The robust and automated determination of crystal symmetry is of utmost importance in material characterization and analysis. Recent studies have shown that deep learning (DL) methods can effectively reveal the correlations between X-ray or electron-beam diffraction patterns and crystal symmetry. Despite their promise, most of these studies have been limited to identifying relatively few classes into which a target material may be grouped. On the other hand, the DL-based identification of crystal symmetry suffers from a drastic drop in accuracy for problems involving classification into tens or hundreds of symmetry classes (e.g., up to 230 space groups), severely limiting its practical usage. Here, we demonstrate that a combined approach of shaping diffraction patterns and implementing them in a multistream DenseNet (MSDN) substantially improves the accuracy of classification. Even with an imbalanced dataset of 108,658 individual crystals sampled from 72 space groups, our model achieves 80.12 ± 0.09% space group classification accuracy, outperforming conventional benchmark models by 17–27 percentage points (%p). The enhancement can be largely attributed to the pattern shaping strategy, through which the subtle changes in patterns between symmetrically close crystal systems (e.g., monoclinic vs. orthorhombic or trigonal vs. hexagonal) are well differentiated. We additionally find that the MSDN architecture is advantageous for capturing patterns in a richer but less redundant manner relative to conventional convolutional neural networks. The proposed protocols in regard to both input descriptor processing and DL architecture enable accurate space group classification and thus improve the practical usage of the DL approach in crystal symmetry identification.
In this paper, a 20-GHz-band 64 × 64 hollow waveguide Butler matrix is proposed. By using two-plane short slot couplers and a modified diagram, a short-axis two dimensional Butler matrix is realized. The design method of the diagram and components is presented. The Butler matrix is composed of two plane hybrids, cross couplers and phase shifters. The designed Butler matrix is fabricated by milling and screwing together nine aluminum plates. The dimensions and weight are 86.40 mm × 74.19 mm × 396.34 mm and 7.0 kg, respectively. Transmission characteristics as a beam switching circuit are characterized by measurements, with a low insertion loss of less than 1.8 dB and an excitation error of 4-dB and 40-deg. standard deviation. Radiation characteristics as a 64-beam antenna are measured, and a wide coverage area of 40% of the hemisphere and high directivity of more than 18.7 dBi were determined by measurements. INDEX TERMS Butler matrix, hollow waveguide, two dimensional beam switching, two-plane short slot coupler.
Quantum‐dot (QD) photovoltaics (PVs) offer promise as energy‐conversion devices; however, their open‐circuit‐voltage (VOC) deficit is excessively large. Previous work has identified factors related to the QD active layer that contribute to VOC loss, including sub‐bandgap trap states and polydispersity in QD films. This work focuses instead on layer interfaces, and reveals a critical source of VOC loss: electron leakage at the QD/hole‐transport layer (HTL) interface. Although large‐bandgap organic materials in HTL are potentially suited to minimizing leakage current, dipoles that form at an organic/metal interface impede control over optimal band alignments. To overcome the challenge, a bilayer HTL configuration, which consists of semiconducting alpha‐sexithiophene (α‐6T) and metallic poly(3,4‐ethylenedioxythiphene) polystyrene sulfonate (PEDOT:PSS), is introduced. The introduction of the PEDOT:PSS layer between α‐6T and Au electrode suppresses the formation of undesired interfacial dipoles and a Schottky barrier for holes, and the bilayer HTL provides a high electron barrier of 1.35 eV. Using bilayer HTLs enhances the VOC by 74 mV without compromising the JSC compared to conventional MoO3 control devices, leading to a best power conversion efficiency of 9.2% (>40% improvement relative to relevant controls). Wider applicability of the bilayer strategy is demonstrated by a similar structure based on shallow lowest‐unoccupied‐molecular‐orbital (LUMO) levels.
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