Recent Articles

Imaging Current Paths in Silicon Photovoltaic Devices with a Quantum Diamond Microscope

S.C. Scholten, G.J. Abrahams, B.C. Johnson, A.J. Healey, I.O. Robertson, D.A. Simpson, A. Stacey, S. Onoda, T. Ohshima, T.C. Kho, J. Ibarra Michel, J. Bullock, L.C.L. Hollenberg, and J.-P. Tetienne

Phys. Rev. Applied 18, 014041 (2022) - Published 18 July, 2022

Quantum diamond microscopy is emerging as a tool for magnetic current imaging (MCI) of electrical devices. Due to the optical invasiveness of the technique, it has not been extended to photovoltaic (PV) devices—until now. This study employs a stroboscopic measurement protocol that allows temporally resolved measurements of silicon PV cells, independent of stimulus. The authors capitalize on the contactless aspect of MCI to image photocurrent loops that are entirely internal to the device (e.g. under open-circuit conditions), equivalent to shunt-resistance paths. The versatile capabilities of quantum diamond microscopy may find wide application in this further context.

Demonstration of Decentralized Physics-Driven Learning

Sam Dillavou, Menachem Stern, Andrea J. Liu, and Douglas J. Durian

Phys. Rev. Applied 18, 014040 (2022) - Published 18 July, 2022

Leveraging physical processes rather than a central processor is key to building machine learning systems that are massively scalable, robust to damage, and energy-efficient, like the brain. To achieve these features, the authors build an electrical network made of identical resistive edges that self-adjust based on local conditions in order to minimize an energy-based global cost function when shown training examples. Problems like regression and data classification are successfully solved by this network. Due to their energy efficiency and scaling advantages, future versions may one day compete with computational neural networks.

Implementation of a Binary Neural Network on a Passive Array of Magnetic Tunnel Junctions

Jonathan M. Goodwill, Nitin Prasad, Brian D. Hoskins, Matthew W. Daniels, Advait Madhavan, Lei Wan, Tiffany S. Santos, Michael Tran, Jordan A. Katine, Patrick M. Braganca, Mark D. Stiles, and Jabez J. McClelland

Phys. Rev. Applied 18, 014039 (2022) - Published 18 July, 2022

Hardware neural networks based on synaptic devices can provide the speed, parallelism, and low energy consumption needed for applications in distributed computing and the Internet of Things. However, the accuracy of inference in a given system can be severely impacted by device variations and other imperfections. In this work, the authors demonstrate that a binary neural network using a passive crossbar array of magnetic tunnel junctions can perform well on a simple wine identification dataset. This work demonstrates the promise of these devices but cautions that careful consideration of hardware realities in scaling up this technology is necessary for real-world applications.

Functional Acoustic Metamaterial Using Shortcut to Adiabatic Passage in Acoustic Waveguide Couplers

Shuai Tang, Jin-Lei Wu, Cheng Lü, Jie Song, and Yongyuan Jiang

Phys. Rev. Applied 18, 014038 (2022) - Published 15 July, 2022

Temperature-Biased Double-Loop Josephson Flux Transducer

C. Guarcello, R. Citro, F. Giazotto, and A. Braggio

Phys. Rev. Applied 18, 014037 (2022) - Published 15 July, 2022

Miniature Biplanar Coils for Alkali-Metal-Vapor Magnetometry

Michael C. D. Tayler, Kostas Mouloudakis, Rasmus Zetter, Dominic Hunter, Vito G. Lucivero, Sven Bodenstedt, Lauri Parkkonen, and Morgan W. Mitchell

Phys. Rev. Applied 18, 014036 (2022) - Published 15 July, 2022

Coiled Phononic Crystal with Periodic Rotational Locking: Subwavelength Bragg Band Gaps

Carson L. Willey, Vincent W. Chen, David Roca, Armin Kianfar, Mahmoud I. Hussein, and Abigail T. Juhl

Phys. Rev. Applied 18, 014035 (2022) - Published 15 July, 2022

Equiaxed Polycrystalline Ice for Ultrasonic Testing of Solids

Francesco Simonetti and Michael D. Uchic

Phys. Rev. Applied 18, 014034 (2022) - Published 14 July, 2022

Rydberg Microwave-Frequency-Comb Spectrometer

Li-Hua Zhang, Zong-Kai Liu, Bang Liu, Zheng-Yuan Zhang, Guang-Can Guo, Dong-Sheng Ding, and Bao-Sen Shi

Phys. Rev. Applied 18, 014033 (2022) - Published 14 July, 2022

Polarization-Selective Excitation of Antiferromagnetic Resonance in Perpendicularly Magnetized Synthetic Antiferromagnets

Yoichi Shiota, Tomonori Arakawa, Ryusuke Hisatomi, Takahiro Moriyama, and Teruo Ono

Phys. Rev. Applied 18, 014032 (2022) - Published 14 July, 2022

Tuning Spin Transport in a Graphene Antiferromagnetic Insulator

Petr Stepanov, Dmitry L. Shcherbakov, Shi Che, Marc W. Bockrath, Yafis Barlas, Dmitry Smirnov, Kenji Watanabe, Takashi Taniguchi, Roger K. Lake, and Chun Ning Lau

Phys. Rev. Applied 18, 014031 (2022) - Published 13 July, 2022

Defect-Polymorphism-Controlled Electrophoretic Propulsion of Anisometric Microparticles in a Nematic Liquid Crystal

Devika V S, Dinesh Kumar Sahu, Ravi Kumar Pujala, and Surajit Dhara

Phys. Rev. Applied 18, 014030 (2022) - Published 13 July, 2022

Broadband Control of Group Delay Using the Brewster Effect in Metafilms

Yasuhiro Tamayama and Hiromu Yamamoto

Phys. Rev. Applied 18, 014029 (2022) - Published 13 July, 2022

Charge-Induced Artifacts in Nonlocal Spin-Transport Measurements: How to Prevent Spurious Voltage Signals

Frank Volmer, Timo Bisswanger, Anne Schmidt, Christoph Stampfer, and Bernd Beschoten

Phys. Rev. Applied 18, 014028 (2022) - Published 13 July, 2022

A lively discussion has emerged in both the valleytronics and spintronics communities, concerning the correct interpretation of nonlocal transport experiments. The authors contribute to this ongoing debate their overview of all mechanisms that can create charge-induced nonlocal voltages, which could be misattributed to spin- or valley-related effects. A detailed description of a further measurement artifact, apparently not discussed in the literature, is also included. Fortunately, special instrumentation can significantly reduce most of these measurement artifacts, and thus can strongly diminish the risk of misinterpretation.

Inertial-Amplified Mechanical Resonators for the Mitigation of Ultralow-Frequency Vibrations

Zhen Dong and Ping Sheng

Phys. Rev. Applied 18, 014027 (2022) - Published 12 July, 2022

Mutual Synchronization of Constriction-Based Spin Hall Nano-Oscillators in Weak In-Plane Magnetic Fields

Hamid Mazraati, Shreyas Muralidhar, Seyyed Ruhollah Etesami, Mohammad Zahedinejad, Seyed Amir Hossein Banuazizi, Sunjae Chung, Ahmad A. Awad, Roman Khymyn, Mykola Dvornik, and Johan Åkerman

Phys. Rev. Applied 18, 014026 (2022) - Published 12 July, 2022

Robust and Programmable Logic-In-Memory Devices Exploiting Skyrmion Confinement and Channeling Using Local Energy Barriers

Naveen Sisodia, Johan Pelloux-Prayer, Liliana D. Buda-Prejbeanu, Lorena Anghel, Gilles Gaudin, and Olivier Boulle

Phys. Rev. Applied 18, 014025 (2022) - Published 12 July, 2022

Modeling of Multimodal Scattering by Conducting Bodies in Quantum Optics: The Method of Characteristic Modes

Gregory Ya. Slepyan, Dmitri Mogilevtsev, Ilay Levie, and Amir Boag

Phys. Rev. Applied 18, 014024 (2022) - Published 12 July, 2022

Asymmetric Localization of Light by Second-Harmonic Generation

Hamed Ghaemi-Dizicheh, Amir Targholizadeh, Baofeng Feng, and Hamidreza Ramezani

Phys. Rev. Applied 18, 014023 (2022) - Published 11 July, 2022

Parallel Electromagnetically Induced Transparency near Ground-State Cooling of a Trapped-Ion Crystal

Jie Zhang, Man-Chao Zhang, Yi Xie, Chun-Wang Wu, Bao-Quan Ou, Ting Chen, Wan-Su Bao, Paul Haljan, Wei Wu, Shuo Zhang, and Ping-Xing Chen

Phys. Rev. Applied 18, 014022 (2022) - Published 11 July, 2022

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