Synergistic Solar-Driven Freshwater Generation and Electricity Output Empowered by Wafer-Scale Nanostructured Silicon.

Electricity generation triggered by the ubiquitous water evaporation process provides an intriguing way to harvest energy from water. Meanwhile, natural water evaporation is also a fundamental way to obtain fresh water for human beings. Here, a wafer-scale nanostructured silicon-based device that takes advantage of its well-aligned configuration that simultaneously realizes solar steam generation (SSG) for freshwater collection and hydrovoltaic effect generation for electricity output is developed. An ingenious porous, black carbon nanotube fabric (CNF) electrode endows the device with sustainable water self-pumping capability, excellent durable conductivity, and intense solar spectrum harvesting. A combined device based on the CNF electrode integrated with nanostructured silicon nanowire arrays (SiNWs) provided an aligned numerous surface-to-volume water evaporation interface that enables a recorded continuous short-circuit current 8.65 mA and a water evaporation rate of 1.31 kg m-2 h-1 under one sun illumination. Such wafer-scale SiNWs-based SSG and hydrovoltaic integration devices would unchain the bottleneck of the weak and discontinuous electrical output of hydrovoltaic devices, which inspires other sorts of semiconductor-based hydrovoltaic device designs to target superior performance.

Colored Silicon Heterojunction Solar Cells Exceeding 23.5% Efficiency Enabled by Luminescent Down-Shift Quantum Dots.

Colored solar panels, realized by depositing various reflection layers or structures, are emerging as power sources for building with visual aesthetics. However, these panels suffer from reduced photocurrent generation due to the less efficient light harvesting from visible light reflection and degraded power conversion efficiency (PCE). Here, color-patterned silicon heterojunction solar cells are achieved by incorporating luminescent quantum dots (QDs) with high quantum yields as light converters to realize an asthenic appearance with high PCE. It is found that large bandgap (blue) QD layers can convert UV light into visible light, which can notably alleviate the parasitic absorption by the front indium tin oxide and doped amorphous silicon. Additionally, a universal optical path model is proposed to understand the light transmission process, which is suitable for luminescent down-shift devices. In this study, solar cells with a PCE exceeding 23.5% are achieved using the combination of a blue QD layer and a top low refractive index anti-reflection layer. Based on our best knoledge,the obtained PCE is the highest for a color-patterned solar cell. The results suggest an enhanced strategy involving incorporation of luminescent QDs with an optical path design for high-performance photovoltaic panels with visual aesthetics.

Revealing a Zinc Oxide/Perovskite Luminescence Quenching Mechanism Targeting Low-Roll-off Light-Emitting Diodes.

Balanced charge injection is key to achieving perovskite light-emitting diodes (PeLEDs) with a low efficiency roll-off at a high brightness. The use of zinc oxide (ZnO) with a high electron mobility as the charge transport layers is desirable; however, photoluminescence (PL) quenching of a perovskite on ZnO always occurs. Here, a quasi-two-dimensional perovskite on ZnO is explored to uncover the PL quenching mechanism, mainly ascribed to the deprotonation of ammonium cations on the ZnO film in association with the decomposition of low-dimensional perovskite phases. Surprisingly, crystal plane-dependent PL quenching results indicate that the deprotonation rate strongly correlates with the crystal orientation of the ZnO surface. We developed a strategy for suppressing perovskite PL quenching by incorporating an atomic layer deposited Al2O3 onto the ZnO film. Consequently, an efficient inverted PeLED was achieved with a maximum external quantum efficiency of 17.7% and a less discernible efficiency roll-off at a high current density.

Intelligent Recognition of Hospital Image Based on Deep Learning: The Relationship between Adaptive Behavior and Family Function in Children with ADHD.

Chronic diseases are gradually becoming the main threat to human health. By designing an efficient hospital management platform to quickly identify the corresponding chronic diseases, it can effectively reduce the labor cost, improve the accuracy of disease identification, and improve treatment efficiency. ADHD is a common behavioral disorder in school-age children, and it is also one of the most common chronic health problems in this period. The internationally recognized prevalence of ADHD is 3%-9%. ADHD often brings adverse effects on children's life and studying and at the same time increases difficulties for their families. Therefore, this paper designs an intelligent management platform for public hospitals based on a deep learning algorithm, evaluates the current situation and influencing factors of ADHD children through the child adaptive behavior scale and the family function assessment scale, and designs its intelligent platform by using a new technology of fNIRS. According to the nonlinearity and unsteadiness of the fNIRS signal, this paper proposes a motion noise removal method based on EMD algorithm methods: to automatically identify children with ADHD and improve the cognitive function of children with ADHD by intervention technology. The data are from the outpatients of the Department of Child Psychology of the First People's Hospital of Tianshui City in Gansu Province in 2018. The results showed that there were significant differences in the adaptive behavior scale (CABS) and fad scores between the two groups. In the seven dimensions of family function, there were significant differences between the two groups (P < 0.01). fNIRS management platform can effectively identify ADHD patients with high recognition accuracy. The intelligent management platform can significantly reduce the number of physical examination personnel, prolong the diagnosis and treatment time, reduce a lot of repetitive work, and improve the efficiency of diagnosis and treatment. At the same time, this technology also provides great help for better research and improvement of ADHD patients and provides a reference for the information intelligent construction of modern hospitals.