Ferroelectric Domain Wall Memory and Logic

Sun, Jie; Jiang, An-Quan; Sharma, Pankaj

doi:10.1021/acsaelm.3c00928

Cited by 6 publications

(1 citation statement)

References 164 publications

(245 reference statements)

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“…Likewise, non-volatile memory is crucial for retaining information even when power is disconnected, offering energy efficiency and data persistence advantages. Sun et al (2023) explore the implications of LiNbO 3 's ferroelectricity in non-volatile memory applications. The study investigates ferroelectric field-effect transistors based on LiNbO 3 , highlighting its potential for highdensity memory storage.…”

Section: Non-volatility and Low Power Consumptionmentioning

confidence: 99%

LiNbO3-based memristors for neuromorphic computing applications: a review

Kibebe,

Liu

2024

Front. Electron. Mater

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Neuromorphic computing is a promising paradigm for developing energy-efficient and high-performance artificial intelligence systems. The unique properties of lithium niobate-based (LiNbO3)-based memristors, such as low power consumption, non-volatility, and high-speed switching, make them ideal candidates for synaptic emulation in neuromorphic systems. This study investigates the potential of LiNbO3-based memristors to revolutionize neuromorphic computing by exploring their synaptic behavior and optimizing device parameters, as well as harnessing the potential of LiNbO3-based memristors to create efficient and high-performance neuromorphic computing systems. By realizing efficient and high-speed neural networks, this literature review aims to pave the way for innovative artificial intelligence systems capable of addressing complex real-world challenges. The results obtained from this investigation will be crucial for future researchers and engineers working on designing and implementing LiNbO3-based neuromorphic computing architectures.

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Section: Non-volatility and Low Power Consumptionmentioning

confidence: 99%

LiNbO3-based memristors for neuromorphic computing applications: a review

Kibebe,

Liu

2024

Front. Electron. Mater

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Multi‐Functional Ferroelectric Domain Wall Nanodevices for In‐Memory Computing and Light Sensing

Zhang,

Li,

Zhang

et al. 2024

Adv Funct Materials

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In‐memory computing and sensing can break through the limit of the traditional Von Neumann architecture where information storing and computing units are separated. Recently the topographic creation of a ferroelectric domain wall in separation of two antiparallel domains in LiNbO3 single‐crystal films integrated with the Si substrate has been the focus of such research. Here, the additional freedom of the light stimulus is reported to modulate the domain wall current significantly, enabling applications in nonvolatile domain wall memory, photodetector, and image recognition processor. These measurements shows the fantastic photosensitivity of 2D domain walls where the photocurrent varies nonlinearly against the accumulative pulse number. With this observation, an associated learning model is constructed to stimulate neuromorphic computing (with a recognition accuracy of 90%) using an artificial neuromorphic network of domain walls. The research promotes the multifold development of artificial intelligence using domain‐wall nanodevices sensitive to both optical and electrical stimulus.

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Oxygen vacancies stabilized 180° charged domain walls in ferroelectric hafnium oxide

Xu,

Zhu,

Zhao

et al. 2024

Applied Physics Letters

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Ferroelectric domain walls (DWs) are spatial interfaces separating domains with distinct polarization orientations. Among these DWs, some can carry bound charges and display metallic-like conductivity. The feature is highly of interest for future nanoelectronics. However, the inherent instability of charged domain walls (CDWs) has posed a critical challenge for their experimental exploration. This Letter reports the head-to-head (HH) and tail-to-tail (TT) 180° CDWs within the context of ferroelectric hafnium oxide. We proposed that oxygen vacancy is a crucial factor stabilizing the periodic CDWs. Through meticulous first-principles calculations, we elaborated on the intricate properties of these CDWs, including their polarization profiles, and potential and charge distributions. Furthermore, we calculated the energy barrier for layer-by-layer propagation of a HH wall and carefully discussed the migration of a TT wall with oxygen vacancy. Our study can shed more light onto the characteristics of CDWs and their implications to hafnia-based ferroelectric devices.

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Ferroelectric Domain Wall Memory and Logic

Cited by 6 publications

References 164 publications

LiNbO3-based memristors for neuromorphic computing applications: a review

LiNbO3-based memristors for neuromorphic computing applications: a review

Multi‐Functional Ferroelectric Domain Wall Nanodevices for In‐Memory Computing and Light Sensing

Oxygen vacancies stabilized 180° charged domain walls in ferroelectric hafnium oxide

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