ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2023
Memcapacitor Crossbar Array with Charge Trap NAND Flash Structure for Neuromorphic Computing.
Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- A Dual-Programmable 2M NOR Flash Architecture for Energy-Efficient In-Memory Computing.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Capacitive in-memory vector-matrix multiplication computing with charge-trap memcapacitors.Nano convergence · 2026Article
- Recent advances in ferroelectric materials, devices, and in-memory computing applications.Nano convergence · 2025Review
- Large-scale crossbar arrays based on three-terminal MoSNature communications · 2025Article
- Wordline Input Bias Scheme for Neural Network Implementation in 3D-NAND Flash.Biomimetics (Basel, Switzerland) · 2025Article
- From light sensing to adaptive learning: hafnium diselenide reconfigurable memcapacitive devices in neuromorphic computing.Light, science & applications · 2025Article
- Neuron Circuit Based on a Split-gate Transistor with Nonvolatile Memory for Homeostatic Functions of Biological Neurons.Biomimetics (Basel, Switzerland) · 2024Article
- A comprehensive review of advanced trends: from artificial synapses to neuromorphic systems with consideration of non-ideal effects.Frontiers in neuroscience · 2024Review
- Memcapacitor Crossbar Array with Charge Trap NAND Flash Structure for Neuromorphic Computing.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The progress of artificial intelligence and the development of large-scale neural networks have significantly increased computational costs and energy consumption. To address these challenges, researchers are exploring low-power neural network implementation approaches and neuromorphic computing systems are being highlighted as potential candidates. Specifically, the development of high-density and reliable synaptic devices, which are the key elements of neuromorphic systems, is of particular interest. In this study, an 8 × 16 memcapacitor crossbar array that combines the technological maturity of flash cells with the advantages of NAND flash array structure is presented. The analog properties of the array with high reliability are experimentally demonstrated, and vector-matrix multiplication with extremely low error is successfully performed. Additionally, with the capability of weight fine-tuning characteristics, a spiking neural network for CIFAR-10 classification via off-chip learning at the wafer level is implemented. These experimental results demonstrate a high level of accuracy of 92.11%, with less than a 1.13% difference compared to software-based neural networks (93.24%).
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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.