Based on nonfullerene IEICO-4F, ITCC and PC71BM acceptors, photo-carrier losses via bi-molecular recombination in organic solar cells (OSCs) with an ultra-narrow band gap are comparatively investigated with mid-gap OSCs.
An extensive and systematic calculation was performed to explore hierarchical cylindrical structures and the order-to-order transitions of AB diblock copolymers (f(A) = 0.3) on a saw-toothed substrate using self-consistent mean-field theory. We obtained fifteen relatively simple morphologies, including the existing morphologies observed experimentally and from simulations, and five more complicated structures, by varying the lateral periodicity of the substrate, the film thickness of diblock copolymers, the interaction between the A-block and the substrate and the tilt angles (or the shape) of the substrate. These structures show that the orientation and number of layers of cylinders can be tailored. Even lamellae and spherical microdomains were observed. Most interestingly, hierarchical structures are also observed, such as the morphology of C(ab)(//) within the upper cylinder perpendicular to the bottom cylinder, SC(b)(//) morphology that the upper is a cylinder but the bottom is a sphere. In addition, we discussed these complex hierarchical structures in detail and have analyzed the order-to-order transitions between the cylindrical morphologies with distinct orientations and layers.
Simple and efficient nanofabrication technology with low cost and high flexibility is indispensable for fundamental nanoscale research and prototyping. Lithography in the near field using the surface plasmon polariton (i.e., plasmonic lithography) provides a promising solution. The system with high stiffness passive nanogap control strategy on a high-speed rotating substrate is one of the most attractive high-throughput methods. However, a smaller and steadier plasmonic nanogap, new scheme of plasmonic lens, and parallel processing should be explored to achieve a new generation high resolution and reliable efficient nanofabrication. Herein, a parallel plasmonic direct-writing nanolithography system is established in which a novel plasmonic flying head is systematically designed to achieve around 15 nm minimum flying-height with high parallelism at the rotating speed of 8–18 m·s−1. A multi-stage metasurface-based polarization insensitive plasmonic lens is proposed to couple more power and realize a more confined spot compared with conventional plasmonic lenses. Parallel lithography of the nanostructures with the smallest (around 26 nm) linewidth is obtained with the prototyping system. The proposed system holds great potential for high-freedom nanofabrication with low cost, such as planar optical elements and nano-electromechanical systems.
Abstract Lane line detection based on deep learning has achieved good results in common scenarios. However, it is challenging to detect lane lines in extreme occlusion scenes where the visual clues are severely missing. To address this problem, we propose a novel method that leverages Vision Transformer (ViT) for de-occlusion and feature fusion. Specifically, we first design a ViT-based model to reconstruct the occluded lane lines from the input image. Then, we extract the feature map of the model and fuse it with the original image feature map. Finally, we use the fused feature map to detect the lane lines in a robust manner. Moreover, we introduce a sensitivity loss function that measures the error of each pixel and considers the coordinate difference between pixels. Experiments show that our sensitivity loss function can improve the performance of lane line detection. We evaluate our method on three benchmark datasets: TuSimple, CULane and CurveLanes. The results demonstrate that our method outperforms the existing methods in terms of accuracy and F1-score on all these datasets.
Cerium-modified Cu-SSZ-13 catalysts were prepared by an aqueous ion-exchange method, and Ce and Cu were incorporated through different ion-exchange sequences. The results of NH3-SCR activity evaluations displayed that Cu1(CeCu)2 catalyst presented excellent catalytic activity, and over 90% NOx conversion was obtained across the temperature range of 200–500 °C. The characterization results showed that the ion-exchange sequence of Cu and Ce species influenced the crystallinity of the zeolites and the coordination of Al. A small amount of Ce could participate in the reduction process and change the location and coordination environment of copper ions. Furthermore, Ce-modified Cu-SSZ-13 catalysts possessed more acidic sites due to their containing replacement of Ce and movement of Cu in the preparation process. The cooperation of strong redox abilities and NH3 storage capacity led to the increase of active adsorbed species adsorption and resulted in better activity of Cu1(CeCu)2.
Abstract High‐efficiency and low‐loss processing is the mainstay to reduce the cost and deepen the application of 4H silicon carbide (4H‐SiC) wafers in high‐power and high‐frequency electronics. In this study, the high‐yield slicing of 4H‐SiC wafers is realized by combining femtosecond laser irradiation and bandgap‐selective photo‐electrochemical (PEC) exfoliation. By combining light‐absorption measurements, micro‐Raman, and micro‐photoluminescence characterizations, it is found that the damage layer formed inside 4H‐SiC after femtosecond‐laser irradiation consists of amorphous silicon and amorphous carbon. This indicates that the femtosecond‐laser irradiation leads to phase separation in 4H‐SiC. The bandgap of the damage layer is 0.4 eV. Taking advantage of the different bandgap energies of the damage layer and the perfect 4H‐SiC region, the damage layer is removed from the perfect region of 4H‐SiC by using bandgap‐selective PEC etching. During the PEC etching, light‐generated holes can selectively oxidize and corrode the damaged layer with the assistance of the HF solution, and leave the upper and lower perfect 4H‐SiC layers being intact. The current work contributes to the development of the high‐yield and high‐throughput femtosecond laser slicing of 4H‐SiC wafers.
Eye tracking has emerged as a valuable tool for both research and clinical applications. However, traditional eye‐tracking systems are often bulky and expensive, limiting their widespread adoption in various fields. Smartphone eye tracking has become feasible with advanced deep learning and edge computing technologies. However, the field still faces practical challenges related to large‐scale datasets, model inference speed, and gaze estimation accuracy. The present study created a new dataset that contains over 3.2 million face images collected with recent phone models and presents a comprehensive smartphone eye‐tracking pipeline comprising a deep neural network framework (MGazeNet), a personalized model calibration method, and a heuristic gaze signal filter. The MGazeNet model introduced a linear adaptive batch normalization module to efficiently combine eye and face features, achieving the state‐of‐the‐art gaze estimation accuracy of 1.59 cm on the GazeCapture dataset and 1.48 cm on our custom dataset. In addition, an algorithm that utilizes multiverse optimization to optimize the hyperparameters of support vector regression (MVO–SVR) was proposed to improve eye‐tracking calibration accuracy with 13 or fewer ground‐truth gaze points, further improving gaze estimation accuracy to 0.89 cm. This integrated approach allows for eye tracking with accuracy comparable to that of research‐grade eye trackers, offering new application possibilities for smartphone eye tracking.
The photoluminescence quantum yield (PLQY) of blue-violet emission for CsPbCl3 quantum dots (QDs) is still low, which has limited its application in multi-colour displays.
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