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In our earlier work [Appl. Phys. Lett. 92, 022509 (2008)], we proposed nonvolatile vortex random access memory (VRAM) based on the energetically stable twofold ground state of vortex-core magnetizations as information carrier. Here we…

Materials Science · Physics 2011-08-12 Young-Sang Yu , Hyunsung Jung , Ki-Suk Lee , Peter Fischer , Sang-Koog Kim

A new genre of Spin-Transfer Torque (STT) MRAM is proposed, in which bi-directional writing is achieved using thermoelectrically controlled magnonic current as an alternative to conventional electric current. The device uses a magnetic…

Materials Science · Physics 2011-08-12 Niladri N. Mojumder , Kaushik Roy , David W. Abraham

Heavy computational demands from artificial intelligence (AI) leads the research community to explore the design space for functional materials that can be used for high performance memory and neuromorphic computing hardware. Novel device…

Materials Science · Physics 2024-09-04 Xinye Li , Padma Srivari , Sayani Majumdar

Large magnetoresistance effect controlled by electric field rather than magnetic field or electric current is a preferable routine for designing low power consumption magnetoresistance-based spintronic devices. Here we propose an…

Mesoscale and Nanoscale Physics · Physics 2019-10-23 Yurong Su , Jia Zhang , Jing-Tao Lü , Jeongmin Hong , Long You

A ringing free bit addressing scheme for magnetic memories like MRAM (magnetic random access memory) is proposed. As in standard MRAM addressing schemes the switching of a selected cell is obtained by the combination of two half-select…

Materials Science · Physics 2010-08-19 H. W. Schumacher

Antiferromagnets (AFMs) hold promise for applications in digital logic. However, switching AFM domains is challenging, as magnetic fields do not couple to the bulk antiferromagnetic order parameter. Here we show that magnetic-field-driven…

Materials Science · Physics 2026-01-13 Sophie F. Weber , Veronika Sunko

Taking advantage of the Magnetoelectric (ME) and its inverse effect, this article demonstrates strain-mediated magnetoelectric write and read operations simultaneously in Co60Fe20B20/ Pb(Mg1/3Nb2/3)0.7Ti0.3O3 heterostructures without using…

Applied Physics · Physics 2020-07-15 Tingting Shen , Vaibhav Ostwal , Kerem Y. Camsari , Joerg Appenzeller

Electric field control of magnetic anisotropy in ferromagnets has been intensively pursued in spintronics to achieve efficient memory and computing devices with low energy consumption. Compared with ferromagnets, antiferromagnets hold huge…

In this letter, we demonstrate a non-volatile memory device in a graphene FET structure using ferroelectric gating. The binary information, i.e. "1" and "0", is represented by the high and low resistance states of the graphene working…

Mesoscale and Nanoscale Physics · Physics 2009-04-23 Yi Zheng , Guang-Xin Ni , Chee-Tat Toh , Ming-Gang Zeng , Shu-Ting Chen , Kui Yao , Barbaros Ozyilmaz

Perpendicular magnetic anisotropy (PMA) is a key property of magnetoresistive random access memory (MRAM). To increase areal density of MRAM it is important to find a way to enhance the PMA. Recently a strong enhancement of the PMA by…

Materials Science · Physics 2023-03-22 Yukie Kitaoka , Hiroshi Imamura

A Ferroelectric Analog Non-Volatile Memory based on a WOx electrode and ferroelectric HfZrO$_4$ layer is fabricated at a low thermal budget (~375$^\circ$C), enabling BEOL processes and CMOS integration. The devices show suitable properties…

Voltage-controlled magnetoresistive random access memory (VC-MRAM) based on voltage-induced dynamic switching in magnetic tunnel junctions (MTJs) is a promising ultimate non-volatile memory with ultralow power consumption. However, the…

Mesoscale and Nanoscale Physics · Physics 2023-05-31 Rie Matsumoto , Shiniji Yuasa , Hiroshi Imamura

Reliable operation of perpendicular spin-transfer-torque magnetic random-access memory (p-STT-MRAM) requires control of magnetic alignment within the synthetic antiferromagnet (SAF) reference layer. At nanopillar dimensions, however,…

Mesoscale and Nanoscale Physics · Physics 2026-05-12 Afan Terko , George Lertzman-Lepofsky , Dieter Suess , Claas Abert , Erol Girt

Spin transfer torque magnetic random access memory (STT-MRAM) is considered as one of the most promising candidates to build up a true universal memory thanks to its fast write/read speed, infinite endurance and non-volatility. However the…

Emerging Technologies · Computer Science 2015-06-04 Weisheng Zhao , Sumanta Chaudhuri , Celso Accoto , Jacques-Olivier Klein , Claude Chappert , Pascale Mazoyer

Harnessing the unique properties of non-collinear antiferromagnets (AFMs) will be essential for exploiting the full potential of antiferromagnetic spintronics. Indeed, many of the effects enabling ferromagnetic spintronic devices have a…

Magnetic Random Access Memories (MRAM) interest is growing fast in the microelectronics industry. Commercial MRAM products already exist and all major industrial players have launched large R\&D efforts to bring Spin Transfer Torque MRAM to…

Applied Physics · Physics 2019-06-26 Gregory Di Pendina , Guillaume Prenat , Bernard Dieny

This work proposes CoMET, a fast and energy-efficient spintronics device for logic applications. An input voltage is applied to a ferroelectric (FE) material, in contact with a composite structure - a ferromagnet (FM) with in-plane magnetic…

Emerging Technologies · Computer Science 2017-04-18 Meghna G. Mankalale , Zhaoxin Liang , Zhengyang Zhao , Chris Kim , Jian-Ping Wang , Sachin S. Sapatnekar

Resistance Random Access Memory (RRAMTM) device, with its electrically induced nanoscale resistive switching capacity, has been gaining considerable attention as future non-volatile memory device. Here, we propose a mechanism of switching…

Spin-memristors are a class of materials that can store memories through the control of spins, potentially leading to novel technologies that address the constraints of standard silicon electronics, thereby facilitating the advancement of…

Materials Science · Physics 2025-12-25 Gaspar De la Barrera , Alvaro S. Nunez

Deep random forest (DRF), which incorporates the core features of deep learning and random forest (RF), exhibits comparable classification accuracy, interpretability, and low memory and computational overhead when compared with deep neural…

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