ArticleScience advances2022
CMOS-compatible compute-in-memory accelerators based on integrated ferroelectric synaptic arrays for convolution neural networks.
Article in Science advances, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
27 citing papers in PubMed.
- Ferroelectric Transistors: from Materials Innovation to Intelligent Electronic Systems.Advanced materials (Deerfield Beach, Fla.) · 2026Review
- Sub-Nanometer Ferroelectric Tunnel Junctions With Record-High on-Current Density Through Synergistic Microwave Annealing and High-Field Activation.Small (Weinheim an der Bergstrasse, Germany) · 2026Article
- Hybrid ferroelectric-ionic memristive hardware for high scalability in-memory computing.Nature communications · 2026Article
- Temporal-Spatial Fusion Vision Hardware Enables Streamlined In-Sensor Computing for Dynamic Scenes.Nature communications · 2026Article
- Optoelectronic-Driven van der Waals Ferroelectric Materials-Based Memory Devices for Retinomorphic and In-Sensory Hardware.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Oxygen-controlled IGZO channel deposition for enhanced memory window in ferroelectric FETs.Scientific reports · 2026Article
- Tunable Switching Mechanisms in HfZrOAdvanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Intelligent Photodetectors: Postmanufacturing Tunability toward Enhanced Performance and Advanced Functions.Chemical reviews · 2025Review
- Electrically programmable organic in-display neuromorphic computing.National science review · 2025Article
- Domain engineering in ferroelectric nematics for nonlinear optical modulation.Science advances · 2025Article
- High-Performance Synapse Arrays for Neuromorphic Computing via Floating Gate-Engineered IGZO Synaptic Transistors.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Memristive Bellman solver for decision-making.Nature communications · 2025Article
- 8-bit states in 2D floating-gate memories using gate-injection mode for large-scale convolutional neural networks.Nature communications · 2025Article
- Low-power edge detection based on ferroelectric field-effect transistor.Nature communications · 2025Article
- Scalable Synaptic Transistor Memory from Solution-Processed Carbon Nanotubes for High-Speed Neuromorphic Data Processing.Advanced materials (Deerfield Beach, Fla.) · 2025Article
- Two-Dimensional MoSAdvanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- Two-dimensional fully ferroelectric-gated hybrid computing-in-memory hardware for high-precision and energy-efficient dynamic tracking.Science advances · 2024Article
- Ferroelectric materials for neuroinspired computing applications.Fundamental research · 2024Review
- Unlocking large memory windows and 16-level data per cell memory operations in hafnia-based ferroelectric transistors.Science advances · 2024Article
- Ultrathin All-Solid-State MoSAdvanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Convolutional neural networks (CNNs) have gained much attention because they can provide superior complex image recognition through convolution operations. Convolution processes require repeated multiplication and accumulation operations, which are difficult tasks for conventional computing systems. Compute-in-memory (CIM) that uses parallel data processing is an ideal device structure for convolution operations. CIM based on two-terminal synaptic devices with a crossbar structure has been developed, but unwanted leakage current paths and the high-power consumption remain as the challenges. Here, we demonstrate integrated ferroelectric thin-film transistor (FeTFT) synaptic arrays that can provide efficient parallel programming and data processing for CNNs by the selective and accurate control of polarization in the ferroelectric layer. In addition, three-terminal FeTFTs can act as both nonvolatile memory and access device, which tackle issues from two-terminal devices. An integrated FeTFT synaptic array with parallel programming capabilities can perform convolution operations to extract image features with a high-recognition accuracy.
Identifiers
What OpenQuestion holds
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.