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用于多功能内存计算的双铁电耦合工程二维晶体管

Dual-Ferroelectric-Coupling-Engineered Two-Dimensional Transistors for Multifunctional In-Memory Computing.

作者信息

Luo Zheng-Dong, Zhang Siqing, Liu Yan, Zhang Dawei, Gan Xuetao, Seidel Jan, Liu Yang, Han Genquan, Alexe Marin, Hao Yue

机构信息

State Key Discipline Laboratory of Wide Band Gap Semiconductor Technology, School of Microelectronics, Xidian University, Xi'an 710071, P. R. China.

School of Materials Science and Engineering, UNSW Sydney, Sydney, NSW 2052, Australia.

出版信息

ACS Nano. 2022 Feb 22;16(2):3362-3372. doi: 10.1021/acsnano.2c00079. Epub 2022 Feb 11.

Abstract

In-memory computing featuring a radical departure from the von Neumann architecture is promising to substantially reduce the energy and time consumption for data-intensive computation. With the increasing challenges facing silicon complementary metal-oxide-semiconductor (CMOS) technology, developing in-memory computing hardware would require a different platform to deliver significantly enhanced functionalities at the material and device level. Here, we explore a dual-gate two-dimensional ferroelectric field-effect transistor (2D FeFET) as a basic device to form both nonvolatile logic gates and artificial synapses, addressing in-memory computing simultaneously in digital and analog spaces. Through diversifying the electrostatic behaviors in 2D transistors with the dual-ferroelectric-coupling effect, rich logic functionalities including linear (AND, OR) and nonlinear (XNOR) gates were obtained in unipolar (MoS) and ambipolar (MoTe) FeFETs. Combining both types of 2D FeFETs in a heterogeneous platform, an important computation circuit, i.e., a half-adder, was successfully constructed with an area-efficient two-transistor structure. Furthermore, with the same device structure, several key synaptic functions are shown at the device level, and an artificial neural network is simulated at the system level, manifesting its potential for neuromorphic computing. These findings highlight the prospects of dual-gate 2D FeFETs for the development of multifunctional in-memory computing hardware capable of both digital and analog computation.

摘要

与冯·诺依曼架构截然不同的内存计算,有望大幅降低数据密集型计算的能耗和时间消耗。随着硅互补金属氧化物半导体(CMOS)技术面临的挑战日益增加,开发内存计算硬件需要一个不同的平台,以便在材料和器件层面显著增强功能。在此,我们探索将双栅二维铁电场效应晶体管(2D FeFET)作为一种基本器件,用于形成非易失性逻辑门和人工突触,同时在数字和模拟空间中实现内存计算。通过利用双铁电耦合效应使二维晶体管中的静电行为多样化,在单极(MoS)和双极(MoTe)铁电场效应晶体管中获得了包括线性(与门、或门)和非线性(异或非门)门在内的丰富逻辑功能。在一个异构平台中结合这两种类型的二维铁电场效应晶体管,成功构建了一个重要的计算电路,即一个半加器,其采用了面积高效的双晶体管结构。此外,利用相同的器件结构,在器件层面展示了几种关键的突触功能,并在系统层面模拟了一个人工神经网络,证明了其在神经形态计算方面的潜力。这些发现突出了双栅二维铁电场效应晶体管在开发能够进行数字和模拟计算的多功能内存计算硬件方面的前景。

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