Quantized Conductance and Switching in Percolating Nanoparticle Films

Sattar, Abdul; Fostner, Shawn; Brown, S. A.

doi:10.1103/physrevlett.111.136808

Cited by 54 publications

(121 citation statements)

References 34 publications

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“…[27]. There it was shown that the probability of obtaining a quantized system conductance when a quantized local conductance was introduced in a tunneling gap increased dramatically as p approached p c ; in that case we replaced the tunnel gaps with the highest field with quantized conductors but did not iteratively solve for a new system conductance, nor did we change V at all.…”

Section: Simulation Detailsmentioning

confidence: 99%

“…We note that in this model the conductance can only increase: These simulations are a deliberate simplification of the experimental situation where decreases in conductance are also observed due to breaking of the atomic scale wires by electromigration [27]. It is intuitively clear that if both creation and breaking of connections is possible there will be random switching of the conductance around some mean value that is determined by the relative probabilities of the two types of events.…”

Section: Simulation Detailsmentioning

confidence: 99%

“…We then identify those gaps with electric fields larger than a chosen threshold (here E th = 0.9) [45] which are then replaced with a large conductor (G Ohmic = 10 −1 ) with probability P ↑ . This process simulates the formation in the tunnel gap of an atomic wire, which occurs due to either electric-field-induced surface diffusion (EFISD) or electric-field-induced evaporation (EFIE) [27,[46][47][48]. We then recalculate the conductance of the network G. At the next voltage step the process is repeated; the voltage ramps continue until the system conductance converges-typically to within 0.1% of the value on the previous step.…”

Section: Simulation Detailsmentioning

confidence: 99%

“…In this system the random deposition of the nanoparticles leads to formation of a complex percolating [31] network comprising groups of particles separated by tunnel gaps. When a voltage is applied across the system the local electric field across the tunnel gaps can be very high resulting in switching events driven by the formation of atomic scale wires in the gaps [27]. Here we model electrical transport across these devices and demonstrate that this complex system fulfills at least some of the criteria for neuromorphic behavior.…”

Section: Introductionmentioning

confidence: 99%

“…We have recently [27] reported switching behavior (along with quantized conduction [28][29][30] at room temperature) in devices composed of tin nanoparticles. In this system the random deposition of the nanoparticles leads to formation of a complex percolating [31] network comprising groups of particles separated by tunnel gaps.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Neuromorphic behavior in percolating nanoparticle films

Fostner

Brown

2015

Phys. Rev. E

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We show that the complex connectivity of percolating networks of nanoparticles provides a natural solid-state system in which bottom-up assembly provides a route to realization of neuromorphic behavior. Below the percolation threshold the networks comprise groups of particles separated by tunnel gaps; an applied voltage causes atomic scale wires to form in the gaps, and we show that the avalanche of switching events that occurs is similar to potentiation in biological neural systems. We characterize the level of potentiation in the percolating system as a function of the surface coverage of nanoparticles and other experimentally relevant variables, and compare our results with those from biological systems. The complex percolating structure and the electric field driven switching mechanism provide several potential advantages in comparison to previously reported solid-state neuromorphic systems.

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Section: Simulation Detailsmentioning

confidence: 99%

Section: Simulation Detailsmentioning

confidence: 99%

Section: Simulation Detailsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Neuromorphic behavior in percolating nanoparticle films

Fostner

Brown

2015

Phys. Rev. E

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Direct Observation of Conversion Between Threshold Switching and Memory Switching Induced by Conductive Filament Morphology

Sun

Liu

et al. 2014

Adv Funct Materials

285

221

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Although the kinetics of CF formation/ dissolution is still unclear, it is widely accepted that the CF formation/dissolution is strongly related to the electromigration and electrochemical reaction of anion (i.e., oxygen vacancy) [13][14][15][16] or cation (i.e., Cu 2+ , Ag + or Ni 2+ ). [17][18][19][20][21][22] Generally, RS behavior can be classifi ed as two modes: nonvolatile memory switching (MS) and volatile threshold switching (TS). In the MS mode, both LRS and HRS can be maintained after removing the external voltage, while the LRS in the TS mode will be back to the HRS once the applied voltage is smaller than a critical value. [23][24][25] To avoid confusion with MS, the LRS and HRS in TS are renamed as "TS ON-state" and "TS OFFstate" in this article. The MS device can be used for the non-volatile data storage [1][2][3][4][5] while TS device can be as a selector in series with memory cell to suppress crosstalk effect in the crossbar array. [26][27][28][29][30] Recently, some groups reported that TS and MS can coexist and mutually transform in a single device at suitable external excitation. [23][24][25][26][27][28] Several models have been proposed to explain this phenomenon, including CF thermal instability, [ 23 ] strong electron correlation effect, [ 24 ] quantum-wire model, [ 25 ] interface barrier modulation, [ 26 ] and space charge effect. [ 27 ] However, the underlying mechanism of the phenomenon is still unclear, especially lacking of direct evidences to uncover when and how the two RS modes happen and what is the internal relationship between them.Here, we demonstrate that the TS and MS modes can be modulated in the Ag/SiO 2 /Pt structure by controlling the compliance current ( I CC ) in electroforming. We systematically investigate the morphologies, chemical components, and dynamic growth of the CF using scanning electron microscope (SEM), high-resolution transmission electron microscopy (HRTEM) and electron energy loss spectroscopy (EELS) analysis. The results confi rm that the TS and MS modes correspond to the CF consisting of isolated and continuous Ag nanocrystals, respectively. In addition, by Kelvin probe force microscopy (KPFM) studies, the voltage potential distribution of CF in the ON-and OFF-state further indicate that the TS mode is Volatile threshold switching (TS) and non-volatile memory switching (MS) are two typical resistive switching (RS) phenomena in oxides, which could form the basis for memory, analog circuits, and neuromorphic applications. Interestingly, TS and MS can be coexistent and converted in a single device under the suitable external excitation. However, the origin of the transition from TS to MS is still unclear due to the lack of direct experimental evidence. Here, conversion between TS and MS induced by conductive fi lament (CF) morphology in Ag/SiO 2 /Pt device is directly observed using scanning electron microscopy and high-resolution transmission electron microscopy. The MS mechanism is related to the formation and dissolution of CF consisting of continuous Ag...

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Resistive Switching Effect in Ag‐poly(ethylene Glycol) Nanofluids: Novel Avenue Toward Neuromorphic Materials

Nikitin,

Biliak,

Pleskunov

et al. 2023

Adv Funct Materials

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Conventional computation techniques face challenges of deviations in Moore's law and the high‐power consumption of data‐centric computation tasks. Neuromorphic engineering attempts to overcome these issues by taking inspiration from neuron assemblies, ranging from distributed synaptic plasticity through orchestration of oscillator‐like action potential toward avalanche dynamics. Although solid networks of nanoparticles (NPs) are proven to replicate fingerprints of criticality and brain‐like dynamics, the aspect of dynamic spatial reconfigurations in the connectivity of networks remains unexplored. In this work, Ag/poly(ethylene glycol) (PEG) nanofluids are demonstrated as potential systems to mimic the spatio‐temporal reconfiguration of network connections. The nanofluids are prepared by directly loading Ag NPs from the gas aggregation cluster source into liquid PEG. The NPs exhibit a negative zeta potential in PEG; if the potential difference is applied between two electrodes submerged in this nanofluid, the NPs migrate toward the anode, accumulate in its vicinity, and form a conductive path. Spikes of electric current passing through the path are detected, accompanied by resistive switching phenomena, similar to the random switching dynamics in solid NPs networks. The unique behavior of Ag/PEG nanofluids makes them promising for the realization of spatio‐temporal reconfigurations in network topologies with the potential to transition to 3D.

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Quantized Conductance and Switching in Percolating Nanoparticle Films

Cited by 54 publications

References 34 publications

Neuromorphic behavior in percolating nanoparticle films

Neuromorphic behavior in percolating nanoparticle films

Direct Observation of Conversion Between Threshold Switching and Memory Switching Induced by Conductive Filament Morphology

Resistive Switching Effect in Ag‐poly(ethylene Glycol) Nanofluids: Novel Avenue Toward Neuromorphic Materials

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