ArticleScience advances2024
Two-dimensional fully ferroelectric-gated hybrid computing-in-memory hardware for high-precision and energy-efficient dynamic tracking.
Article in Science advances, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Ferroelectric Transistors: from Materials Innovation to Intelligent Electronic Systems.Advanced materials (Deerfield Beach, Fla.) · 2026Review
- Reconfigurable ferroelectric transistor array for embodied neuromorphic vision with hardware-native sensing, computing, and activation.Science advances · 2026Article
- Amphibian-inspired neuromorphic dynamic vision systems based on ferroelectric field-effect transistor.Nature communications · 2026Article
- Towards Artificial Intelligence Hardware With 3D Integrated Ferroelectric Transistors.Small (Weinheim an der Bergstrasse, Germany) · 2026Article
- Reconfigurable skin electronics enabled by intrinsically stretchable photoelectric memory transistors.Nature communications · 2026Article
- Electroluminescent perovskite QD-based neural networks for energy-efficient and accelerate multitasking learning.Science advances · 2026Article
- Owl-vision-inspired near sensor computing.Nature communications · 2026Article
- Homogeneous integration of two-dimensional material-based optoelectronic neurons and ferroelectric synapses for neuromorphic vision.Nature communications · 2026Article
- Integration of Freestanding High-k Oxide Membranes for 2D Ferroelectric Field-Effect Transistors.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Coplanar Floating-Gate Antiferroelectric Transistor with Multifunctionality for All-in-One Analog Reservoir Computing.Nano-micro letters · 2026Article
- Synaptic Plasticity Engineering for Neural Precision, Temporal Learning, and Scalable Neuromorphic Systems.Nano-micro letters · 2026Review
- In-memory ferroelectric differentiator.Nature communications · 2025Article
Corrections and comments
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Authors and funding
16 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Computing in memory (CIM) breaks the conventional von Neumann bottleneck through in situ processing. Monolithic integration of digital and analog CIM hardware, ensuring both high precision and energy efficiency, provides a sustainable paradigm for increasingly sophisticated artificial intelligence (AI) applications but remains challenging. Here, we propose a complementary metal-oxide semiconductor-compatible ferroelectric hybrid CIM platform that consists of Boolean logic and triggers for digital processing and multistage cell arrays for analog computation. The basic ferroelectric-gated units are assembled with solution-processable two-dimensional (2D) molybdenum disulfide atomic-thin channels at a wafer-scale yield of 96.36%, delivering high on/off ratios (>10
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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.