ArticleNature communications2025
Wafer-scale fabrication of memristive passive crossbar circuits for brain-scale neuromorphic computing.
Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Wafer-scale SOT-MRAM for analog crossbar array applications.Science advances · 2026Article
- Neuromorphic Devices and Computing for Sensing, Memory, and Control.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 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
- Neuromorphic Technologies for Neuroengineering: From Adaptive Stimulation to SNN-Based Inference and Deployable Biointerfaces.Sensors (Basel, Switzerland) · 2026Review
- Compute-in-memory implementation of state space models for event sequence processing.Nature communications · 2026Article
- Kesterite-based optoelectronic synaptic memristors: a mini-review on material design and neuromorphic application.Science and technology of advanced materials · 2026Review
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Memristive passive crossbar circuits hold great promise for neuromorphic computing, offering high integration density combined with massively parallel operation. However, scaling up the integration complexity of such circuits remains challenging due to low device yield, stemming from the intrinsic properties of filamentary switching and limitations in current crossbar fabrication technologies. Here, we report a scalable passive crossbar device technology achieved through a co-design approach for memristors and crossbar structures. The proposed hardware platform is fabricated using CMOS-compatible processes without complex and high-temperature steps, enabling high device yield along with reliable and multibit operation. Importantly, the fabrication process is successfully scaled to a 4-inch wafer, maintaining an average device yield (>~95%) and preserving key switching characteristics. The potential of this platform is showcased by implementing image classification of the fashion MNIST benchmark with an ex-situ trained spiking neural network. We believe that our work represents a significant step toward brain-scale neuromorphic computing systems.
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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.