ArticleNature communications2022
Experimental demonstration of highly reliable dynamic memristor for artificial neuron and neuromorphic computing.
Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 65 papers.
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Who cites it
65 citing papers in PubMed.
- Controlling Ion Dynamics at Nanoscale for Memristor-Based Neuromorphic Computing.Small (Weinheim an der Bergstrasse, Germany) · 2026Article
- Analysis and Applications of Neuromorphic Memristors in Artificial Intelligence Computing.Nano-micro letters · 2026Review
- From Device-Level Implementation to In-Sensor Computing in Memristive-Device-Based Biosensors: A Review.Biosensors · 2026Review
- Damage-free van der Waals metal/NbONano convergence · 2026Article
- Perception, Synaptic Plasticity, and Spiking Neuron Function Enabled by a 2D Ferroelectric NbOBrAdvanced materials (Deerfield Beach, Fla.) · 2026Article
- Tunable Dynamics via Dual-Ion Modulation for Event-based Data Processing Using a Highly Uniform and Self-Rectifying Memristor Array.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Reconfigurable ferroelectric transistor array for embodied neuromorphic vision with hardware-native sensing, computing, and activation.Science advances · 2026Article
- Anisotropic Memristive Switching in NbOClAdvanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Realization of the Bienenstock-Cooper-Munro rule in a single memristor.Nature communications · 2026Article
- Programmable memtransistor array with temporal dynamics modulation for efficient time-series data processing.Nature communications · 2026Article
- Gradient-distributed metal-halide dynamic memristors for adaptive and robust voiceprint recognition.Nature communications · 2026Article
- Deep learning-enabled versatile shape perception for soft robots via single-ended multimode fiber.Science advances · 2026Article
- Memristive Physical Reservoir Computing.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Volatile self-selective memristive neuron for millisecond-latency neuromorphic object detection at the edge.Nature communications · 2026Article
- Neuromorphic Near-Sensor and In-Sensor Computing Enabled by Next-Generation Material-Based Sensors.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Programmable Speech Recognition Based on Cu/CuBiSeACS omega · 2026Article
- Heterosynaptic Memtransistors Based on Switching Operation Mechanism Using Designed Organic/Inorganic Heterostructures for Neuromorphic Electronics.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Al Nanoparticle-Decorated Metal Oxide Synaptic Transistors for Ultralow-Energy Neuromorphic Computing with Wide Dynamic Range.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- An Analogue Memristor Based on Conjugated Porous Polymer Composite for Artificial Synapse.Exploration (Beijing, China) · 2026Article
- A reconfigurable photosensitive split-floating-gate memory for neuromorphic computing and nonlinear activation.Nature communications · 2026Article
5 more citing papers are in PubMed but not listed here.
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Neuromorphic computing, a computing paradigm inspired by the human brain, enables energy-efficient and fast artificial neural networks. To process information, neuromorphic computing directly mimics the operation of biological neurons in a human brain. To effectively imitate biological neurons with electrical devices, memristor-based artificial neurons attract attention because of their simple structure, energy efficiency, and excellent scalability. However, memristor's non-reliability issues have been one of the main obstacles for the development of memristor-based artificial neurons and neuromorphic computings. Here, we show a memristor 1R cross-bar array without transistor devices for individual memristor access with low variation, 100% yield, large dynamic range, and fast speed for artificial neuron and neuromorphic computing. Based on the developed memristor, we experimentally demonstrate a memristor-based neuron with leaky-integrate and fire property with excellent reliability. Furthermore, we develop a neuro-memristive computing system based on the short-term memory effect of the developed memristor for efficient processing of sequential data. Our neuro-memristive computing system successfully trains and generates bio-medical sequential data (antimicrobial peptides) while using a small number of training parameters. Our results open up the possibility of memristor-based artificial neurons and neuromorphic computing systems, which are essential for energy-efficient edge computing devices.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.