Understanding filamentary growth and rupture by Ag ion migration through single-crystalline 2D layered CrPS4

Lee, Mi Jung; Kim, Sung Hoon; Lee, Sangik; Yoon, Chansoo; Min, Kyung‐Ah; Choi, Hyunsoo; Hong, Suklyun; Lee, Sung-Min; Park, Je‐Geun; Ahn, Jae‐Pyoung; Park, Bae Ho

doi:10.1038/s41427-020-00272-x

Cited by 15 publications

(2 citation statements)

References 40 publications

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“…Intercalation of species such as Ag is well reported in other 2D systems too. 37,40,41 The conduction in the HRS state (2 orders higher than the pristine state) is predominantly mediated by electron tunneling across these nodes, with hBN acting as tunnel barrier between interlayer nodes, and vacuum as the barrier between intralayer nodes. In such a self-assembled tunnel network of Ag nodes, application of a small perturbing voltage creates uctuations in the clusters/nodes, dynamically changing the spacing between them, thus giving rise to correlated nanoampere uctuations in tunnel current (Fig.…”

Section: Discussionmentioning

confidence: 99%

Realizing neuromorphic networks at self-organized criticality on a 2D hexagonal BN platform

Nukala

Rao

Sanjay

et al. 2023

Preprint

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Networks and systems which exhibit brain-like behavior can analyze information from intrinsically noisy and unstructured data with very low power consumption. Such characteristics arise due to the critical nature and complex interconnectivity of the brain and its neuronal network. We demonstrate that a system comprising of multilayer hexagonal Boron Nitride (hBN) films contacted with Silver (Ag), that can uniquely host two different self-assembled networks, which are self-organized at criticality (SOC). This system shows bipolar resistive switching between high resistance (HRS) and low resistance states (LRS). In the HRS, Ag clusters (nodes) intercalate in the van der Waals gaps of hBN forming a network of tunnel junctions, whereas the LRS contains a network of Ag filaments. The temporal avalanche dynamics in both these states exhibit power-law scaling, long-range temporal correlation, and SOC. These networks can be tuned from one to another with voltage as a control parameter. For the first time, different neuron-like networks are realized in a single CMOS compatible, 2D materials platform.

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Section: Discussionmentioning

confidence: 99%

Realizing neuromorphic networks at self-organized criticality on a 2D hexagonal BN platform

Nukala

Rao

Sanjay

et al. 2023

Preprint

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“…Intercalation of species such as Ag is well reported in other 2D systems too. 46,49,50 The conduction in the HRS (2 orders higher than the pristine state) is predominantly mediated by electron tunneling across these nodes, with hBN acting as a tunnel barrier between interlayer nodes, and vacuum as the barrier between intralayer nodes. In such a self-assembled tunnel network of Ag nodes, application of a small perturbing voltage creates fluctuations in the clusters/ nodes, dynamically changing the spacing between them, thus giving rise to correlated nanoampere fluctuations in tunnel current (Fig.…”

Section: Discussionmentioning

confidence: 99%

Realizing avalanche criticality in neuromorphic networks on a 2D hBN platform

Rao,

Sanjay,

Dey

et al. 2023

Mater. Horiz.

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High‐Performance Memristors Based on Few‐Layer Manganese Phosphorus Trisulfide for Neuromorphic Computing

Weng,

Zheng,

Lei

et al. 2023

Adv Funct Materials

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While transition‐metal thiophosphate (MPX3) materials have been a subject of extensive research in recent years, experimental studies on MPX3‐based memristors are still in their early stages, with device performance being less than ideal. Here, the successful fabrication of high‐yield, high‐performance, and uniform memristors are demonstrated to possess desired characteristics for neuromorphic computing using a single‐crystalline few‐layered manganese phosphorus trisulfide (MnPS3) as a resistive switching medium. The Ti/MnPS3/Au memristor exhibits small switching voltage (<1 V), long memory retention (104 s), fast switching speed (≈20 ns), high On/Off ratio (nearly two orders of magnitude), and simultaneously achieves emulation of synaptic weight plasticity. The microscopic investigation of the structural and chemical characteristics of the few‐layer MnPS3 reveals the presence of structural defects and residual Ti throughout the stacked layer following the application of voltage, which contributes to the uniformity of switching with a low set voltage. With highly linear and symmetric analog weight updates coupled with the capability of accurate decimal arithmetic operations, a high accuracy of 95.15% in supervised learning using the MNIST handwritten recognition dataset is achieved in the artificial neural network. Furthermore, convolutional image processing can be implemented using hardware multiply‐and‐accumulate operation in an experimental memristor crossbar array.

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Understanding filamentary growth and rupture by Ag ion migration through single-crystalline 2D layered CrPS4

Cited by 15 publications

References 40 publications

Realizing neuromorphic networks at self-organized criticality on a 2D hexagonal BN platform

Realizing neuromorphic networks at self-organized criticality on a 2D hexagonal BN platform

Realizing avalanche criticality in neuromorphic networks on a 2D hBN platform

High‐Performance Memristors Based on Few‐Layer Manganese Phosphorus Trisulfide for Neuromorphic Computing

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