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The memristor is promising to be the basic cell of next-generation computation systems. Compared to the traditional MOSFET device, the memristor is efficient over energy and area. But one of the biggest challenges faced with researchers is…

Emerging Technologies · Computer Science 2016-11-22 Junyi Li , Fulin Peng , Fan Yang , Xuan Zeng

Magnetoelastic and magnetoelectric coupling in the artificial multiferroic heterostructures facilitate valuable features for device applications such as magnetic field sensors and electric write magnetic-read memory devices. In a…

The morphology and dimension of the conductive filament formed in a memristive device are strongly influenced by the thickness of its switching medium layer. Aggressive scaling of this active layer thickness is critical towards reducing the…

Quantum memory is a central component for quantum information processing devices, and will be required to provide high-fidelity storage of arbitrary states, long storage times and small access latencies. Despite growing interest in applying…

The possibility to develop neuromorphic computing devices able to mimic the extraordinary data processing capabilities of biological systems spurs the research on memristive systems. Memristors with additional functionalities such as robust…

Owing to the outstanding properties provided by nontrivial band topology, topological phases of matter are considered as a promising platform towards low-dissipation electronics, efficient spin-charge conversion, and topological quantum…

Antiferromagnets are magnetically ordered materials which exhibit no net moment and thus are insensitive to magnetic fields. Antiferromagnetic spintronics aims to take advantage of this insensitivity for enhanced stability, while at the…

Non-volatile magnetic storage, from 1940s magnetic core to present day racetrack memory and magnetic anisotropy switching devices rely on the metastability of magnetic domains to store information. However, the inherent inefficiency of…

Orbital degrees of freedom in condensed matters could play important roles in forming a variety of exotic electronic states by interacting with conduction electrons. In 4f electron systems, because of strong intra-atomic spin-orbit…

Strongly Correlated Electrons · Physics 2016-08-24 T. Onimaru , K. Izawa , K. T. Matsumoto , T. Yoshida , Y. Machida , T. Ikeura , K. Wakiya , K. Umeo , S. Kittaka , K. Araki , T. Sakakibara , T. Takabatake

Materials that combine magnetic and ferroelectric properties have generated increasing interest over the last few years, due to both their diverse properties and their potential utility in new types of magnetoelectric device applications.…

Materials Science · Physics 2014-11-17 Claude Ederer , Nicola A. Spaldin

We propose a new type of magnetoelectric memory device that stores magnetic easy-axis information or pseudo-magnetization, rather than a definite magnetization direction, in piezoelectric/ferromagnetic (PE/FM) heterostructures.…

Applied Physics · Physics 2023-07-20 Tingting Shen , Orchi Hassan , Neil R. Dilley , Kerem Y. Camsari , Joerg Appenzeller

This paper reports the first demonstration of a magnet-free, high performance microelectromechanical system (MEMS) based circulator. An innovative circuit based on the commutation of MEMS resonators with high quality (Q) factor using RF…

Non-volatile resistive switching, also known as memristor effect in two terminal devices, has emerged as one of the most important components in the ongoing development of high-density information storage, brain-inspired computing, and…

Mesoscale and Nanoscale Physics · Physics 2020-02-06 Saban M. Hus , Ruijing Ge , Po-An Chen , Meng-Hsueh Chiang , Gavin E. Donnelly , Wonhee Ko , Fumin Huang , Liangbo Liang , An-Ping Li , Deji Akinwande

Recently, in addition to the well-known resistor, capacitor and inductor, a fourth passive circuit element, named memristor, has been identified following theoretical predictions. The model example used in such case consisted in a nanoscale…

Mesoscale and Nanoscale Physics · Physics 2009-11-21 Yu. V. Pershin , M. Di Ventra

Memristive neural networks (MNNs), which use memristors as neurons or synapses, have become a hot research topic recently. However, most memristors are not compatible with mainstream integrated circuit technology and their stabilities in…

Emerging Technologies · Computer Science 2019-01-03 Zhiri Tang , Ruohua Zhu , Peng Lin , Jin He , Hao Wang , Qijun Huang , Sheng Chang , Qiming Ma

In-memory computing is an emerging non-von Neumann computing paradigm where certain computational tasks are performed in memory by exploiting the physical attributes of the memory devices. Memristive devices such as phase-change memory…

Emerging Technologies · Computer Science 2020-04-08 Anastasios Petropoulos , Irem Boybat , Manuel Le Gallo , Evangelos Eleftheriou , Abu Sebastian , Theodore Antonakopoulos

Analog computing based on memristor technology is a promising solution to accelerating the inference phase of deep neural networks (DNNs). A fundamental problem is to map an arbitrary matrix to a memristor crossbar array (MCA) while…

Emerging Technologies · Computer Science 2019-11-28 Baogang Zhang , Necati Uysal , Deliang Fan , Rickard Ewetz

Interface-type resistive switching (RS) devices with lower operation current and more reliable switching repeatability exhibits great potential in the applications for data storage devices and ultra-low-energy computing. However, the…

Although photons are robust, room-temperature carriers well suited to quantum machine learning, the absence of photon-photon interactions hinder the realization of memory functionalities that are critical for capturing long-range context.…

Quantum Physics · Physics 2026-02-02 Chaehyeon Lim , Hyungchul Park , Beomjoon Chae , Jeonghun Kwak , Soo-Yeon Lee , Namkyoo Park , Sunkyu Yu

The technological exploitation of ferroelectricity in CMOS electron devices offers new design opportunities, but also significant challenges from an integration, optimization and modelling perspective. We here revisit the working principle…

Emerging Technologies · Computer Science 2021-05-04 David Esseni , Riccardo Fontanini , Daniel Lizzit , Marco Massarotto , Francesco Driussi , Mirko Loghi
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