Stable Millivolt Range Resistive Switching in Percolating Molybdenum Nanoparticle Networks

To overcome the limitations of the conventional Von Neumann architecture, inspiration from the mammalian brain has led to the development of nanoscale neuromorphic networks. In the present research, molybdenum nanoparticles (NPs), which were produced by means of gas phase condensation based on magnetron sputtering, are shown to be the constituents of electrically percolating networks that exhibit stable, complex, neuron-like spiking behavior at low potentials in the millivolt range, satisfying well the requirement of low energy consumption. Characterization of the NPs using both scanning electron microscopy and scanning transmission electron microscopy revealed not only pristine shape, size, and density control of Mo NPs but also a preliminary proof of the working mechanism behind the spiking behavior due to filament formations. Furthermore, electrostatics COMSOL Multiphysics simulations of the morphology of the NPs provided evidence that the stable switching is due to the as-deposited stellate Mo NPs creating high electric field strengths, while keeping them separated, not seen before in other percolating networks based on spherical NPs. Hence, our results show the working mechanism behind switching in percolating Mo NP networks and show that they are very promising for realistic neuromorphic systems.

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Publication Details

Journal
ACS Applied Materials & Interfaces
Published
2024-11-13
DOI
https://doi.org/10.1021/acsami.4c12051
Citations
7
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
1.46

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article

Stable Millivolt Range Resistive Switching in Percolating Molybdenum Nanoparticle Networks

Adrianus Julien Theodoor van der Ree, G. Palasantzas, Gert H. ten Brink, Majid Ahmadi et al.
7 citations
ACS Applied Materials & Interfaces
Advanced Memory and Neural Computing
1.46
article

Stable Millivolt Range Resistive Switching in Percolating Molybdenum Nanoparticle Networks

Adrianus Julien Theodoor van der Ree, G. Palasantzas, Gert H. ten Brink, Majid Ahmadi, Bart Jan Kooi
article en
7 citations

Abstract

To overcome the limitations of the conventional Von Neumann architecture, inspiration from the mammalian brain has led to the development of nanoscale neuromorphic networks. In the present research, molybdenum nanoparticles (NPs), which were produced by means of gas phase condensation based on magnetron sputtering, are shown to be the constituents of electrically percolating networks that exhibit stable, complex, neuron-like spiking behavior at low potentials in the millivolt range, satisfying well the requirement of low energy consumption. Characterization of the NPs using both scanning electron microscopy and scanning transmission electron microscopy revealed not only pristine shape, size, and density control of Mo NPs but also a preliminary proof of the working mechanism behind the spiking behavior due to filament formations. Furthermore, electrostatics COMSOL Multiphysics simulations of the morphology of the NPs provided evidence that the stable switching is due to the as-deposited stellate Mo NPs creating high electric field strengths, while keeping them separated, not seen before in other percolating networks based on spherical NPs. Hence, our results show the working mechanism behind switching in percolating Mo NP networks and show that they are very promising for realistic neuromorphic systems.

ACS Applied Materials & InterfacesVol. 16(47)
University of Groningen (NL)
Rijksuniversiteit Groningen, Zernike Institute for Advanced Materials, Rijksuniversiteit Groningen
Affordable and clean energy
Openalex Percentile: Top 17%
Advanced Memory and Neural Computing
1.46
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Stable Millivolt Range Resistive Switching in Percolating Molybdenum Nanoparticle Networks — Adrianus Julien Theodoor van der Ree, G. Palasantzas, et al. · ACS Applied Materials & Interfaces (2024) | TGRS Research Map | TGRS