Design of Memristor-Based Combinational Logic Circuits

Liu, Gongzhi; Shen, Shuhang; Jin, Peipei; Wang, Guangyi; Liang, Yan

doi:10.1007/s00034-021-01770-1

Cited by 33 publications

(11 citation statements)

References 21 publications

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“…The simple logic circuits are usually composed of gate circuits, including NOT gate, AND gate, OR gate, NAND gate, NOR gate, XOR gate, and XNOR gate. [188,189] The development of integrated logic circuits confronts the limitations of voltage loss and high energy consumption. [190][191][192] Regarding this, researchers have discovered that the charge doping of 2D materials at the nanoscale holds promise to address the issues of integrated logic circuits.…”

Section: Logic Circuitsmentioning

confidence: 99%

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Emerging MXene‐Based Memristors for In‐Memory, Neuromorphic Computing, and Logic Operation

Ling

Zhang

et al. 2022

Adv Funct Materials

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Confronted by the difficulties of the von Neumann bottleneck and memory wall, traditional computing systems are gradually inadequate for satisfying the demands of future data-intensive computing applications. Recently, memristors have emerged as promising candidates for advanced in-memory and neuromorphic computing, which pave one way for breaking through the dilemma of current computing architecture. Till now, varieties of functional materials have been developed for constructing high-performance memristors. Herein, the review focuses on the emerging 2D MXene materials-based memristors. First, the mainstream synthetic strategies and characterization methods of MXenes are introduced. Second, the different types of MXenebased memristive materials and their widely adopted switching mechanisms are overviewed. Third, the recent progress of MXene-based memristors for data storage, artificial synapses, neuromorphic computing, and logic circuits is comprehensively summarized. Finally, the challenges, development trends, and perspectives are discussed, aiming to provide guidelines for the preparation of novel MXene-based memristors and more engaging information technology applications.

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Section: Logic Circuitsmentioning

confidence: 99%

“…The simple logic circuits are usually composed of gate circuits, including NOT gate, AND gate, OR gate, NAND gate, NOR gate, XOR gate, and XNOR gate. [ 188,189 ]…”

Section: Mxene‐based Memristor Applicationsmentioning

confidence: 99%

Emerging MXene‐Based Memristors for In‐Memory, Neuromorphic Computing, and Logic Operation

Ling

Zhang

et al. 2022

Adv Funct Materials

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“…While there have been reports on two-terminal memristors as cascaded logic in the form of modeled circuits, [46][47][48][49] no physical representation has yet to be achieved. This article presents the first implementation of a synaptic-emulating memristor that demonstrates cascading logical computations with only two p6DTP-based devices and no additional components.…”

Section: Arithmetic and Logic Operationsmentioning

confidence: 99%

Cascaded Logic Gates with Printed Electrochemical Memristors

Grant,

Wanless,

Bandera

et al. 2023

Adv Materials Technologies

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Electrochemical‐based memristors are highly attractive that are capable of nonvolatile analog tuning, long‐term state stability, low power consumption, device scalability, and fast switching speeds. Through the combination of film deposition techniques, i.e., vapor phase polymerization and screen printing, fabrication of a poly(4‐(6‐hexyl)‐4H‐dithieno[3,2‐b:2′,3′‐d]pyrrole) (p6DTP)‐based synaptic‐emulating three‐terminal memristor is designed. Through voltage‐driven pulse programming, and square waves with an amplitude of 100 mV and duration of 100 msec, the device exhibits a power consumption of 1 pJmm−2 per synaptic event. By analyzing the fundamental operational trends of the p6DTP‐based device, simple and advanced integrated applications can be demonstrated along with synaptic‐like responses. This effort is the first presentation of the vapor phase polymerization technique for any dithienopyrrole‐based monomers, along with the physical implementation of any memristive system as an advanced logical circuit, demonstrated here as a cascaded combinational logic gate.

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“…That being said, the memristor, proposed by Professor Cai and manufactured by HP Lab [2], has the characteristics of a small size and a low power consumption, as well as the advantages of nonlinearity and non-volatility. The realization of brain-like intelligence based on memristors can greatly promote the development of artificial neural networks for associative memory [3][4][5][6][7][8][9][10][11][12] and emotional intelligence [13][14][15][16][17][18][19]. With the rapid development of artificial intelligence, more and more people are paying attention to the research on brain-like emotional intelligence [20][21][22][23].…”

Section: Introductionmentioning

confidence: 99%

Multimodal Mood Consistency and Mood Dependency Neural Network Circuit Based on Memristors

Wang

Sun²,

Wang³

et al. 2023

Electronics

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The factors that affect learning efficiency in different environments have been considered in many studies, but multimode mood-consistent learning has not been considered specifically. In this paper, a neural network circuit based on memristors to determine multimode mood consistency and mood dependency was constructed. The circuit is composed of a voltage control module, an emotion module, and a synaptic neuron module. Through the voltage control module and emotion module, learning materials with different properties are input into the synaptic neurons. The learning efficiency of different learning materials under different emotions was analyzed in detail. A dual-channel mood-consistent learning was realized, and the mood dependency was further considered. The influence of different channels on the learning was studied to provide ideas for the future development of intelligent brain-like neural networks.

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Design of Memristor-Based Combinational Logic Circuits

Cited by 33 publications

References 21 publications

Emerging MXene‐Based Memristors for In‐Memory, Neuromorphic Computing, and Logic Operation

Emerging MXene‐Based Memristors for In‐Memory, Neuromorphic Computing, and Logic Operation

Cascaded Logic Gates with Printed Electrochemical Memristors

Multimodal Mood Consistency and Mood Dependency Neural Network Circuit Based on Memristors

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