Grid-graph modeling of emergent neuromorphic dynamics and heterosynaptic plasticity in memristive nanonetworks

Self-assembled memristive nanonetworks composed of many interacting nano objects have been recently exploited for neuromorphic-type data processing and for the implementation of unconventional computing paradigms, such as reservoir computing. In these networks, information processing and computing tasks are performed by exploiting the emergent network behaviour without the need of fine tuning its components. Here, we propose grid-graph modelling of the emergent behaviour of memristive nanonetworks, where the memristive behaviour is decoupled from the particular and detailed behaviour of each network element. In this model, the memristive behavior of each edge is regulated by an analytical potentiation-depression rate balance equation deduced from physical arguments. By comparing modelling and experimental results obtained on nanonetworks based on Ag NWs, the model is shown to be able to emulate the main features of the emergent memristive behaviour and spatio-temporal dynamics of the nanonetwork, including short-term plasticity, paired-pulse facilitation and heterosynaptic plasticity. These results show that the model represents a versatile platform for exploring the implementation of unconventional computing paradigms in nanonetworks

Modeling of Short-Term Synaptic Plasticity Effects in ZnO Nanowire-Based Memristors Using a Potentiation-Depression Rate Balance Equation

This letter deals with short-term plasticity (STP) effects in the conduction characteristics of single crystalline ZnO nanowires, including potentiation, depression and relaxation phenomena. The electrical behavior of the structures is modeled following Chua's approach for memristive systems, i.e. one equation for the electron transport and one equation for the memory state of the device. Linear conduction is assumed in the first case together with a voltage-controlled rate balance equation for the normalized conductance. The devices are subject to electrical stimuli such as ramped and pulsed voltages of both polarities with varying amplitude and frequency. In each case, the proposed model is able to account for the STP effects exhibited by ZnO highlighting its neuromorphic capabilities for bio-inspired circuits. An equivalent circuit representation and the SPICE implementation of the compact model is also provided

In materia implementation strategies of physical reservoir computing with memristive nanonetworks

Physical reservoir computing (RC) represents a computational framework that exploits information-processing capabilities of programmable matter, allowing the realization of energy-efficient neuromorphic hardware with fast learning and low training cost. Despite self-organized memristive networks have been demonstrated as physical reservoir able to extract relevant features from spatiotemporal input signals, multiterminal nanonetworks open the possibility for novel strategies of computing implementation. In this work, we report on implementation strategies of in materia RC with self-assembled memristive networks. Besides showing the spatiotemporal information processing capabilities of self-organized nanowire networks, we show through simulations that the emergent collective dynamics allows unconventional implementations of RC where the same electrodes can be used as both reservoir inputs and outputs. By comparing different implementation strategies on a digit recognition task, simulations show that the unconventional implementation allows a reduction of the hardware complexity without limiting computing capabilities, thus providing new insights for taking full advantage of in materia computing toward a rational design of neuromorphic systems

Experimental and Modeling Study of Metal–Insulator Interfaces to Control the Electronic Transport in Single Nanowire Memristive Devices

Memristive devices relying on redox-based resistive switching mechanisms represent promising candidates for the development of novel computing paradigms beyond von Neumann architecture. Recent advancements in understanding physicochemical phenomena underlying resistive switching have shed new light on the importance of an appropriate selection of material properties required to optimize the performance of devices. However, despite great attention has been devoted to unveiling the role of doping concentration, impurity type, adsorbed moisture, and catalytic activity at the interfaces, specific studies concerning the effect of the counter electrode in regulating the electronic flow in memristive cells are scarce. In this work, the influence of the metal-insulator Schottky interfaces in electrochemical metallization memory (ECM) memristive cell model systems based on single-crystalline ZnO nanowires (NWs) is investigated following a combined experimental and modeling approach. By comparing and simulating the electrical characteristics of single NW devices with different contact configurations and by considering Ag and Pt electrodes as representative of electrochemically active and inert electrodes, respectively, we highlight the importance of an appropriate choice of electrode materials by taking into account the Schottky barrier height and interface chemistry at the metal-insulator interfaces. In particular, we show that a clever choice of metal-insulator interfaces allows to reshape the hysteretic conduction characteristics of the device and to increase the device performance by tuning its resistance window. These results obtained from single NW-based devices provide new insights into the selection criteria for materials and interfaces in connection with the design of advanced ECM cells

Recommended implementation of electrical resistance tomography for conductivity mapping of metallic nanowire networks using voltage excitation

open6noThe knowledge of the spatial distribution of the electrical conductivity of metallic nanowire networks (NWN) is important for tailoring the performance in applications. This work focuses on Electrical Resistance Tomography (ERT), a technique that maps the electrical conductivity of a sample from several resistance measurements performed on its border. We show that ERT can be successfully employed for NWN characterisation if a dedicated measurement protocol is employed. When applied to other materials, ERT measurements are typically performed with a constant current excitation; we show that, because of the peculiar microscopic structure and behaviour of metallic NWN, a constant voltage excitation protocols is preferable. This protocol maximises the signal to noise ratio in the resistance measurements-and thus the accuracy of ERT maps-while preventing the onset of sample alterations.openCultrera, Alessandro; Milano, Gianluca; De Leo, Natascia; Ricciardi, Carlo; Boarino, Luca; Callegaro, LucaCultrera, Alessandro; Milano, Gianluca; De Leo, Natascia; Ricciardi, Carlo; Boarino, Luca; Callegaro, Luc

Memristive Devices for Quantum Metrology

As a consequence of the redefinition of the International System of Units (SI), where units are defined in terms of fundamental physical constants, memristive devices represent a promising platform for quantum metrology. Coupling ionics with electronics, memristive devices can exhibit conductance levels quantized in multiples of the fundamental quantum of conductance G(0) = 2e(2)/h. Since the fundamental quantum of conductance G(0) is related only to physical constants that assume fixed value in the revised SI, memristive devices can be exploited for the practical realization of a quantum-based resistance standard that, differently from quantum-Hall based devices conventionally adopted as resistance standards, can operate in different ambient conditions (air, vacuum, harsh environment), in a wide range of temperatures and without the need of an applied magnetic field In this work, the possibility of using memristive devices for quantum metrology is critically discussed, based on recent experimental and theoretical advances on quantum conductance phenomena reported in literature. Thanks to the high operational speed, high scalability down to the nanometer scale, and CMOS compatibility, memristive devices allow on-chip implementation of a resistance standard required for the realization of self-calibrating electrical systems and equipment with zero-chain traceability in accordance with the revised SI

Effect of electrode materials on resistive switching behaviour of NbOx-based memristive devices

Memristive devices that rely on redox-based resistive switching mechanism have attracted great attention for the development of next-generation memory and computing architectures. However, a detailed understanding of the relationship between involved materials, interfaces, and device functionalities still represents a challenge. In this work, we analyse the effect of electrode metals on resistive switching functionalities of NbOx-based memristive cells. For this purpose, the effect of Au, Pt, Ir, TiN, and Nb top electrodes was investigated in devices based on amorphous NbOx grown by anodic oxidation on a Nb substrate exploited also as counter electrode. It is shown that the choice of the metal electrode regulates electronic transport properties of metal–insulator interfaces, strongly influences the electroforming process, and the following resistive switching characteristics. Results show that the electronic blocking character of Schottky interfaces provided by Au and Pt metal electrodes results in better resistive switching performances. It is shown that Pt represents the best choice for the realization of memristive cells when the NbOx thickness is reduced, making possible the realization of memristive cells characterised by low variability in operating voltages, resistance states and with low device-to-device variability. These results can provide new insights towards a rational design of redox-based memristive cells

Mapping Time-Dependent Conductivity of Metallic Nanowire Networks by Electrical Resistance Tomography toward Transparent Conductive Materials

partially_open7Metallic nanowire (NW) networks have attracted great attention as promising transparent conductive materials thanks to the low sheet resistance, high transparency, low cost production, and compatibility with flexible substrates. Despite many efforts having been devoted to investigating the conduction mechanism, a quantitative characterization of local electrical properties of nanowire networks at the macroscale still represents a challenge. In this work, we report on the investigation of local electrical properties and their evolution over time of Ag NW networks by means of electrical resistance tomography (ERT). Spatial correlation of local conductivity properties and optical transparency revealed that the nonscanning and rapid ERT technique allows to probe local electrical inhomogeneities in the NW network, differently from conventional measurement techniques such as van der Pauw and the four-point probe. In addition, ERT mapping over time was employed for in situ monitoring the evolution of Ag NW networks conductivity, elucidating the dependence of the degradation of local electrical properties under ambient exposure on the initial conductivity. Our results shed light on the importance of the characterization of local electrical properties of NW networks where uniformity and stability represent the main challenges to overcome for their use as transparent conductive materials.openGianluca Milano; Alessandro Cultrera; Katarzyna Bejtka; Natascia De Leo; Luca Callegaro; Carlo Ricciardi; Luca BoarinoMilano, Gianluca; Cultrera, Alessandro; Bejtka, Katarzyna; DE LEO, Maria; Callegaro, Luca; Ricciardi, Carlo; Boarino, Luc