Themed collection Memristors and Neuromorphic Systems

27 items
Editorial

Introduction to memristors and neuromorphic systems

Xiaodong Chen, Cheol Seong Hwang, Yoeri van de Burgt and Francesca Santoro present a themed collection in Materials Horizons and Nanoscale Horizons gathering the latest developments in memristive materials, device fabrication, characterization and circuit design for neuromorphic systems.

Graphical abstract: Introduction to memristors and neuromorphic systems
From the themed collection: Memristors and Neuromorphic Systems
Opinion

Oxovanadium electronics for in-memory, neuromorphic, and quantum computing applications

Redox- and spin-active macrocyclic vanadyl(IV) complexes and polyoxovanadates(V) have promising structural and physicochemical characteristics for innovative bottom-up hybrid electronics.

Graphical abstract: Oxovanadium electronics for in-memory, neuromorphic, and quantum computing applications
From the themed collection: Memristors and Neuromorphic Systems
Review Article

Emerging ferroelectric materials ScAlN: applications and prospects in memristors

The research found that after doping with rare earth elements, a large number of electrons and holes will be produced on the surface of AlN, which makes the material have the characteristics of spontaneous polarization.

Graphical abstract: Emerging ferroelectric materials ScAlN: applications and prospects in memristors
From the themed collection: Recent Review Articles
Open Access Review Article

Growth of emergent simple pseudo-binary ferroelectrics and their potential in neuromorphic computing devices

Ferroelectric memory devices such as ferroelectric memristors, ferroelectric tunnel junctions, and field-effect transistors are considered among the most promising candidates for neuromorphic computing devices.

Graphical abstract: Growth of emergent simple pseudo-binary ferroelectrics and their potential in neuromorphic computing devices
From the themed collection: Memristors and Neuromorphic Systems
Review Article

Emerging memristive artificial neuron and synapse devices for the neuromorphic electronics era

A review and universal benchmark for assessing the artificial neuron and synapse device performance from an energy perspective, with the introduction of neuromorphics from biological to electronics and their prospects.

Graphical abstract: Emerging memristive artificial neuron and synapse devices for the neuromorphic electronics era
From the themed collection: Memristors and Neuromorphic Systems
Communication

Origin of discrete resistive switching in chemically heterogeneous vanadium oxide crystals

Vacancy-induced filament formation and rupturing across Magnéli phases of VO2. The resistive switching shows the variations in threshold voltage with discreteness as a function of number of cycles.

Graphical abstract: Origin of discrete resistive switching in chemically heterogeneous vanadium oxide crystals
From the themed collection: Memristors and Neuromorphic Systems
Open Access Communication

An organic brain-inspired platform with neurotransmitter closed-loop control, actuation and reinforcement learning

Organic neuromorphic platforms have recently received growing interest for the implementation and integration of hybrid systems, acting as a bridge between biological tissue and artificial computing architectures.

Graphical abstract: An organic brain-inspired platform with neurotransmitter closed-loop control, actuation and reinforcement learning
From the themed collection: Memristors and Neuromorphic Systems
Open Access Communication

High-performance one-dimensional halide perovskite crossbar memristors and synapses for neuromorphic computing

Pyridinium-templated one-dimensional (1D) halide perovskites are studied as crossbar memristive materials for artificial neural networks with higher on–off ratios, enhanced endurance, and superior retention characteristics.

Graphical abstract: High-performance one-dimensional halide perovskite crossbar memristors and synapses for neuromorphic computing
From the themed collection: Memristors and Neuromorphic Systems
Open Access Communication

Oxygen tracer diffusion in amorphous hafnia films for resistive memory

We quantified the oxygen tracer diffusion in amorphous hafnium oxide thin films. These tracer diffusion values are consistent with the experimentally measured retention times of hafnium oxide resistive memory devices.

Graphical abstract: Oxygen tracer diffusion in amorphous hafnia films for resistive memory
From the themed collection: Memristors and Neuromorphic Systems
Open Access Communication

Memory effect and coexistence of negative and positive photoconductivity in black phosphorus field effect transistor for neuromorphic vision sensors

Black phosphorus (BP) field-effect transistors with ultrathin channels exhibit unipolar p-type electrical conduction over a wide range of temperatures and pressures.

Graphical abstract: Memory effect and coexistence of negative and positive photoconductivity in black phosphorus field effect transistor for neuromorphic vision sensors
From the themed collection: Memristors and Neuromorphic Systems
Communication

Ovonic threshold switching-based artificial afferent neurons for thermal in-sensor computing

This research demonstrates an OTS-based temperature-sensing afferent neuron that features low power consumption and a compact circuit structure.

Graphical abstract: Ovonic threshold switching-based artificial afferent neurons for thermal in-sensor computing
From the themed collection: Memristors and Neuromorphic Systems
Communication

Experimental demonstration of combination-encoding content-addressable memory of 0.75 bits per switch utilizing Hf–Zr–O ferroelectric tunnel junctions

We have fabricated 4-CECAM (with keys encoded into 8-long binary arrays and 8 FTJs) with a content density of 0.75 bits per switch, which highlights 50% increase in content density compared to that of the conventional TCAM (0.5 bits per switch).

Graphical abstract: Experimental demonstration of combination-encoding content-addressable memory of 0.75 bits per switch utilizing Hf–Zr–O ferroelectric tunnel junctions
From the themed collection: Memristors and Neuromorphic Systems
Open Access Communication

Analytical modelling of the transport in analog filamentary conductive-metal-oxide/HfOx ReRAM devices

The recent co-optimization of memristive technologies and programming algorithms enabled neural networks training with in-memory computing systems.

Graphical abstract: Analytical modelling of the transport in analog filamentary conductive-metal-oxide/HfOx ReRAM devices
From the themed collection: Memristors and Neuromorphic Systems
Open Access Communication

Reliability effects of lateral filament confinement by nano-scaling the oxide in memristive devices

We fabricate a nano-device that laterally confines the switching oxide and filament to 10 nm. Electrical measurements demonstrate lower variability and reduced ionic noise compared to unconfined filaments, which is supported by our 3D simulation.

Graphical abstract: Reliability effects of lateral filament confinement by nano-scaling the oxide in memristive devices
From the themed collection: Memristors and Neuromorphic Systems
Communication

Physical reservoirs based on MoS2–HZO integrated ferroelectric field-effect transistors for reservoir computing systems

This work demonstrated a high-performance ferroelectric field-effect transistor (FeFET) via the integration of HZO and 2D MoS2, showing efficacy in processing diverse real-life tasks within a reservoir computing system.

Graphical abstract: Physical reservoirs based on MoS2–HZO integrated ferroelectric field-effect transistors for reservoir computing systems
From the themed collection: Memristors and Neuromorphic Systems
Communication

Multicolor vision perception of flexible optoelectronic synapse with high sensitivity for skin sunburn warning

We propose a self-powered flexible optoelectronic synapse based on PEA2SnI4 films for multicolor vision perception and skin sunburn warning.

Graphical abstract: Multicolor vision perception of flexible optoelectronic synapse with high sensitivity for skin sunburn warning
From the themed collection: Memristors and Neuromorphic Systems
Open Access Communication

Fully printed memristors made with MoS2 and graphene water-based inks

Fully printed memristors based on silver and water-based 2D material inks were demonstrated on rigid and flexible substrates. The Ag filaments formation depends on the annealing process and can be inhibited by integrating CVD graphene in the device.

Graphical abstract: Fully printed memristors made with MoS2 and graphene water-based inks
From the themed collection: Memristors and Neuromorphic Systems
Communication

Insights into synaptic functionality and resistive switching in lead iodide flexible memristor devices

Neuromorphic platforms are gaining popularity due to their superior efficiency, low power consumption, and adaptable parallel signal processing capabilities, overcoming the limitations of traditional von Neumann architecture.

Graphical abstract: Insights into synaptic functionality and resistive switching in lead iodide flexible memristor devices
From the themed collection: Memristors and Neuromorphic Systems
Open Access Communication

Electrochemical rewiring through quantum conductance effects in single metallic memristive nanowires

In this work, Milano et al. reported on quantum conductance effects in memristive nanowires, unveiling the origin of deviations of conductance levels from integer multiples of the conductance quantum and analyzing conductance fluctuations over time of memristive devices.

Graphical abstract: Electrochemical rewiring through quantum conductance effects in single metallic memristive nanowires
From the themed collection: Memristors and Neuromorphic Systems
Communication

Heterogeneous reservoir computing in second-order Ta2O5/HfO2 memristors

The mixture of leaky and self-rectifying memristors in the reservoir increases the accuracy in MNIST-digits recognition task.

Graphical abstract: Heterogeneous reservoir computing in second-order Ta2O5/HfO2 memristors
From the themed collection: Memristors and Neuromorphic Systems
Communication

Stretchable and neuromorphic transistors for pain perception and sensitization emulation

A fully stretchable artificial pain perception nociceptor is prepared. The device is stretched in various ways with stable synaptic and nociceptor simulation performance. This work contributes to the development of flexible sensor devices.

Graphical abstract: Stretchable and neuromorphic transistors for pain perception and sensitization emulation
From the themed collection: Memristors and Neuromorphic Systems
Open Access Communication

3D simulation of conductive nanofilaments in multilayer h-BN memristors via a circuit breaker approach

A 3D simulation of conductive nanofilaments (CNFs) in multilayer hexagonal-BN memristors is performed.

Graphical abstract: 3D simulation of conductive nanofilaments in multilayer h-BN memristors via a circuit breaker approach
From the themed collection: Memristors and Neuromorphic Systems
Communication

An in-sensor humidity computing system for contactless human–computer interaction

Respiratory detection and contactless human–computer interaction capacity is achieved by a humidity-sensitive memristor.

Graphical abstract: An in-sensor humidity computing system for contactless human–computer interaction
From the themed collection: Memristors and Neuromorphic Systems
Communication

Neuromorphic devices realised using self-forming hierarchical Al and Ag nanostructures: towards energy-efficient and wide ranging synaptic plasticity

Self-formed hierarchical structures of Al and Ag closely mimicking the biological neural network offer wide range synaptic plasticity with ultra-low energy usage. Al islands can be exploited as contact pads to introduce multiple sensory signals.

Graphical abstract: Neuromorphic devices realised using self-forming hierarchical Al and Ag nanostructures: towards energy-efficient and wide ranging synaptic plasticity
From the themed collection: Memristors and Neuromorphic Systems
Communication

Adapted MLP-Mixer network based on crossbar arrays of fast and multilevel switching (Co–Fe–B)x(LiNbO3)100−x nanocomposite memristors

MLP-Mixer neuromorphic network based on nanocomposite memristive synapses has been developed for efficient and robust classification of images.

Graphical abstract: Adapted MLP-Mixer network based on crossbar arrays of fast and multilevel switching (Co–Fe–B)x(LiNbO3)100−x nanocomposite memristors
From the themed collection: Memristors and Neuromorphic Systems
Communication

Multistate switching of scanning tunnelling microscopy machined polyoxovanadate–dysprosium–phthalocyanine nanopatterns on graphite

We demonstrate the formation of stable monolayers of polyoxometalates on a graphite substrate, which can be electronically multi-level switched and nanostructured without physical contact by the electric field of a scanning tunnelling microscope tip.

Graphical abstract: Multistate switching of scanning tunnelling microscopy machined polyoxovanadate–dysprosium–phthalocyanine nanopatterns on graphite
From the themed collection: Memristors and Neuromorphic Systems
Communication

A high-dimensional in-sensor reservoir computing system with optoelectronic memristors for high-performance neuromorphic machine vision

A high-dimensional in-sensor reservoir computing system with optoelectronic memristors is demonstrated utilizing optical and electrical masks. Handwritten digit classification and human action recognition are successfully achieved with high accuracy.

Graphical abstract: A high-dimensional in-sensor reservoir computing system with optoelectronic memristors for high-performance neuromorphic machine vision
From the themed collection: Memristors and Neuromorphic Systems
27 items

About this collection

In late 2022, ChatGPT was launched with global impact across many different fields and society. However, similar to other artificial intelligence (AI) algorithms it has a substantional downside: consuming a lot of energy. ChatGPT requires almost ten times more energy cost than a conventional search algorithm, such as Google, as the large language model used in this new algorithm is built on a massive neural network, where the number of parameters to be optimized is overwhelming (several hundreds of billions). These models fundamentally belong to machine learning algorithms, where backpropagation-based deep learning produces remarkable performances. However, these methods are entirely disparate from human brain operation, which operates in a massively parallel and spike-based fashion and vastly outperforms computing algorithms in some classification tasks at much lower energy cost.

The research field dedicated to mimicking the brain is called neuromorphic engineering, and covers a wide range of disciplines, including electrical engineering, computing, materials science, chemistry, physics, and even psychology. Yet, conventional CMOS-based hardwares are based on the von-Neumann architecture which operates sequentially (instead of in parallel) suffling data back and forth between processing and memory, and thus barely fulfil the low-energy requirements for neuromorphic engineering. Memristors, which can be synaptic, neural, or even a combination of both, offer a potential solution and as such have been the focus of enhanced research efforts. In addition to their low-energy cost requirements, new materials properties employed by memristors may lead to new algorithms or help solve conventionally challenging tasks, such as NP-hard problems.

This themed collection in Materials Horizons and Nanoscale Horizons guest edited by Prof. Xiaodong Chen (Nanyang Technological University, Singapore), Prof. Cheol Seong Hwang (Seoul National University, Korea), Prof. Francesca Santoro (Forschungszentrum Jülich, Germany) and Prof. Yoeri Van de Burgt (Eindhoven University of Technology, The Netherlands) aims to report the latest developments in memristive materials. Exploring their fabrication, characterization, circuit design, and performance for applications in the future of neuromorphics.

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