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In this study, a highly crystalline and transparent indium-tin-oxide (ITO) thin film was prepared on a quartz substrate via RF sputtering to fabricate an efficient bottom-to-top illuminated electrode for an ultraviolet C (UVC) photodetector. Accordingly, the 26.6 nm thick ITO thin film, which was deposited using the sputtering method followed by post-annealing treatment, exhibited good transparency to deep-UV spectra (67% at a wavelength of 254 nm), along with high electrical conductivity (11.3 S/cm). Under 254 nm UVC illumination, the lead-halide-perovskite-based photodetector developed on the prepared ITO electrode in a vertical structure exhibited an excellent on/off ratio of 1.05 × 104, a superb responsivity of 250.98 mA/W, and a high specific detectivity of 4.71 × 1012 Jones without external energy consumption. This study indicates that post-annealed ITO ultrathin films can be used as electrodes that satisfy both the electrical conductivity and deep-UV transparency requirements for high-performance bottom-illuminated optoelectronic devices, particularly for use in UVC photodetectors.

Abstract Sunlight‐originated ultraviolet B (UVB) rays influence daily life in both beneficial and detrimental ways, depending upon light power and exposure time. Therefore, precise and timely UVB irradiance control is of great importance to humans. This study proposes a self‐powered and wearable zinc sulfide (ZnS) nanoparticle (NP)‐based UVB‐C detector for the in situ monitoring of UVB levels in ambient environments. The performance of the ZnS‐based photodetector can be markedly enhanced by constructing a vertical p‐n heterojunction for testing the feasibility of a self‐powered UVB‐C detector, employing a thin polyethylenimine (PEI) film for inhibiting current leakage and charge recombination, and introducing a poly(9,9‐dioctylfluorene‐alt‐N‐[4‐s‐butylphenyl]‐diphenylamine) (TFB) film as a hole transport layer to increase the photocurrent and enhance the response speed. In particular, we demonstrate that the ZnS NP/TFB junction in the device enables the direct monitoring of narrow and specific UVB bands from sunlight owing to its unique energy band structure and light absorption characteristics. The optimized device has a fast rise/fall time of 50/62 ms, high specific detectivity of 8.20 × 1010 Jones, and good stability over long‐term storage and against mechanical bending under 254‐nm light illumination. Our study provides new insights into self‐powered devices that can be implemented for the facile, precise, and rapid estimation of UVB levels under sunlight for various personal healthcare applications.

Recommendation systems based on convolutional neural network (CNN) have attracted great attention due to their effectiveness in processing unstructured data such as images or audio. However, a huge amount of raw data produced by data crawling and digital transformation is structured, which makes it difficult to utilize the advantages of CNN. This paper introduces a novel autoencoder, named Half Convolutional Autoencoder, which adopts convolutional layers to discover the high-order correlation between structured features in the form of Tag Genome, the side information associated with each movie in the MovieLens 20 M dataset, in order to generate a robust feature vector. Subsequently, these new movie representations, along with the introduction of users’ characteristics generated via Tag Genome and their past transactions, are applied into well-known matrix factorization models to resolve the initialization problem and enhance the predicting results. This method not only outperforms traditional matrix factorization techniques by at least 5.35% in terms of accuracy but also stabilizes the training process and guarantees faster convergence.