Recent Articles

Modeling of the Thermodiffusion-Induced Filament Formation in TiN/TaxO1−x/TiN Resistive-Switching Devices

Jingjia Meng, Enkui Lian, Jonathan D. Poplawsky, and Marek Skowronski

Phys. Rev. Applied 17, 054040 (2022) - Published 24 May, 2022

Spatiotemporal Analysis of Electromagnetic Field Coherence in Complex Media

Thomas Fromenteze, Matthieu Davy, Okan Yurduseven, Yann Marie-Joseph, and Cyril Decroze

Phys. Rev. Applied 17, 054039 (2022) - Published 24 May, 2022

Universal Deterministic Quantum Operations in Microwave Quantum Links

Guillermo F. Peñas, Ricardo Puebla, Tomás Ramos, Peter Rabl, and Juan José García-Ripoll

Phys. Rev. Applied 17, 054038 (2022) - Published 24 May, 2022

Neural Networks Based on Ultrafast Time-Delayed Effects in Exciton Polaritons

R. Mirek, A. Opala, M. Furman, M. Król, K. Tyszka, B. Seredyński, W. Pacuski, J. Suffczyński, J. Szczytko, M. Matuszewski, and B. Piętka

Phys. Rev. Applied 17, 054037 (2022) - Published 23 May, 2022

Large Antisymmetric Interlayer Exchange Coupling Enabling Perpendicular Magnetization Switching by an In-Plane Magnetic Field

Hiroto Masuda, Takeshi Seki, Yuta Yamane, Rajkumar Modak, Ken-ichi Uchida, Jun'ichi Ieda, Yong-Chang Lau, Shunsuke Fukami, and Koki Takanashi

Phys. Rev. Applied 17, 054036 (2022) - Published 23 May, 2022

Stability of Quantized Conductance Levels in Memristors with Copper Filaments: Toward Understanding the Mechanisms of Resistive Switching

Oleg G. Kharlanov, Boris S. Shvetsov, Vladimir V. Rylkov, and Anton A. Minnekhanov

Phys. Rev. Applied 17, 054035 (2022) - Published 23 May, 2022

Determining the Thickness of the Dead Layer in Superconducting Film Using a Two-Coil Mutual-Inductance Technique

Ruozhou Zhang, Zhanyi Zhao, Mingyang Qin, Juan Xu, Wenxin Cheng, Yangmu Li, Qihong Chen, Jie Yuan, and Kui Jin

Phys. Rev. Applied 17, 054034 (2022) - Published 20 May, 2022

Breakdown of the Weak-Coupling Limit in Quantum Annealing

Yuki Bando, Ka-Wa Yip, Huo Chen, Daniel A. Lidar, and Hidetoshi Nishimori

Phys. Rev. Applied 17, 054033 (2022) - Published 20 May, 2022

Reduced Hysteresis and Enhanced Giant Magnetocaloric Effect in B-Doped all-d-Metal Ni-Co-Mn-Ti-Based Heusler Materials

Fengqi Zhang, Ivan Batashev, Niels van Dijk, and Ekkes Brück

Phys. Rev. Applied 17, 054032 (2022) - Published 19 May, 2022

Laser Frequency-Offset Locking at 10-Hz-Level Instability Using Hybrid Electronic Filters

Vyacheslav Li, Fritz Diorico, and Onur Hosten

Phys. Rev. Applied 17, 054031 (2022) - Published 19 May, 2022

Far-Field Acoustic Subwavelength Imaging with Blind Structured Illumination and Joint-Sparsity Reconstruction

Jinuan Lin and Chu Ma

Phys. Rev. Applied 17, 054030 (2022) - Published 18 May, 2022

Quantifying Power in Silicon Photonic Neural Networks

Alexander N. Tait

Phys. Rev. Applied 17, 054029 (2022) - Published 18 May, 2022

Interdash Coupling within Dense Ensembles of Quantum Dashes: Comparison of InAs/(In,Al,Ga)As/InP and InAs/(In,Al)As/InP Systems

P. Holewa, M. Gawełczyk, A. Maryński, K. Ryczko, V. Liverini, M. Beck, J. Faist, G. Sęk, and M. Syperek

Phys. Rev. Applied 17, 054028 (2022) - Published 17 May, 2022

Quasi-Fermi-Level Phase Space and its Applications in Ambipolar Two-Dimensional Field-Effect Transistors

Zhao-Yi Yan, Kan-Hao Xue, Zhan Hou, Yang Shen, He Tian, Yi Yang, and Tian-Ling Ren

Phys. Rev. Applied 17, 054027 (2022) - Published 17 May, 2022

Quasi-Fermi levels (QFLs) have become a canonical concept in semiconductor device modeling. However, a global model to cover both unipolar and ambipolar transport modes of two-dimensional field-effect transistors (2D FETs) based on QFLs is still needed, as it is challenging to capture quantitatively the effect of QFL splitting on transport. This work establishes a theoretical platform to account for that effect: the quasi-Fermi-level phase space (QFLPS). With QFLPS a unified picture of unipolar and ambipolar transport is drawn, the working modes of 2D FETs acquire more intuitive physical interpretations, and many valuable outcomes for device modeling and circuit design are realized.

Viscosity-Limited Drift Instabilities in Two-Dimensional Electron Systems

Aleksandr S. Petrov and Dmitry Svintsov

Phys. Rev. Applied 17, 054026 (2022) - Published 16 May, 2022

Terahertz technology suffers from a lack of efficient emitters, but dc excitation of plasma waves in two-dimensional electron systems (2DESs) is a promising solution. Ultrahigh-mobility 2DESs would help to avoid the Ohmic losses that have plagued the implementation of such devices, but reduced Ohmic loss comes at the cost of damping via viscous loss. The authors exploit a recently developed perturbative technique to develop a systematic treatment of viscosity-induced plasmon damping, and provide a powerful tool for optimizing plasmonic resonators.

Acoustic Beam Splitting and Cloaking Based on a Compressibility-Near-Zero Medium

Changqing Xu, Sibo Huang, Zhiwei Guo, Haitao Jiang, Yong Li, Ying Wu, and Hong Chen

Phys. Rev. Applied 17, 054025 (2022) - Published 16 May, 2022

High-Order Pulse-Echo Ultrasound

Urs A.T. Hofmann, Sergio Pérez-López, Héctor Estrada, and Daniel Razansky

Phys. Rev. Applied 17, 054024 (2022) - Published 16 May, 2022

Computational Verification and Experimental Validation of the Vibration-Attenuation Properties of a Geometrically Nonlinear Metamaterial Design

Kyriakos Alexandros Chondrogiannis, Andrea Colombi, Vasilis Dertimanis, and Eleni Chatzi

Phys. Rev. Applied 17, 054023 (2022) - Published 13 May, 2022

Metamaterials continue to be conceptually intriguing for the manipulation of propagating waves. However, preventing low-frequency wave propagation proves to be challenging, due to limited metamaterial dimensions and mass. This study focuses on a metamaterial lattice featuring geometrically nonlinear behavior that can lead to negative stiffness, aimed at overcoming the requirement of large mass for low-frequency vibration attenuation. This approach can find application in structural engineering to protect against low-frequency excitations—such as earthquakes.

Topological Characterization of Dynamic Chiral Magnetic Textures Using Machine Learning

Tim Matthies, Alexander F. Schäffer, Thore Posske, Roland Wiesendanger, and Elena Y. Vedmedenko

Phys. Rev. Applied 17, 054022 (2022) - Published 13 May, 2022

Characterizing magnetic textures is important for applications in stochastic computing and memory devices based on magnetic skyrmions. Knowing the exact number of skyrmions is essential for these tasks, yet this count is particularly difficult to determine when dealing with quickly moving skyrmions at nonzero temperatures, where only time-averaged, smeared results are available. The present study uses machine-learning techniques to solve this problem successfully, to the benefit of future investigations in spintronic computation and memory applications.

Multinode State Transfer and Nonlocal State Preparation via a Unidirectional Quantum Network

Hao Ai, Ying-Yü Fang, Cheng-Rui Feng, Zhihui Peng, and Ze-Liang Xiang

Phys. Rev. Applied 17, 054021 (2022) - Published 12 May, 2022

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