ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2024
Formation of Cluster-Structured Metallic Filaments in Organic Memristors for Wearable Neuromorphic Systems with Bio-Mimetic Synaptic Weight Distributions.
Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Grain Boundary Enabled Diamond Memristor.Advanced materials (Deerfield Beach, Fla.) · 2026Article
- Flexible Neuromorphic Memristors: From Mechanisms to Applications.Materials (Basel, Switzerland) · 2026Review
- Weaving Intelligence: Thermally Drawn Multimaterial Fibers Toward AI-Enabled Smart Textiles.Advanced materials (Deerfield Beach, Fla.) · 2026Review
- Wearable Multifunctional Sensors for Human Activity Recognition.Sensors (Basel, Switzerland) · 2026Review
- Multisensory Neuromorphic Devices: From Physics to Integration.Nano-micro letters · 2026Review
- Multimodal In-Sensor Computing with Dual-Phase Organic Synapses for Wearable Fitness Monitoring.Advanced materials (Deerfield Beach, Fla.) · 2026Article
- Liquid Resistive Switching Devices with Printable Electrodes.Micromachines · 2025Article
- Flexible Synaptic Memristors With Controlled Rigidity in Zirconium-Oxo Clusters for High-Precision Neuromorphic Computing.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Space-Confined Growth of Ultrathin 2D β-GaSmall science · 2024Article
- Stochastic switching and analog-state programmable memristor and its utilization for homomorphic encryption hardware.Nature communications · 2024Article
- Formation of Cluster-Structured Metallic Filaments in Organic Memristors for Wearable Neuromorphic Systems with Bio-Mimetic Synaptic Weight Distributions.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
With increasing demand for wearable electronics capable of computing huge data, flexible neuromorphic systems mimicking brain functions have been receiving much attention. Despite considerable efforts in developing practical neural networks utilizing several types of flexible artificial synapses, it is still challenging to develop wearable systems for complex computations due to the difficulties in emulating continuous memory states in a synaptic component. In this study, polymer conductivity is analyzed as a crucial factor in determining the growth dynamics of metallic filaments in organic memristors. Moreover, flexible memristors with bio-mimetic synaptic functions such as linearly tunable weights are demonstrated by engineering the polymer conductivity. In the organic memristor, the cluster-structured filaments are grown within the polymer medium in response to electric stimuli, resulting in gradual resistive switching and stable synaptic plasticity. Additionally, the device exhibits the continuous and numerous non-volatile memory states due to its low leakage current. Furthermore, complex hardware neural networks including ternary logic operators and a noisy image recognitions system are successfully implemented utilizing the developed memristor arrays. This promising concept of creating flexible neural networks with bio-mimetic weight distributions will contribute to the development of a new computing architecture for energy-efficient wearable smart electronics.
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