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Adaptive ferroelectric memristors with high-throughput BaTiO3 thin films for neuromorphic computing
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DOI：10.1039/D5MH00526D.png)
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Abstract
En 中文
Ferroelectric tunnel junctions (FTJs) and ferroelectric diodes (FDs) have been considered as promising artificial synaptic devices for constructing brain-inspired neuromorphic computing systems. However; their functionalities and applications are limited due to their strong dependence on the ferroelectric layer thickness and the thickness optimization is labour-intensive and time-consuming. Here; we demonstrate high-performance electronic synapses based on a high-throughput ferroelectric BaTiO3 (BTO) thin film. Two-terminal ferroelectric memristors are fabricated on a thickness-gradient BTO film with thickness ranging from 1 to 30 unit cells (UC); and intrinsic ferroelectricity is revealed in regions with thickness >5 UC. Notably; three typical resistive switching behaviors of resistor; FTJ; and FD occur sequentially with increasing BTO thickness; allowing these three basic electronic components to be integrated. High-performance FTJ synapses with adaptive conductance compensation from resistor and FD components are proposed based on an on-chip integration configuration. This approach improves the accuracy of handwritten digit recognition using artificial neural networks (ANNs) from 91.3% to 95.7%. Despite Gaussian noise interference; the ANN based on this adaptive compensation approach remains extremely fault-tolerant; and is expected to meet the increasing demands of contemporary electronic devices; particularly in the fields of memory; logic processing; and neuromorphic computing.
Keywords:
ferroelectric tunnel junctions
ferroelectric diodes
neuromorphic computing
resistive switching
synaptic devices
Journal
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10.7
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3.6K
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2.4W
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