Micrometer thick soft magnetic films with magnetic moments restricted strictly in plane by negative magnetocrystalline anisotropy

Stripe domains or any other type domain structures with part of their magnetic moments deviating from the film plane, which usually occur above a certain film thickness, are known problems that limit their potential applications for soft magnetic thin films (SMTFs). In this work, we report the growth of micrometer thick c-axis oriented hcp-Co84Ir16 SMTFs with their magnetic moments restricted strictly in plane by negative magnetocrystalline anisotropy. Extensive characterizations have been performed on these films, which show that they exhibit very good soft magnetic properties even for our micrometer thick films. Moreover, the anisotropy properties and high-frequency properties were thoroughly investigated and our results show very promising properties of these SMTFs for future applications.Comment: 11 pages, 6 figure

Achievement of Diverse Domain Structures in Soft Magnetic Thin Film through Adjusting Intrinsic Magnetocrystalline Anisotropy

Oriented soft magnetic hcp-Co(1 − x)Ir(x) films with a fixed thickness of 120 nm were fabricated. All prepared films exhibit soft magnetic properties but various magnetocrystalline anisotropies with the variation of Ir content. The measured data shows that diverse domain structures including the Néel wall, Bloch wall, and stripe domains present in a fixed film thickness. It is singular for the single-layer soft magnetic film to possess diverse domains in a fixed thickness. This phenomenon was explained by introducing intrinsic magnetocrystalline anisotropy energy into soft magnetic films rather than the structural parameters of the film, inner stress, and microstructure effect

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

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