Xiaoxue Yang, Xue-Feng Zhang, Changfeng Li and Huiting Li
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Magnetic-field-controlled positioning of magnetic domain wall in tie-shaped asymmetric nanowire and its application for magnetic field detection†
With topological spin texture, magnetic domain walls have soliton-like dynamic behaviors in magnetic nanowires, which can be used in information transmission and storage technology. Therefore, precisely controlling the dynamic behavior of the magnetic domain wall and its pinning behavior is one of the important technical challenges in realizing domain-wall-based spintronic devices. In this work, a geometrically defect-free scheme for domain wall pinning/depinning is proposed using micromagnetic simulations based on a tie-shaped asymmetric nanowire, which can precisely control the position of the magnetic domain wall in an external magnetic field. The results show that the domain wall in tie-shaped nanowires exhibits excellent linear response and ultrafast time response to external magnetic fields, which endow them with potential applications for high-frequency weak-magnetic-field detection. We further propose a scheme for constructing a magnetic-field sensor using the tie-structured nanowire, and we study its feasibility.
期刊介绍:
Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions.
The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.