ArticleNature communications2024
Purely self-rectifying memristor-based passive crossbar array for artificial neural network accelerators.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
24 citing papers in PubMed.
- From Device-Level Implementation to In-Sensor Computing in Memristive-Device-Based Biosensors: A Review.Biosensors · 2026Review
- 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
- Integration of Reconfigurable p-Bit and 1R Crossbar Array for Memristive Probabilistic Computing.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Two-terminal β-GaLight, science & applications · 2026Article
- Ultra-high density perovskite nanowire array memristor-based multi-layer perceptron.Nature communications · 2026Article
- HfOScience advances · 2026Article
- Vertical Self-Rectifying Memristive Arrays for Page-Wise Parallel Logic and Arithmetic Processing.Advanced materials (Deerfield Beach, Fla.) · 2026Article
- Self-Rectifying Memristors for Beyond-CMOS Computing: Mechanisms, Materials, and Integration Prospects.Nano-micro letters · 2026Review
- Demonstration of CMOS-compatible memristor-based electrochemical biosensor transducer with threshold-sensing functionality.Nature communications · 2025Article
- Device-level nonlinearity and temporal memory in optoelectronic reservoir computing.Nano convergence · 2025Review
- Computational magnetic metasurfaces in the low radiofrequency regime.Scientific reports · 2025Article
- Large-scale crossbar arrays based on three-terminal MoSNature communications · 2025Article
- Wafer-scale fabrication of memristive passive crossbar circuits for brain-scale neuromorphic computing.Nature communications · 2025Article
- Multifunctional Chiral Halide Perovskites: Advancing Chiro-Optics, Chiro-Optoelectronics, and Spintronics.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Review
- Real-time signal processing enabled by fused networks on a memristor-based system on a chip.Science advances · 2025Article
- Self-rectifying memristors with high rectification ratio for attack-resilient autonomous driving systems.Nature communications · 2025Article
- Electric Field-Driven Conformational Changes in Molecular Memristor and Synaptic Behavior.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- SynthSoM: A synthetic intelligent multi-modal sensing-communication dataset for Synesthesia of Machines (SoM).Scientific data · 2025Article
- Flexible self-rectifying synapse array for energy-efficient edge multiplication in electrocardiogram diagnosis.Nature communications · 2025Article
- A Fully Integrated Memristive Chaotic Circuit Based on Memristor Emulator with Voltage-Controlled Oscillator.Micromachines · 2025Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
Memristor-integrated passive crossbar arrays (CAs) could potentially accelerate neural network (NN) computations, but studies on these devices are limited to software-based simulations owing to their poor reliability. Herein, we propose a self-rectifying memristor-based 1 kb CA as a hardware accelerator for NN computations. We conducted fully hardware-based single-layer NN classification tasks involving the Modified National Institute of Standards and Technology database using the developed passive CA, and achieved 100% classification accuracy for 1500 test sets. We also investigated the influences of the defect-tolerance capability of the CA, impact of the conductance range of the integrated memristors, and presence or absence of selection functionality in the integrated memristors on the image classification tasks. We offer valuable insights into the behavior and performance of CA devices under various conditions and provide evidence of the practicality of memristor-integrated passive CAs as hardware accelerators for NN applications.
Identifiers
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Registered trials
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.