摘要
In recent years,the emergence of numerous applications of artificial intelligence(AI)has sparked a new technological revolution.These applications include facial recognition,autonomous driving,intelligent robotics,and image restoration.However,the data processing and storage procedures in the conventional von Neumann architecture are discrete,which leads to the“memory wall”problem.As a result,such architecture is incompatible with AI requirements for efficient and sustainable processing.Exploring new computing architectures and material bases is therefore imperative.Inspired by neurobiological systems,in-memory and in-sensor computing techniques provide a new means of overcoming the limitations inherent in the von Neumann architecture.The basis of neural morphological computation is a crossbar array of high-density,high-efficiency non-volatile memory devices.Among the numerous candidate memory devices,ferroelectric memory devices with non-volatile polarization states,low power consumption and strong endurance are expected to be ideal candidates for neuromorphic computing.Further research on the complementary metal-oxide-semiconductor(CMOS)compatibility for these devices is underway and has yielded favorable results.Herein,we first introduce the development of ferroelectric materials as well as their mechanisms of polarization reversal and detail the applications of ferroelectric synaptic devices in artificial neural networks.Subsequently,we introduce the latest developments in ferroelectrics-based in-memory and in-sensor computing.Finally,we review recent works on hafnium-based ferroelectric memory devices with CMOS process compatibility and give a perspective for future developments.
基金
supported by National Key Research and Development Program of China(2021YFA1200700)
The National Natural Science Foundation of China(T2222025 and 62174053)
Open Research Projects of Zhejiang Lab(2021MD0AB03)
Shanghai Science and Technology Innovation Action Plan(21JC1402000 and 21520714100)
the Fundamental Research Funds for the Central Universities。
作者简介
Dong Wang,received his B.S.degree in College of Electrical Engineering from Nantong University,Jiangsu Province,China in 2020.Now,he is currently pursuing M.S degree in School of physics and Electronic science from East China Normal University,Shanghai,China.His major research interest is artificial synaptic devices based on ferroelectric materials;Corresponding authors:Shenglan Hao.(BRID:00981.00.86563)received her B.E.degree in 2015 from Hebei Normal University,her M.Sc.degree in 2018 from Shaanxi Normal University,and her Ph.D.degree in January 2022 from Paris-Saclay University.Her Ph.D.project is about ferroelectric photovoltaics to find novel photovoltaics materials and improve optical absorption.Shenglan Hao is doing a post-doc at East China Normal University,and her current research focuses on the ferroelectric photovoltaic synapses for neuromorphic computing.E-mail addresses:slhao@phy.ecnu.edu.cn;Corresponding authors:Bobo Tian.(BRID:06156.00.21887)earned his Ph.D.in Microelectronics and Solid-State Electronics from the Shanghai Institute of Technical Physics(SITP)of the Chinese Academy of Sciences,Shanghai,China and CentraleSupélec,UniversitéParis-Saclay,Paris,France in 2016.Then he joined in East China Normal University,Shanghai,China.He has been a professor at the Key Lab of Polar Materials and Devices(MOE),East China Normal University since 2019.He was selected by Excellent Young Scientists Fund awarded by the National Natural Science Foundation of China(NSFC)in 2022.He is now the director assistant of Shanghai Center of Brain-inspired Intelligent Materials and Devices,Shanghai,China.His group is currently working on ferroelectric memory and neuromorphic computing.He has published over 80 papers in journals such as Nat.Electron.,Nat.Commun.,Appl.Phys.Rev.,and Adv.Funct.Mater.,etc.E-mail addresses:bbtian@ee.ecnu.edu.cn。
