The pursuit of designing superconductors with high Tc has been a long-standing endeavor. However, the widespread incorporation of doping in high Tc superconductors significantly impacts electronic structure, intricately influencing Tc. The complex interplay between the structural composition and material performance presents a formidable challenge in superconductor design. Based on a novel generative model, diffusion model, and doping adaptive representation: three-channel matrix, we have designed a high Tc superconductors inverse design model called Supercon-Diffusion. It has achieved remarkable success in accurately generating chemical formulas for doped high Tc superconductors. Supercon-Diffusion is capable of generating superconductors that exhibit high Tc and excels at identifying the optimal doping ratios that yield the peak Tc. The doping effectiveness (55%) and electrical neutrality (55%) of the generated doped superconductors exceed those of traditional GAN models by more than tenfold. Density of state calculations on the structures further confirm the validity of the generated superconductors. Additionally, we have proposed 200 potential high Tc superconductors that have not been documented yet. This groundbreaking contribution effectively reduces the search space for high Tc superconductors. Moreover, it successfully establishes a bridge between the interrelated aspects of composition, structure, and property in superconductors, providing a novel solution for designing other doped materials.
Quantitative analysis of gait parameters, such as stride frequency and step speed, is essential for optimizing physical exercise for the human body. However, the current electronic sensors used in human motion monitoring remain constrained by factors such as battery life and accuracy. This study developed a self-powered gait analysis system (SGAS) based on a triboelectric nanogenerator (TENG) fabricated electrospun composite nanofibers for motion monitoring and gait analysis for regulating exercise programs. The SGAS consists of a sensing module, a charging module, a data acquisition and processing module, and an Internet of Things (IoT) platform. Within the sensing module, two specialized sensing units, TENG-S1 and TENG-S2, are positioned at the forefoot and heel to generate synchronized signals in tandem with the user's footsteps. These signals are instrumental for real-time step count and step speed monitoring. The output of the two TENG units is significantly improved by systematically investigating and optimizing the electrospun composite nanofibers' composition, strength, and wear resistance. Additionally, a charge amplifier circuit is implemented to process the raw voltage signal, consequently bolstering the reliability of the sensing signal. This refined data is then ready for further reading and calculation by the micro-controller unit (MCU) during the signal transmission process. Finally, the well-conditioned signals are wirelessly transmitted to the IoT platform for data analysis, storage, and visualization, enhancing human motion monitoring.
Silver nanowire (AgNW) networks hold great promises as next-generation flexible transparent electrodes (FTEs) for high-performance flexible optoelectronic devices. However, achieving large-area flexible AgNW network electrodes with low sheet resistance, high optical transmittance, and a smooth surface remains a grand challenge. Here, we report a straightforward and cost-effective roll-to-roll method that includes interface assembly/wetting-induced climbing transfer, nanowelding, and washing processess to fabricate flexible ordered layered AgNW electrodes with high network uniformity. By manipulating the stacking number of the interfacially assembled AgNW monolayer, we can precisely tailor and balance the transparency and the conductivity of the electrodes, achieving an exceptional Figure of Merit (FoM) value of 862. Moreover, the ordered layered structure enhances surface smoothness, compared with randomly arranged structures. To highlight the potential of these ordered layered AgNW network electrodes in flexible optoelectronic devices, we successfully employ them as highly sensitive strain sensors, large-area flexible touch screens, and flexible smart windows. Overall, this work represents a substantial advance toward high-performance FTEs over large areas, opening up exciting opportunities for the development of advanced optoelectronic devices.
The inherent unpredictability of the maritime environment leads to low rates of survival during accidents. Life jackets serve as a crucial safety measure in underwater environments. Nonetheless, most conventional life jackets lack the capability to monitor the wearer's underwater body movements, impeding their effectiveness in rescue operations. Here, we present an intelligent self-powered life jacket system (SPLJ) composed of a wireless body area sensing network, a set of deep learning analytics, and a human condition detection platform. Six coaxial core-shell structure triboelectric fiber sensors with high sensitivity, stretchability, and flexibility are integrated into this system. Additionally, a portable integrated circuit module is incorporated into the SPLJ to facilitate real-time monitoring of the wearer's movement. Moreover, by leveraging the deep-learning-assisted data analytics and establishing a robust correlation between the wearer's movements and condition, we have developed a comprehensive system for monitoring drowning individuals, achieving an outstanding recognition accuracy of 100%. This groundbreaking work introduces a fresh approach to underwater intelligent survival devices, offering promising prospects for advancing underwater smart wearable devices in rescue operations and the development of ocean industry.
Due to their unique photoelectric properties, nontoxic tin-based perovskites are emerging candidates for efficient near-infrared LEDs. However, the facile oxidation of Sn2+ and the rapid crystallization rate of tin-based perovskites result in suboptimal film quality, leading to inferior efficiencies of tin-based perovskite light-emitting diodes (Pero-LEDs). In this study, we investigate the influence of commonly used solvents on the quality of the CsSnI3 films. Remarkably, DMSO exhibits a stronger interaction with SnI2, forming a stable intermediate phase of SnI2·3DMSO. This intermediate effectively inhibits the oxidation of Sn2+ and slows down the crystallization rate, bringing in lower defect state density and higher photoluminescence quantum yield of the prepared perovskite films. Consequently, the corresponding Pero-LEDs achieve a maximum external quantum efficiency (EQE) of 5.6%, among the most efficient near-infrared Pero-LEDs. In addition, the device processes ultra-low efficiency roll-off and high reproducibility. Our research underscores the crucial role of solvent-perovskite coordination in determining film quality. These findings offer valuable guidance for screening solvents to prepare highly efficient and stable tin-based perovskites.
The regulation of carrier generation and transport by Schottky junctions enables effective optoelectronic conversion in optoelectronic devices. A simple and general strategy to spontaneously generate photocurrent is of great significance for self-powered photodetectors but is still being pursued. Here, we propose that a photocurrent can be induced at zero bias by the transmittance contrast of MXene electrodes in MXene/semiconductor Schottky junctions. Two MXene electrodes with a large transmittance contrast (84%) between the thin and thick zones were deposited on the surface of a semiconductor wafer using a simple and robust solution route. Kelvin probe force microscopy tests indicated that the photocurrent at zero bias could be attributed to asymmetric carrier generation and transport between the two Schottky junctions under illumination. As a demonstration, the MXene/GaN ultraviolet (UV) photodetector exhibits excellent performance superior to its counterpart without transmittance contrast, including high responsivity (81 mA W–1), fast response speed (less than 31 and 29 ms) and ultrahigh on/off ratio (1.33 × 106), and good UV imaging capability. Furthermore, this strategy has proven to be universal for first- to third-generation semiconductors such as Si and GaAs. These results provide a facile and cost-effective route for high-performance self-powered photodetectors and demonstrate the versatile and promising applications of MXene electrodes in optoelectronics.
Near-infrared (NIR) luminescent metal halide (LMH) materials have attracted great attention in various optoelectronic applications due to their low-temperature solution-processable synthesis, abundant crystallographic/electronic structures, and unique optoelectronic properties. However, some challenges still remain in their luminescence design, performance improvement, and application assignments. This review systematically summarizes the development of NIR LMHs through classifying NIR luminescent origins into four major categories: band-edge emission, self-trapped exciton (STE) emission, ion emission, and defect-related emission. The luminescence mechanisms of different types of NIR LMHs are discussed in detail by analyzing typical examples. Reasonable strategies for designing and optimizing luminescence/optoelectronic properties of NIR LMHs are summarized, including bandgap engineering, self-trapping state engineering, chemical composition modification, energy transfer, and other auxiliary strategies such as improvement of synthesis scheme and post-processing. Furthermore, application prospects based on the optoelectronic devices are revealed, including phosphor-converted light-emitting diodes (LEDs), electroluminescent LEDs, photodetectors, solar cells, and x-ray scintillators, as well as demonstrations of some related practical applications. Finally, the existing challenges and future perspectives on the development of NIR LMH materials are critically proposed. This review aims to provide general understanding and guidance for the design of high-performance NIR LMHs materials.