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We propose an improved scheme for low-power writing of binary bits in non-volatile (multiferroic) magnetic memory with electrically generated mechanical stress. Compared to an earlier idea [Tiercelin, et al., J. Appl. Phys., 109, 07D726…

Mesoscale and Nanoscale Physics · Physics 2015-06-18 Ayan K. Biswas , Supriyo Bandyopadhyay , Jayasimha Atulasimha

The storage industry is moving toward emerging non-volatile memories (NVMs), including the spin-transfer torque magnetoresistive random-access memory (STT-MRAM) and the phase-change memory (PCM), owing to their high density and low-power…

Emerging Technologies · Computer Science 2020-04-28 Nikhil Rangarajan , Satwik Patnaik , Johann Knechtel , Ozgur Sinanoglu , Shaloo Rakheja

Since Felix Bloch's introduction of the concept of spin waves in 1930, magnons (the quanta of spin waves) have been extensively studied in a range of materials for spintronics, particularly for non-volatile logic-in-memory devices.…

Compute-in-memory (CiM) is a promising approach to alleviating the memory wall problem for domain-specific applications. Compared to current-domain CiM solutions, charge-domain CiM shows the opportunity for higher energy efficiency and…

Emerging Technologies · Computer Science 2021-02-03 Guodong Yin , Yi Cai , Juejian Wu , Zhengyang Duan , Zhenhua Zhu , Yongpan Liu , Yu Wang , Huazhong Yang , Xueqing Li

The magnetoelectric effects in multiferroics have a great potential in creating next-generation memory devices. We conceive a new concept of non-volatile memories based on a type of nonlinear magnetoelectric effects showing a…

Materials Science · Physics 2016-08-17 Jianxin Shen , Junzhuang Cong , Yisheng Chai , Dashan Shang , Shipeng Shen , Kun Zhai , Ying Tian , Young Sun

Neuromorphic devices, with their distinct advantages in energy efficiency and parallel processing, are pivotal in advancing artificial intelligence applications. Among these devices, memristive transistors have attracted significant…

Applied Physics · Physics 2024-11-08 Shengbo Wang , Jingfang Pei , Cong Li , Xuemeng Li , Li Tao , Arokia Nathan , Guohua Hu , Shuo Gao

Reservoir computing is a highly efficient machine learning framework for processing temporal data by extracting features from the input signal and mapping them into higher dimensional spaces. Physical reservoir layers have been realized…

Machine Learning · Computer Science 2023-11-17 Md Razuan Hossain , Ahmed Salah Mohamed , Nicholas Xavier Armendarez , Joseph S. Najem , Md Sakib Hasan

Exploiting spin degree of freedom of electron a new proposal is given to characterize spin-based logical operations using a quantum interferometer that can be utilized as a programmable spin logic device (PSLD). The ON and OFF states of…

Mesoscale and Nanoscale Physics · Physics 2018-09-19 Moumita Patra , Santanu K. Maiti

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

The demands of modern electronic components require advanced computing platforms for efficient information processing to realize in-memory operations with a high density of data storage capabilities towards developing alternatives to von…

The realization of fully reconfigurable, voltage-controlled, and programmable on-chip magnonic devices is essential to fully harness the potential of spin waves for signal processing, logic and neuromorphic computing. Yet, existing…

Integrated optoelectronic systems strive to combine the logic/memory density of electronics with the bandwidth of photonics, but monolithic realization is impeded by the inefficient electronic-to-photonic interface. Current architectures…

Spin transport through magnetic insulators has been demonstrated in a variety of materials and is an emerging pathway for next-generation spin-based computing. To modulate spin transport in these systems, one typically applies a…

Scalable, low-dissipation memory operating below 4 K is a critical requirement for superconducting and quantum computing systems. Existing cryogenic memory technologies rely on CMOS derivatives or hybrid architectures that incur leakage,…

Superconductivity · Physics 2026-04-27 Sonam Bhakat , Pushpak Banerjee , Ahmedullah Aziz , Jackson Miller , Avradeep Pal

Memristors are emerging as key electronic components that retain resistance states without power. Their non-volatile nature and ability to mimic synaptic behavior make them ideal for next-generation memory technologies and neuromorphic…

Mesoscale and Nanoscale Physics · Physics 2025-10-28 Tongxin Chen , Yinyu Nie , Yafei Hao , Shengchun Shen , Jiajun Pan , Xiaoguang Li , Yuan Lu

The surface state of a 3D topological insulator (3DTI) is a spin-momentum locked conductive state, whose large spin hall angle can be used for the energy-efficient spin orbit torque based switching of an overlying ferromagnet (FM).…

Mesoscale and Nanoscale Physics · Physics 2022-12-20 Hamed Vakili , Samiran Ganguly , George J. de Coster , Mahesh R. Neupane , Avik W. Ghosh

Memristor, one of the fundamental circuit elements, has promising applications in non-volatile memory and storage technology as it can theoretically achieve infinite states. Information can be stored independently in these states and…

Emerging Technologies · Computer Science 2019-05-14 Santosh Parajuli , Ram Kaji Budhathoki , Hyongsuk Kim

A new class of spin-transfer torque magnetic random access memory (STT-MRAM) is discussed, in which writing is achieved using thermally initiated magnonic current pulses as an alternative to conventional electric current pulses. The…

Materials Science · Physics 2015-05-28 Niladri N. Mojumder , David W. Abraham , Kaushik Roy , D. C. Worledge

Reconfigurable memristors featuring neural and synaptic functions hold great potential for neuromorphic circuits by simplifying system architecture, cutting power consumption, and boosting computational efficiency. Their additive…

Prospective spintronic memory and logic devices will benefit from the negligible stray field and ultrafast magnetic dynamics inherent to antiferromagnets [1]. However, realizing isothermal, nonvolatile, and deterministic switching of…