Results 31 to 40 of about 267 (149)

Ultra-dense co-integration of FeFETs and CMOS logic enabling very-fine grained Logic-in-Memory

, 2022
Ferroelectric field-effect transistors (FeFET) based on hafnium oxide offer great opportunities for Logic-in-Memory applications, due to their natural ability to combine logic (transistor) and memory (ferroelectric material), their low-power operation ...
Breyer, Evelyn T., Trommer, Jens, Melde, Thomas, Beyer, Sven, Dünkel, Stefan, Slesazeck, Stefan, Mulaosmanovic, Halid, Trentzsch, Martin, Mikolajick, Thomas   +8 more
core   +1 more source

Powering Disturb-Free Reconfigurable Computing and Tunable Analog Electronics with Dual-Port Ferroelectric FET

, 2023
Single-port ferroelectric FET (FeFET) that performs write and read operations on the same electrical gate prevents its wide application in tunable analog electronics and suffers from read disturb, especially to the high-threshold voltage (VTH) state as ...
Amrouch, Hussam, Chauhan, Yogesh Singh, Kleimaier, Dominik, Mohamed, Mohamed, Beyer, Sven, Xu, Yixin, Mulaosmanovic, Halid, Chatterjee, Swetaki, Ni, Kai, Joshi, Rajiv, Zhao, Zijian, Xiao, Yi, Duenkel, Stefan, Deng, Shan, Jiang, Zhouhang, Islam, Muhammad Shaffatul, Narayanan, Vijaykrishnan, Meninger, Scott   +17 more
core  

Ultra-low power flexible precision FeFET based analog in-memory computing

, 2022
S.29.2.1-29.2.4This paper presents an efficient crossbar design and implementation intended for analog compute-in-memory (ACiM) acceleration of artificial neural networks based on ferroelectric FET (FeFET) technology.
Müller, F., Kirchner, T., Ali, T., Lederer, M., Hoffmann, T., Sudarshan, C., Guntoro, A., Soliman, T., Karimov, E., Kämpfe, T., Ganem, H., Wehn, N.   +11 more
core   +1 more source

Neuromorphic Electronics for Intelligence Everywhere: Emerging Devices, Flexible Platforms, and Scalable System Architectures

Advanced Materials, EarlyView.
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj, Roshni Satheesh Babu, Yuxin Xia, Eva Bestelink, Radu Sporea, Nikos Hastas, Ioannis Zeimpekis, Dimitra G. Georgiadou, Sayani Majumdar   +8 more
wiley   +1 more source

FeFET-based Binarized Neural Networks Under Temperature-dependent Bit Errors

, 2021
Ferroelectric FET (FeFET) is a highly promising emerging non-volatile memory (NVM) technology, especially for binarized neural network (BNN) inference on the low-power edge.
Gupta, Aniket, Henkel, Jorg, Amrouch, Hussam, Yayla, Mikail, Chen, Kuan-Hsun, Morik, Katharina, Buschjager, Sebastian, Chen, Jian-Jia   +7 more
core   +1 more source

Ferroelectric Devices for In‐Memory and In‐Sensor Computing

Advanced Science, EarlyView.
Inspired by biological systems, in‐memory and in‐sensor computing overcome von Neumann bottlenecks. Ferroelectric devices can mimic synaptic functions and sense stimuli like light or force, therefore are ideal for these paradigms. This review introduces the ferroelectric devices applied for in‐memory and in‐sensor computing, covering their structures ...
Hong Fang, Ronghuan Xie, Qiang Cao, Shishen Yan, Xiaolin Wang, Limei Zheng   +5 more
wiley   +1 more source

Sustainable Synaptic Device with Two‐Dimensional Ferroelectric Materials for Neuromorphic Computing

Advanced Science, EarlyView.
α‐In2Se3 based FeSFETs can be utilized as sustainable devices through polarization switching governed by both out‐of‐plane and in‐plane polarizations. Upon reaching a fatigued state, current annealing enabled by conductance modulation can significantly enhance the endurance of FeSFETs.
Jaewook Yoo, Seokjin Oh, Minah Park, Jong Min Song, Hongseung Lee, Seohyeon Park, Sojin Jung, Seongbin Lim, Soohyun Lim, Dongsun Shin, Ji Won Heo, TaeWan Kim, Hagyoul Bae   +12 more
wiley   +1 more source

Neuromorphic Near‐Sensor and In‐Sensor Computing Enabled by Next‐Generation Material‐Based Sensors

Advanced Science, EarlyView.
This Review presents a structural framework that classifies neuromorphic sensing into near‐sensor and in‐sensor architectures, clarifying physical coupling between sensing and computation. The framework connects neural and synaptic device functions with recent advances in optical, mechanical, and chemical sensing, compares energy consumption and ...
Su Yeon Jung, Gwang Ya Kim, Sejin Kim, Hyunjong Seo, Se Gi Lee, Sang Min Won, Dongjoon Rhee, Joohoon Kang   +7 more
wiley   +1 more source

The Effect of Ferroelectric/Dielectric Capacitance Ratio on Short-Term Retention Characteristics of MFMIS FeFET

IEEE Journal of the Electron Devices Society
Metal-ferroelectric-metal-insulator-semiconductor (MFMIS) FeFETs have significant potential for use in non-volatile memory applications. This is primarily due to their compatibility with CMOS technology and reliable switching characteristics.
Junghyeon Hwang, Giuk Kim, Hongrae Joh, Jinho Ahn, Sanghun Jeon   +4 more
doaj   +1 more source

Fundamental Challenges, Physical Implementations, and Integration Strategies for Ising Machines in Large‐Scale Optimization Tasks

Advanced Electronic Materials, EarlyView.
Ising machines are emerging as specialized hardware solvers for computationally hard optimization problems. This review examines five major platforms—digital CMOS, analog CMOS, emerging devices, coherent optics, and quantum systems—highlighting physics‐rooted advantages and shared bottlenecks in scalability and connectivity.
Hyunjun Lee, Joon Pyo Kim, Sanghyeon Kim
wiley   +1 more source