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Anomalies in radio-frequency (rf) stations can result in unplanned downtime and performance degradation in linear accelerators such as SLAC’s Linac Coherent Light Source (LCLS). Detecting these anomalies is challenging due to the complexity of accelerator systems, high data volume, and scarcity of labeled fault data. Prior work identified faults using beam-based detection, combining rf amplitude and beam position monitor data. Due to the simplicity of the rf amplitude data, classical methods are sufficient to identify faults, but the recall is constrained by the low-frequency and asynchronous characteristics of the data. In this work, we leverage high-frequency, time-synchronous rf phase datamore » to enhance anomaly detection in the LCLS accelerator. Due to the complexity of phase data, classical methods fail, and we instead train deep neural networks within the Coincident Anomaly Detection (CoAD) framework. We find that applying CoAD to phase data detects nearly 3 times as many anomalies as when applied to amplitude data, while achieving broader coverage across rf stations. Furthermore, the rich structure of phase data enables us to cluster anomalies into distinct physical categories. Through the integration of auxiliary system status bits, we link clusters to specific fault signatures, providing additional granularity for uncovering the root cause of faults. We also investigate interpretability via Shapley values, confirming that the learned models focus on the most informative regions of the data and providing insight for cases where the model makes mistakes. This work demonstrates that phase-based anomaly detection for rf stations improves both diagnostic coverage and root cause analysis in accelerator systems and that deep neural networks are essential for effective analysis.« less

Two-dimensional (2D) van der Waals (vdW) heterostructures offer new platforms for exploring novel physics and diverse applications ranging from electronics and photonics to optoelectronics at the nanoscale. The studies to date have largely focused on transition-metal dichalcogenides (TMDCs) based samples prepared by mechanical exfoliation method, therefore it is of signi ficant interests to study high-quality vdW heterostructures using novel materials prepared by a versatile method. Here, we report a two-step vapor phase growth process for the creation of high-quality vdW heterostructures based on perovskites and TMDCs, such as 2D Cs₃Bi₂I₉/MoSe₂, with a large lattice mismatch. Supported by experimental and theoreticalmore » investigations, we discover that the Cs₃Bi₂I₉/MoSe₂ vdW heterostructure possesses hybrid band alignments consisting of type -I and type-II heterojunctions because of the existence of defect energy levels in Cs₃Bi₂I₉. More importantly, we demonstrate that the type-II heterojunction in the Cs₃Bi₂I₉/MoSe₂ vdW heterostructure not only shows a higher interlayer exciton density, but also exhibits a longer interlayer exciton lifetime than traditional 2D TMDCs based type-II heterostructures. We attribute this phenomenon to the reduced overlap of electron and hole wavefunctions caused by the large lattice mismatch. Finally, our work demonstrates that it is possible to directly grow high-quality vdW heterostructures based on entirely different materials which provide promising platforms for exploring novel physics and cutting-edge applications, such as optoelectronics, valleytronics, and high-temperature super fluidity.« less

Halide perovskites are revolutionizing the renewable energy sector owing to their high photovoltaic efficiency, low manufacturing cost, and flexibility. Their remarkable mobility and long carrier lifetime are also valuable for information technology, but fundamental challenges like poor stability under an electric field prevent realistic applications of halide perovskites in electronics. Here, it is discovered that valleytronics is a promising route to leverage the advantages of halide perovskites and derivatives for information storage and processing. The synthesized all-inorganic lead-free perovskite derivative, Cs₃Bi₂I₉, exhibits strong light-matter interaction and parity-dependent optically addressable valley degree of freedom. In this work, robust optical helicity inmore » all odd-layer-number crystals with inversion symmetry breaking is observed, indicating excitonic coherence extending well beyond 11 layers. The excellent optical and valley properties of Cs₃Bi₂I₉ arise from the unique parallel bands, according to first principles calculations. This discovery points to new materials design principles for scalable valleytronic devices and demonstrates the promise of perovskite derivatives beyond energy applications.« less

In this paper, we employ lithium-conducting covalent-organic-framework (COF) as the coating layer for silicon (Si) nanoparticles, which serve as artificial solid electrolyte interphase (SEI) for Si electrode. Here, the COF coating layer reduces the electrolyte decomposition, thus the coulombic efficiency (CE) and cycling stability of the Si electrodes are dramatically improved. Additionally, the superior lithium–ion conductivity of COF can enhance the lithium-ion transportation kinetics of Si electrode. COF coated Si presented a high specific capacity of 1864 mAh g^–1 at a high current density of 2000 mA g^–1 and high capacity retention of more than 60% after 1000 cycles.