Complex electrical spiking activity in resistive switching nanostructured Au two-terminal devices

Engineering the structural and electrical interplay of nanostructured Au resistive switching networks by controlling the forming process

Networks of random-assembled gold clusters produced in the gas phase show resistive switching (RS) activity at room temperature and they are suitable for the fabrication of devices for neuromorphic data processing and classification. Fully connected cluster-assembled nanostructured Au films are characterized by a granular structure rich of interfaces, grain boundaries and crystalline defects. Here we report a systematic characterization of the electroforming process of the cluster-assembled films demonstrating how this process affects the interplay between the nano- and mesoscale film structure and the neuromorphic characteristics of the resistive switching activity. The understanding and the control of the influence of the resistive switching forming process on the organization of specific structures at different scales of the cluster-assembled films, provide the possibility to engineer random-assembled neuromorphic architectures for data processing task.

Solving classification tasks by a receptron based on nonlinear optical speckle fields

Among several approaches to tackle the problem of energy consumption in modern computing systems, two solutions are currently investigated: one consists of artificial neural networks (ANNs) based on photonic technologies, the other is a different paradigm compared to ANNs and it is based on random networks of non-linear nanoscale junctions resulting from the assembling of nanoparticles or nanowires as substrates for neuromorphic computing. These networks show the presence of emergent complexity and collective phenomena in analogy with biological neural networks characterized by self-organization, redundancy, and non-linearity. Starting from this background, we propose and formalize a generalization of the perceptron model to describe a classification device based on a network of interacting units where the input weights are non-linearly dependent. We show that this model, called "receptron", provides substantial advantages compared to the perceptron as, for example, the solution of non-linearly separable Boolean functions with a single device. The receptron model is used as a starting point for the implementation of an all-optical device that exploits the non-linearity of optical speckle fields produced by a solid scatterer. By encoding these speckle fields we generated a large variety of target Boolean functions. We demonstrate that by properly setting the model parameters, different classes of functions with different multiplicity can be solved efficiently. The optical implementation of the receptron scheme opens the way for the fabrication of a completely new class of optical devices for neuromorphic data processing based on a very simple hardware.

A novel method for the synthesis of core-shell nanoparticles for functional applications based on long-term confinement in a radio frequency plasma

A novel combined setup of a Haberland type gas aggregation source and a secondary radio frequency discharge is used to generate, confine, and coat nanoparticles over much longer time scales than traditional in-flight treatment. The process is precisely monitored using localized surface plasmon resonance and Fourier-transform infrared spectroscopy as in situ diagnostics. They indicate that both untreated and treated particles can be confined for extended time periods (at least one hour) with minimal losses. During the entire confinement time, the particle sizes do not show considerable alterations, enabling multiple well-defined modifications of the seed nanoparticles in this synthesis approach. The approach is demonstrated by generating Ag@SiO₂ nanoparticles with a well-defined surface coating. The in situ diagnostics provide insights into the growth kinetics of the applied coating and are linked to the coating properties by using ex situ transmission electron microscopy and energy dispersive X-ray spectroscopy. Surface coating is shown to occur in two phases: first, singular seeds appear on the particle surface which then grow to cover the entire particle surface over 3 to 5 minutes. Afterwards, deposition occurs via surface growth which coincides with lower deposition rates. Our setup offers full control for various treatment options, which is demonstrated by coating the nanoparticles with a SiO₂ layer followed by the etching of the part of the applied coating using hydrogen. Thus, complex multi-step nanofabrication, e.g., using different monomers, as well as very large coating thicknesses is possible.

Gas-phase synthesis of nanoparticles: current application challenges and instrumentation development responses

Nanoparticles constitute fundamental building blocks required in several fields of application with current global importance. To fully exploit nanoparticle properties specifically determined by the size, shape, chemical composition and interfacial configuration, rigorous nanoparticle growth and deposition control is needed. Gas-phase synthesis, in particular magnetron-sputtering inert-gas condensation, provides unique opportunities to realise engineered nanoparticles optimised for the desired use case. Here, we provide an overview of recent nanoparticle growth experiments via this technique, how the latter can meet application-specific requirements, and what challenges might impede the wide-spread adoption for scalable industrial synthesis. More specifically, we discuss the timely topics of energy, catalysis, and sensing applications enabled by gas-phase synthesised nanoparticles, as well as recently emerging advances in neuromorphic devices for unconventional computing. Having identified the most relevant challenges and limiting factors, we outline how advances in nanoparticle source instrumentation and/or in situ diagnostics can address current shortcomings. Eventually we identify common trends and directions, giving our perspective on the most promising and impactful applications of gas-phase synthesised nanoparticles in the future.

Brain-like critical dynamics and long-range temporal correlations in percolating networks of silver nanoparticles and functionality preservation after integration of insulating matrix

Random networks of nanoparticle-based memristive switches enable pathways for emulating highly complex and self-organized synaptic connectivity together with their emergent functional behavior known from biological neuronal networks. They therefore embody a distinct class of neuromorphic hardware architectures and provide an alternative to highly regular arrays of memristors. Especially, networks of memristive nanoparticles (NPs) poised at the percolation threshold are promising due to their capabilities of showing brain-like activity such as critical dynamics or long-range temporal correlation (LRTC), which are closely connected to the computational capabilities in biological neuronal networks. Here, we adapt this concept to networks of Ag-NPs poised at the electrical percolation threshold, where the memristive properties are governed by electro-chemical metallization. We show that critical dynamics and LRTC are preserved although the nature of individual memristive gaps throughout the network is fundamentally changed by filling the gaps with an insulating matrix. The results in this work generate important contributions towards the practical applicability of critical dynamics and LRTC in percolating NP networks by elucidating the consequences of NP network encapsulation, which is considered as an important step towards device integration.

Dynamical stochastic simulation of complex electrical behavior in neuromorphic networks of metallic nanojunctions

Nanostructured Au films fabricated by the assembling of nanoparticles produced in the gas phase have shown properties suitable for neuromorphic computing applications: they are characterized by a non-linear and non-local electrical behavior, featuring switches of the electric resistance whose activation is typically triggered by an applied voltage over a certain threshold. These systems can be considered as complex networks of metallic nanojunctions where thermal effects at the nanoscale cause the continuous rearrangement of regions with low and high electrical resistance. In order to gain a deeper understanding of the electrical properties of this nano granular system, we developed a model based on a large three dimensional regular resistor network with non-linear conduction mechanisms and stochastic updates of conductances. Remarkably, by increasing enough the number of nodes in the network, the features experimentally observed in the electrical conduction properties of nanostructured gold films are qualitatively reproduced in the dynamical behavior of the system. In the activated non-linear conduction regime, our model reproduces also the growing trend, as a function of the subsystem size, of quantities like Mutual and Integrated Information, which have been extracted from the experimental resistance series data via an information theoretic analysis. This indicates that nanostructured Au films (and our model) possess a certain degree of activated interconnection among different areas which, in principle, could be exploited for neuromorphic computing applications.

In-materio reservoir working at low frequencies in a Ag2S-island network

A Ag₂S-island network is fabricated with surrounding electrodes to enable it to be used as a reservoir for unconventional computing. Local conductance change occurs due to the growth/shrinkage of Ag filaments from/into each Ag₂S island in the reservoir. The growth/shrinkage of Ag filaments is caused by the drift of Ag⁺ cations in each Ag₂S island, which results in a unique non-linear response as a reservoir, especially at lower frequencies. The response of the reservoir is shown to depend on the frequency and amplitude of the input signals. So as to evaluate its capability as a reservoir, logical operations were performed using the subject Ag₂S-island network, with the results showing an accuracy of greater than 99%.

Molecular dynamics simulation of nanofilament breakage in neuromorphic nanoparticle networks

Neuromorphic computing systems may be the future of computing and cluster-based networks are a promising architecture for the realization of these systems. The creation and dissolution of synapses between the clusters are of great importance for their function. In this work, we model the thermal breakage of a gold nanofilament located between two gold nanoparticles via molecular dynamics simulations to study on the mechanisms of neuromorphic nanoparticle-based devices. We employ simulations of Au nanowires of different lengths (20-80 Å), widths (4-8 Å) and shapes connecting two Au₁₄₁₅nanoparticles (NPs) and monitor the evolution of the system via a detailed structural identification analysis. We found that atoms of the nanofilament gradually aggregate towards the clusters, causing the middle of wire to gradually thin and then break. Most of the system remains crystalline during this process but the center is molten. The terminal NPs increase the melting point of the NWs by fixing the middle wire and act as recrystallization areas. We report a strong dependence on the width of the NWs, but also their length and structure. These results may serve as guidelines for the realization of cluster-based neuromorphic computing systems.

Phase Transition to Heptagonal-Cluster-Packed Structure of Gold Nanoribbons

Transforming periodic crystals into packing of atomic clusters is attracting enormous interest for both fundamental research and potential application, but it still remains a big challenge for noble metals. Here, we have observed gold nanoribbons packed with heptagonal clusters, where every two or three constituent clusters connect edge-to-edge with their neighbors. This is the first reported metallic structure packed from building blocks with heptagonal symmetry. The cluster-packed nanoribbons transited from two-dimensional hexagonal structure under tensile condition and a reverse transition occurred by compression, resolved by in situ observation. The cluster-packed structure was stabilized by the s-d orbital hybridization. Theoretical calculations demonstrate that the conductance of the ribbons undergoes a quantized change from 6 to 4 G₀ (G₀ = 2e²/h) during the phase transition and backward for the reverse transition.

Energy-adaptive resistive switching with controllable thresholds in insulator–metal transition

Adaptive energy-scaling resistive switching with active response and self-regulation via controllable insulator–metal transition shows promise in energy-efficient devices.

Nanostructure Determines the Wettability of Gold Surfaces by Ionic Liquid Ultrathin Films

Ionic liquids are employed in energy storage/harvesting devices, in catalysis and biomedical technologies, due to their tunable bulk and interfacial properties. In particular, the wettability and the structuring of the ionic liquids at the interface are of paramount importance for all those applications exploiting ionic liquids tribological properties, their double layer organization at electrified interfaces, and interfacial chemical reactions. Here we report an experimental investigation of the wettability and organization at the interface of an imidazolium-based ionic liquid ([Bmim][NTf2]) and gold surfaces, that are widely used as electrodes in energy devices, electronics, fluidics. In particular, we investigated the role of the nanostructure on the resulting interfacial interactions between [Bmim][NTf2] and atom-assembled or cluster-assembled gold thin films. Our results highlight the presence of the solid-like structured ionic liquid domains extending several tens of nanometres far from the gold interfaces, and characterized by different lateral extension, according to the wettability of the gold nanostructures by the IL liquid-phase.

Anomalous electrical conduction and negative temperature coefficient of resistance in nanostructured gold resistive switching films

We report the observation of non-metallic electrical conduction, resistive switching, and a negative temperature coefficient of resistance in nanostructured gold films above the electrical percolation and in strong-coupling regime, from room down to cryogenic temperatures (24 K). Nanostructured continuous gold films are assembled by supersonic cluster beam deposition of Au aggregates formed in the gas phase. The structure of the cluster-assembled films is characterized by an extremely high density of randomly oriented crystalline nanodomains, separated by grain boundaries and with a large number of lattice defects. Our data indicates that space charge limited conduction and Coulomb blockade are at the origin of the anomalous electrical behavior. The high density of extended defects and grain boundaries causes the localization of conduction electrons over the entire investigated temperature range.