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Antiferromagnetic materials have a vanishingly small net magnetization, which generates weak dipolar fields and makes them robust against external magnetic perturbation and rapid magnetization dynamics, as dictated by the geometric mean of…

Materials Science · Physics 2024-11-19 Ankit Shukla , Siyuan Qian , Shaloo Rakheja

Artificial intelligence is widely used in everyday life. However, an insufficient computing efficiency due to the so-called von Neumann bottleneck cannot satisfy the demand for real-time processing of rapidly growing data. Memristive…

Applied Physics · Physics 2024-02-23 Jing Yang , Lingxiang Hu , Liufeng Shen , Jingrui Wang , Peihong Cheng , Huanming Lu , Fei Zhuge , Zhizhen Ye

Spintronic nanodevices have ultrafast nonlinear dynamic and recurrence behaviors on a nanosecond scale that promises to enable spintronic reservoir computing (RC) system. Here two physical RC systems based on a single magnetic skyrmion…

Emerging Technologies · Computer Science 2020-10-28 Wencong Jiang , Lina Chen , Kaiyuan Zhou , Liyuan Li , Qingwei Fu , Youwei Du , Ronghua Liu

Spintronics, which is the basis of a low-power, beyond-CMOS technology for computational and memory devices, remains up to now entirely based on critical materials such as Co, heavy metals and rare-earths. Here, we show that Mn4N, a…

Materials Science · Physics 2019-03-05 T. Gushi , M. Jovičević Klug , J. Peña Garcia , H. Okuno , J. Vogel , J. P. Attané , T. Suemasu , S. Pizzini , L. Vila

Antiferromagnetic materials promise improved performance for spintronic applications, as they are robust against external magnetic field perturbations and allow for faster magnetization dynamics compared to ferromagnets. The direct…

Antiferromagnetic (AFM) materials are a pathway to spintronic memory and computing devices with unprecedented speed, energy efficiency, and bit density. Realizing this potential requires AFM devices with simultaneous electrical writing and…

Superlattices may play an important role in next generation electronic and spintronic devices if the key-challenge of the reading and writing data can be solved. This challenge emerges from the coupling of low dimensional individual layers…

Mesoscale and Nanoscale Physics · Physics 2014-08-04 S. Narayana Jammalamadaka , Johan Vanacken , V. V. Moshchalkov

Over the last two decades, the new branch of spintronics, i.e., semiconductor spintronics, has gained more attention because it integrates the characteristics of conventional semiconductors, such as optical bandgap and charge carriers,…

Materials Science · Physics 2024-10-22 Pankaj Bhardwaj , Jarnail Singh , Vikram Verma , Ravi Kumar

The coexistence and coupling between magnetization and electric polarization in multiferroic materials provide extra degrees of freedom for creating next-generation memory devices. A variety of concepts of multiferroic or magnetoelectric…

Materials Science · Physics 2016-06-23 Jianxin Shen , Junzhuang Cong , Dashan Shang , Yisheng Chai , Shipeng Shen , Kun Zhai , Young Sun

Non-Boolean computing based on emerging post-CMOS technologies can potentially pave the way for low-power neural computing platforms. However, existing work on such emerging neuromorphic architectures have either focused on solely mimicking…

Emerging Technologies · Computer Science 2016-11-15 Abhronil Sengupta , Yong Shim , Kaushik Roy

Memristors have attracted interest as neuromorphic computation elements because they show promise in enabling efficient hardware implementations of artificial neurons and synapses. We performed measurements on interface-type memristors to…

Emerging Technologies · Computer Science 2021-01-07 Thomas F. Tiotto , Anouk S. Goossens , Jelmer P. Borst , Tamalika Banerjee , Niels A. Taatgen

The human brain achieves exceptional energy efficiency by co-locating memory and processing, yet reproducing this principle in hardware remains challenging because many neuromorphic devices require standby power, offer limited…

Neural networks have revolutionized the area of artificial intelligence and introduced transformative applications to almost every scientific field and industry. However, this success comes at a great price; the energy requirements for…

Memristors are promising next-generation memory candidates that are nonvolatile, possess low power requirements and are capable of nanoscale fabrication. In this article we physically realise and describe the use of organic memristors in…

Emerging Technologies · Computer Science 2012-12-17 Victor Erokhin , Gerard David Howard , Andrew Adamatzky

Magnetic skyrmion-based data storage and unconventional computing devices have gained increasing attention due to their topological protection, small size, and low driving current. However, skyrmion creation, deletion, and motion are still…

Materials Science · Physics 2023-01-11 Aijaz H. Lone , Arnab Ganguly , Selma Amara , Gobind Das , H. Fariborzi

The discovery of the spin torque effect has made magnetic nanodevices realistic candidates for active elements of memory devices and applications. Magnetoresistive effects allow the read-out of increasingly small magnetic bits, and the spin…

Materials Science · Physics 2014-01-07 Nicolas Locatelli , Vincent Cros , Julie Grollier

We demonstrate a non-volatile magnetoelectric magnonic memory (MEMM) that enables fully electrical write/read via direct magnon-driven sensing in an insulating antiferromagnet. A fabricated SrIrO3/La-BiFeO3/SrIrO3 trilayer exhibits sub-100…

In this paper we review the recent field of organic spintronics, where organic materials are applied as a medium to transport and control spin-polarized signals. The contacts for injecting and detecting spins are formed by metals, oxides,…

Mesoscale and Nanoscale Physics · Physics 2007-06-13 W. J. M. Naber , S. Faez , W. G. van der Wiel

We propose a new type of multi-bit and energy-efficient magnetic memory based on current-driven, field-free, and highly controlled domain wall motion. A meandering domain wall channel with precisely interspersed pinning regions provides the…

Emerging Technologies · Computer Science 2024-05-29 Pengxiang Zhang , Wilfried Haensch , Charudatta M. Phatak , Supratik Guha

Spintronic nano-neurons offer a promising route towards energy-efficient, high-performance hardware neural networks thanks to their inherent low-input nonlinear dynamics. However, training such networks remains a major bottleneck as it…

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