PZT Optical Memristors
Optical memristors represent a monumental leap in the fusion of photonics and electronics, heralding a new era of new applications from neuromorphic computing to artificial intelligence. However, current technologies are hindered by complex fabrication, limited endurance, high optical loss or low mo...
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Main Authors | , , , , , , , , , , , , , , , |
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Format | Journal Article |
Language | English |
Published |
07.11.2024
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Subjects | |
Online Access | Get full text |
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Summary: | Optical memristors represent a monumental leap in the fusion of photonics and
electronics, heralding a new era of new applications from neuromorphic
computing to artificial intelligence. However, current technologies are
hindered by complex fabrication, limited endurance, high optical loss or low
modulation efficiency. For the first time, we unprecedentedly reveal optical
non-volatility in thin-film Lead Zirconate Titanate (PZT) by electrically
manipulating the ferroelectric domains to control the refractive index,
providing a brand-new routine for optical memristors. The developed PZT optical
memristors offer unprecedented advantages more than exceptional performance
metrics like low loss, high precision, high-efficiency modulation, high
stability quasi-continuity and reconfigurability. The wafer-scale sol-gel
fabrication process also ensures compatible with standardized mass fabrication
processes and high scalability for photonic integration. Specially, these
devices also demonstrate unique functional duality: setting above a threshold
voltage enables non-volatile behaviors, below this threshold allows volatile
high-speed optical switching. This marks the first-ever optical memristor
capable of performing high-speed signal processing and non-volatile retention
on a single platform, and is also the inaugural demonstration of scalable
functional systems. The PZT optical memristors developed here facilitate the
realization of novel paradigms for high-speed and energy-efficient optical
interconnects, programmable PICs, quantum computing, neural networks, in-memory
computing and brain-like architecture. |
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DOI: | 10.48550/arxiv.2411.04665 |