267 research outputs found

    Evidence of local superconductivity in granular Bi nanowires fabricated by electrodeposition

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    An unusual enhancement of resistance (i.e., superresistivity) below a certain characteristic temperature Tsr was observed in granular Bi nanowires. This superresistive state was found to be dependent on the applied magnetic field (H) as well as the excitation current (I). The suppression of Tsr by magnetic field resembles that of a superconductor. The observed superresistivity appears to be related to the nucleation of local superconductivity inside the granular nanowire without long-range phase coherence. The phenomenon is reminiscent of the Bose-insulator observed previously in ultra thin two-dimensional (2D) superconducting films and 3D percolative superconducting films.Comment: 11 pages, 5 figures. submitted to PR

    Metal-free photo-induced sulfidation of aryl iodide and other chalcogenation

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    A photo-induced C-S radical cross-coupling of aryl iodides and disulfides under transition-metal and external photosensitizer free conditions for the synthesis of aryl sulfides at room temperature has been presented, which features mild reaction conditions, broad substrate scope, high efficiency, and good functional group compatibility. The developed methodology could be readily applied to forge C-S bond in the field of pharmaceutical and material science

    Doublade: Unknown Vulnerability Detection in Smart Contracts Via Abstract Signature Matching and Refined Detection Rules

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    With the prosperity of smart contracts and the blockchain technology, various security analyzers have been proposed from both the academia and industry to address the associated risks. Yet, there does not exist a high-quality benchmark of smart contract vulnerability for security research. In this study, we propose an approach towards building a high-quality vulnerability benchmark. Our approach consists of two parts. First, to improve recall, we propose to search for similar vulnerabilities in an automated way by leveraging the abstract vulnerability signature (AVS). Second, to remove the false positives (FPs) due to AVS-based matching, we summarize the detection rules of existing tools and apply the refined rules by considering various defense mechanisms (DMs). By integrating AVS-based code matching and the refined detection rules (RDR), our approach achieves higher precision and recall. On the collected 76,354 contracts, we build a benchmark consisting of 1,219 vulnerabilities covering five different vulnerability types identified together by our tool (DOUBLADE) and other three scanners. Additionally, we conduct a comparison between DOUBLADE and the others, on an additional 17,770 contracts. Results show that DOUBLADE can yield a better detection accuracy with similar execution time
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