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Journal Articles Applied Physics Reviews Year : 2022

Ferroelectric polymers for neuromorphic computing

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Abstract

The last few decades have witnessed the rapid development of electronic computers relying on von Neumann architecture. However, due to the spatial separation of the memory unit from the computing processor, continuous data movements between them result in intensive time and energy consumptions, which unfortunately hinder the further development of modern computers. Inspired by biological brain, the in situ computing of memristor architectures, which has long been considered to hold unprecedented potential to solve the von Neumann bottleneck, provides an alternative network paradigm for the next-generation electronics. Among the materials for designing memristors, i.e., nonvolatile memories with multistate tunable resistances, ferroelectric polymers have drawn much research interest due to intrinsic analog switching property and excellent flexibility. In this review, recent advances on artificial synapses based on solution-processed ferroelectric polymers are discussed. The relationship between materials' properties, structural design, switching mechanisms, and systematic applications is revealed. We first introduce the commonly used ferroelectric polymers. Afterward, device structures and the switching mechanisms underlying ferroelectric synapse are discussed. The current applications of organic ferroelectric synapses in advanced neuromorphic systems are also summarized. Eventually, the remaining challenges and some strategies to eliminate non-ideality of synaptic devices are analyzed.
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Dates and versions

hal-03721242 , version 1 (12-07-2022)

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Xuezhong Niu, Bobo Tian, Qiuxiang Zhu, Brahim Dkhil, Chungang Duan. Ferroelectric polymers for neuromorphic computing. Applied Physics Reviews, 2022, 9 (2), pp.021309. ⟨10.1063/5.0073085⟩. ⟨hal-03721242⟩
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