Monolithic 3D integration of 2D transistors and vertical RRAMs in 1T–4R structure for high-density memory

Xie, Maosong; Jia, Yueyang; Nie, Chen; Liu, Zuheng; Tang, Alvin; Fan, Shiquan; Liang, Xiaoyao; Jiang, Li; He, Zhezhi; Yang, Rui

doi:10.1038/s41467-023-41736-2

Cited by 6 publications

(3 citation statements)

References 70 publications

(91 reference statements)

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“…Further optimizations have to be focused both at the device architectural level and at the material selection choices to minimise issues like the high ON current observed in RRAM devices. Device architectural innovations like multi-terminal device design [ 172 ], 3D stacking [ 173 ], interface & filament modulation [ 174 ], defect engineering [ 175 ], etc. have been effective in mitigating RRAM device-level non-idealities.…”

Section: Challenges and Future Outlookmentioning

confidence: 99%

Resistive Switching Devices for Neuromorphic Computing: From Foundations to Chip Level Innovations

Udaya Mohanan

2024

Nanomaterials

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Neuromorphic computing has emerged as an alternative computing paradigm to address the increasing computing needs for data-intensive applications. In this context, resistive random access memory (RRAM) devices have garnered immense interest among the neuromorphic research community due to their capability to emulate intricate neuronal behaviors. RRAM devices excel in terms of their compact size, fast switching capabilities, high ON/OFF ratio, and low energy consumption, among other advantages. This review focuses on the multifaceted aspects of RRAM devices and their application to brain-inspired computing. The review begins with a brief overview of the essential biological concepts that inspire the development of bio-mimetic computing architectures. It then discusses the various types of resistive switching behaviors observed in RRAM devices and the detailed physical mechanisms underlying their operation. Next, a comprehensive discussion on the diverse material choices adapted in recent literature has been carried out, with special emphasis on the benchmark results from recent research literature. Further, the review provides a holistic analysis of the emerging trends in neuromorphic applications, highlighting the state-of-the-art results utilizing RRAM devices. Commercial chip-level applications are given special emphasis in identifying some of the salient research results. Finally, the current challenges and future outlook of RRAM-based devices for neuromorphic research have been summarized. Thus, this review provides valuable understanding along with critical insights and up-to-date information on the latest findings from the field of resistive switching devices towards brain-inspired computing.

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Section: Challenges and Future Outlookmentioning

confidence: 99%

Resistive Switching Devices for Neuromorphic Computing: From Foundations to Chip Level Innovations

Udaya Mohanan

2024

Nanomaterials

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“…As the fourth fundamental element, memristors have recently been utilized as artificial synapses and neurons in neuromorphic architectures due to their simplicity and power efficiency and have been found to be a promising candidate for artificial synapses and neurons [12,[22][23][24][25][26][27]. Additionally, more reports have proven that emerging two-dimensional (2D) layered materials are being actively and innovatively used in memristive devices to make a more intelligent electronic synapse [28][29][30][31][32][33]. Y. Gogotsi et al discovered that MXenes have catalyzed the development of a vast and rapidly growing array of 2D materials [34][35][36].…”

Section: Introductionmentioning

confidence: 99%

Realization of Empathy Capability for the Evolution of Artificial Intelligence Using an MXene(Ti3C2)-Based Memristor

Wang,

Zhang,

Wang

et al. 2024

Electronics

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Empathy is the emotional capacity to feel and understand the emotions experienced by other human beings from within their frame of reference. As a unique psychological faculty, empathy is an important source of motivation to behave altruistically and cooperatively. Although human-like emotion should be a critical component in the construction of artificial intelligence (AI), the discovery of emotional elements such as empathy is subject to complexity and uncertainty. In this work, we demonstrated an interesting electrical device (i.e., an MXene (Ti3C2) memristor) and successfully exploited the device to emulate a psychological model of “empathic blame”. To emulate this affective reaction, MXene was introduced into memristive devices because of its interesting structure and ionic capacity. Additionally, depending on several rehearsal repetitions, self-adaptive characteristic of the memristive weights corresponded to different levels of empathy. Moreover, an artificial neural system was designed to analogously realize a moral judgment with empathy. This work may indicate a breakthrough in making cool machines manifest real voltage-motivated feelings at the level of the hardware rather than the algorithm.

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“…[1,[13][14][15] In particular, recent notable achievements in the monolithic 3D integration of 2D materials or advanced memory demonstrate significant potential for the advancement of diverse processor technology. [16,17] However, several challenges hinder the use of graphene in interconnect applications. First, the growth of highly crystalline graphene using chemical vapor deposition (CVD) technology necessitates a high-temperature process above 800 °C.…”

Section: Introductionmentioning

confidence: 99%

Optimizing Ultrathin 2D Transistors for Monolithic 3D Integration: A Study on Directly Grown Nanocrystalline Interconnects and Buried Contacts

Bae,

Ryu,

Kim

et al. 2024

Advanced Materials

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The potential of monolithic 3D integration technology is largely dependent on the enhancement of interconnect characteristics which can lead to thinner stacks, better heat dissipation, and reduced signal delays. Carbon materials such as graphene, characterized by sp2 hybridized carbons, are promising candidates for future interconnects due to their exceptional electrical, thermal conductivity and resistance to electromigration. However, a significant challenge lies in achieving low contact resistance between extremely thin semiconductor channels and graphitic materials. To address this issue, we propose an innovative wafer‐scale synthesis approach that enables low contact resistance between dry‐transferred 2D semiconductors and as‐grown nanocrystalline graphitic interconnects. A hybrid graphitic interconnect with metal doping reduced the sheet resistance by 84% compared to an equivalent thickness metal‐film. Furthermore, the introduction of a buried graphitic contact resulted in a contact resistance that is 17‐times lower than that of bulk metal contacts (>40 nm). Transistors with this optimal structure were used to successfully demonstrate a simple logic function. The thickness of active layer was maintained within sub‐7 nm range, encompassing both channels and contacts. The ultra‐thin transistor and interconnect stack developed in this work, characterized by a readily etchable interlayer and low parasitic resistance, leads to heterogeneous integration of future 3D ICs.This article is protected by copyright. All rights reserved

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Monolithic 3D integration of 2D transistors and vertical RRAMs in 1T–4R structure for high-density memory

Cited by 6 publications

References 70 publications

Resistive Switching Devices for Neuromorphic Computing: From Foundations to Chip Level Innovations

Resistive Switching Devices for Neuromorphic Computing: From Foundations to Chip Level Innovations

Realization of Empathy Capability for the Evolution of Artificial Intelligence Using an MXene(Ti3C2)-Based Memristor

Optimizing Ultrathin 2D Transistors for Monolithic 3D Integration: A Study on Directly Grown Nanocrystalline Interconnects and Buried Contacts

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