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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

In this work, we theoretically and experimentally investigate the working principle and non-volatile memory (NVM) functionality of 2D $\alpha$-In$_2$Se$_3$ based ferroelectric-semiconductor-metal-junction (FeSMJ). First, we analyze the…

Applied Physics · Physics 2020-12-02 Atanu K. Saha , Mengwei Si , Peide Ye , Sumeet K. Gupta

Superconductor electronics (SCE) is a promising complementary and beyond CMOS technology. However, despite its practical benefits, the realization of SCE logic faces a significant challenge due to the absence of dense and scalable…

Superconductivity · Physics 2024-12-05 Mustafa Altay Karamuftuoglu , Beyza Zeynep Ucpinar , Sasan Razmkhah , Massoud Pedram

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…

The ultimate goal of multiferroic research is the development of new-generation non-volatile memory devices, the so-called magnetoelectric (ME) memories, where magnetic bits are controlled via electric fields without the application of…

Embedded machine learning (ML) systems have now become the dominant platform for deploying ML serving tasks and are projected to become of equal importance for training ML models. With this comes the challenge of overall efficient…

Hardware Architecture · Computer Science 2022-06-29 Ahmet Inci , Mehmet Meric Isgenc , Diana Marculescu

Ferroelectric field-effect transistors (Fe-FETs) with ferroelectric hafnium oxide (FE HfO2) as gate insulator are being extensively explored as a promising device candidate for three-dimensional (3D) NAND memory application. FE HfO2…

Mesoscale and Nanoscale Physics · Physics 2021-10-04 Mengwei Si , Peide D. Ye

Compute in-memory (CIM) is a promising technique that minimizes data transport, the primary performance bottleneck and energy cost of most data intensive applications. This has found wide-spread adoption in accelerating neural networks for…

Signal Processing · Electrical Eng. & Systems 2021-02-16 Brian Crafton , Samuel Spetalnick , Arijit Raychowdhury

Spintronic devices based on antiferromagnetic (AFM) materials hold the promise of fast switching speeds and robustness against magnetic fields. Different device concepts have been predicted and experimentally demonstrated, such as…

Modern computing systems are embracing non-volatile memory (NVM) to implement high-capacity and low-cost main memory. Elevated operating voltages of NVM accelerate the aging of CMOS transistors in the peripheral circuitry of each memory…

Hardware Architecture · Computer Science 2020-12-02 Shihao Song , Anup Das , Onur Mutlu , Nagarajan Kandasamy

The deluge of sensors and data generating devices has driven a paradigm shift in modern computing from arithmetic-logic centric to data-centric processing. Data-centric processing require innovations at device level to enable novel…

I present a review of both experimental and theoretical studies performed during the recent three years, which deal with the physical properties and possible applications of graphene placed on ferroelectric (organic or Pb(ZrxTi1-x)O3 (PZT)…

Mesoscale and Nanoscale Physics · Physics 2015-06-05 Maksym Strikha

In-memory computing (IMC) can eliminate the data movement between processor and memory which is a barrier to the energy-efficiency and performance in Von-Neumann computing. Resistive RAM (RRAM) is one of the promising devices for IMC…

Hardware Architecture · Computer Science 2020-11-03 Sina Sayyah Ensan , Swaroop Ghosh , Seyedhamidreza Motaman , Derek Weast

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

Processing-in-memory (PIM) architectures have demonstrated great potential in accelerating numerous deep learning tasks. Particularly, resistive random-access memory (RRAM) devices provide a promising hardware substrate to build PIM…

Hardware Architecture · Computer Science 2022-02-01 Weidong Cao , Yilong Zhao , Adith Boloor , Yinhe Han , Xuan Zhang , Li Jiang

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

The integration of computing with memory is essential for distributed, massively parallel, and adaptive architectures such as neural networks in artificial intelligence (AI). Accelerating AI can be achieved through photonic computing, but…

Information and communication technologies account for a growing portion of global environmental impacts. While emerging technologies, such as emerging non-volatile memories (eNVM), offer a promising solution to energy efficient computing,…

Hardware Architecture · Computer Science 2026-02-06 Hongbang Wu , Xuesi Chen , Shubham Jadhav , Amit Lal , Lillian Pentecost , Udit Gupta

The quest for energy-efficient, scalable neuromorphic computing has elevated compute-in-memory (CIM) architectures to the forefront of hardware innovation. While memristive memories have been extensively explored for synaptic implementation…

Materials Science · Physics 2025-08-20 Kapil Bhardwaj , Ella Paasio , Sayani Majumdar

Computationally hard combinatorial optimization problems are pervasive in science and engineering, yet their NP-hard nature renders them increasingly inefficient to solve on conventional von Neumann architectures as problem size grows.…

Emerging Technologies · Computer Science 2025-12-22 Yu Qian , Alptekin Vardar , Konrad Seidel , David Lehninger , Maximilian Lederer , Zhiguo Shi , Cheng Zhuo , Kai Ni , Thomas Kämpfe , Xunzhao Yin