switch behavior is explored. The platform has excellent sensitivity to both optical and electrical stimuli and can respond to lights in the visible to short‐wavelength infrared region in volatile/non‐volatile manner under gate voltage modulation, with a response of 98 mA W−1 (to 1800 nm light), a current on/off ratio of over 106, and a high field‐effect mobility of 137.55 cm2 V−1 s−1. With its simple structure, unique photoelectric interaction, and controllable operating mechanism, the platform has the potential to simplify the complexity of neuromorphic computing circuitry systems, paving the way for high‐performance hybrid technologies suitable for artificial intelligence applications. [ABSTRACT FROM AUTHOR]

The functional differences between state-owned capital investment companies and production-oriented state-owned enterprises determine the need to reconstruct the performance evaluation system of state-owned capital specialized operation. Based on the goal of specialized operation of state-owned capital, this paper puts forward the ideas and principles of selecting performance indicators, and constructs the evaluation index system.

The algorithm used for reconstruction or resolution enhancement is one of the factors affecting the quality of super-resolution images obtained by fluorescence microscopy. Deep-learning-based algorithms have achieved state-of-the-art performance in super-resolution fluorescence microscopy and are becoming increasingly attractive. We firstly introduce commonly-used deep learning models, and then review the latest applications in terms of the network architectures, the training data and the loss functions. Additionally, we discuss the challenges and limits when using deep learning to analyze the fluorescence microscopic data, and suggest ways to improve the reliability and robustness of deep learning applications. [ABSTRACT FROM AUTHOR]

Corrosion behaviour of carbon steel (CS) exposed in the tidal zone of Beibu Gulf was investigated by experimental method. Q235 CS specimens were designed and exposed for 12 months. The corrosion mechanism of CS was characterised by scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS) and X-Ray diffraction (XRD). Results show that the corrosion performance of CS can be verified by the formula D = atn. The corrosion products are mainly composed of α-FeOOH, γ-FeOOH, β-FeOOH, Fe3O4 and γ-Fe2O3. Significantly, Cl– is an intermediate in the corrosion process and promotes the formation of the characteristic product β-FeOOH. [ABSTRACT FROM AUTHOR]

Neuromorphic visual sensory and memory systems that can sense, learn and memorize optical information have great potential in many areas such as image recognition and autonomous driving. However, most current artificial neuromorphic vision technology is suffering from large power consumptions (>100 pJ per switching), high circuitry complexity, and difficulty in miniaturization due to the physical separation of the optic sensing, processing, and memory units. Here, a photonic neuromorphic device based on WSe2/In2Se3 van der Waals (vdW) heterostructure is developed to meet the requirements of high‐performance photonic synapse devices. Owing to the optically controlled ferroelectric polarization switching, the device shows light‐tunable synaptic functions. For the first time, the light‐stimulated synaptic behavior extends from visible light to short‐wavelength infrared region (up to 1800 nm). Taking advantage of the ultra‐low dark current of the heterojunction, the power consumption of the photonic synapse can be as low as 258 fJ per switching under a bias of −0.1 V, comparable to biological synapses. These findings demonstrate a novel photonic synapse, deepen the understanding of light‐controlled polarization switching in semiconducting ferroelectric materials, and open up new application fields in multifunctional electronic and photonic devices based on 2D ferroelectric vdW heterostructures. [ABSTRACT FROM AUTHOR]