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Neuromorphic computing aims to replicate the brain's remarkable energy efficiency and parallel processing capabilities for large-scale artificial intelligence applications. In this work, we present a comprehensive comparative study of three…

Neural and Evolutionary Computing · Computer Science 2025-05-08 Logan Larsh , Raiyan Siddique , Sarah Sharif Yaser Mike Banad

Antiferromagnets are promising materials for future spintronic applications due to their unique properties including zero stray fields, robustness versus external magnetic fields and ultrafast dynamics, which have attracted extensive…

Mesoscale and Nanoscale Physics · Physics 2021-08-18 Xue Liang , Jing Xia , Xichao Zhang , Motohiko Ezawa , Oleg A. Tretiakov , Xiaoxi Liu , Lei Qiu , Guoping Zhao , Yan Zhou

Magnetic skyrmions, due to their topological stability and high mobility, are strong candidates for information carriers in spintronic devices. To advance their practical applications, a detailed understanding of their nucleation and…

Materials Science · Physics 2025-09-09 Tamali Mukherjee , V Satya Narayana Murthy , Banasree Sadhukhan

In 2D-semiconductor-based field-effect transistors and optoelectronic devices, metal-semiconductor junctions are one of the crucial factors determining device performance. The Fermi-level (FL) pinning effect, which commonly caused by…

Ferroelectrics offer a promising materials platform to realize energy-efficient non-volatile memory technology with the FeFET-based implementations being one of the most area-efficient ferroelectric memory architectures. However, the FeFET…

Systems and Control · Electrical Eng. & Systems 2021-08-30 Jaykumar Vaidya , R S Surya Kanthi , Shamiul Alam , Nazmul Amin , Ahmedullah Aziz , Nikhil Shukla

Deep 'Analog Artificial Neural Networks' (ANNs) perform complex classification problems with remarkably high accuracy. However, they rely on humongous amount of power to perform the calculations, veiling the accuracy benefits. The…

Emerging Technologies · Computer Science 2018-04-17 Parami Wijesinghe , Aayush Ankit , Abhronil Sengupta , Kaushik Roy

This work proposes a novel logic device (SkyLogic) based on skyrmions, which are magnetic vortex-like structures that have low depinning current density and are robust to defects. A charge current sent through a polarizer ferromagnet (P-FM)…

Emerging Technologies · Computer Science 2019-05-01 Meghna G. Mankalale , Zhengyang Zhao , Jian-Ping Wang , Sachin S. Sapatnekar

Nanotransistors typically operate in far-from-equilibrium (FFE) conditions, that cannot be described neither by drift-diffusion, nor by purely ballistic models. In carbonbased nanotransistors, source and drain contacts are often…

Mesoscale and Nanoscale Physics · Physics 2010-07-01 Paolo Michetti , Giuseppe Iannaccone

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…

The problem of Fermi-level pinning at semiconductor-metal contacts is readdressed starting from first-principles calculations for Al/GaAs. We give quantitative evidence that the Schottky barrier height is very little affected by any…

Materials Science · Physics 2009-10-30 Alice Ruini , Raffaele Resta , Stefano Baroni

Learning and logic are fundamental brain functions that make the individual to adapt to the environment, and such functions are established in human brain by modulating ionic fluxes in synapses. Nanoscale ionic/electronic devices with…

Materials Science · Physics 2013-04-29 Chang Jin Wan , Li Qiang Zhu , Yi Shi , Qing Wan

The multiple ferroelectric polarization tuned by external electric field could be used to simulate the biological synaptic weight. Ferroelectric synaptic devices have two advantages compared with other reported ones: One is the intrinsic…

Applied Physics · Physics 2020-07-17 Bobo Tian , Ni Zhong , Chungang Duan

Much attention has been focused on the design of low barrier nanomagnets (LBM), whose magnetizations vary randomly in time owing to thermal noise, for use in binary stochastic neurons (BSN) which are hardware accelerators for machine…

Mesoscale and Nanoscale Physics · Physics 2023-01-24 Md Ahsanul Abeed , Supriyo Bandyopadhyay

Spin-based memories are attractive for their non-volatility and high durability but provide modest resistance changes, whereas semiconductor logic transistors are capable of large resistance changes, but lack memory function with high…

In the quest for reliable and power-efficient memristive devices, ferroelectric tunnel junctions are being investigated as potential candidates. CMOS-compatible ferroelectric hafnium oxides are at the forefront. However, in epitaxial tunnel…

Neuro-symbolic artificial intelligence (AI) excels at learning from noisy and generalized patterns, conducting logical inferences, and providing interpretable reasoning. Comprising a 'neuro' component for feature extraction and a 'symbolic'…

In tunnel junctions with ferroelectric barriers, switching the polarization direction modifies the electrostatic potential profile and the associated average tunnel barrier height. This results in strong changes of the tunnel transmission…

Mesoscale and Nanoscale Physics · Physics 2014-02-07 S. Boyn , S. Girod , V. Garcia , S. Fusil , S. Xavier , C. Deranlot , H. Yamada , C. Carrétéro , E. Jacquet , M. Bibes , A. Barthélémy , J. Grollier

Spin field-effect transistors (SFETs) are promising candidates for low-power spin-based electronics, yet existing realizations that rely on spin-orbit coupling are constrained by limited material choices and short spin-coherence lengths.…

Materials Science · Physics 2025-12-03 Ziye Zhu , Xianzhang Chen , Xunkai Duan , Zhou Cui , Jiayong Zhang , Igor Zutic , Tong Zhou

Continued progress in high speed computing depends on breakthroughs in both materials synthesis and device architectures. The performance of logic and memory can be enhanced significantly by introducing a memristor, a two terminal device…

Mesoscale and Nanoscale Physics · Physics 2015-04-08 V. K. Sangwan , D. Jariwala , I. S. Kim , K. -S. Chen , T. J. Marks , L. J. Lauhon , M. C. Hersam

In this letter, we quantify the impact of device limitations on the classification accuracy of an artificial neural network, where the synaptic weights are implemented in a Ferroelectric FET (FeFET) based in-memory processing architecture.…

Emerging Technologies · Computer Science 2019-08-22 Insik Yoon , Matthew Jerry , Suman Datta , Arijit Raychowdhury
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