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Ferroelectric Transistors for Memory and Neuromorphic Device Applications

Ik‐Jyae Kim, Jang‐Sik Lee

2022Advanced Materials222 citationsDOI

Abstract

Ferroelectric materials have been intensively investigated for high-performance nonvolatile memory devices in the past decades, owing to their nonvolatile polarization characteristics. Ferroelectric memory devices are expected to exhibit lower power consumption and higher speed than conventional memory devices. However, non-complementary metal-oxide-semiconductor (CMOS) compatibility and degradation due to fatigue of traditional perovskite-based ferroelectric materials have hindered the development of high-density and high-performance ferroelectric memories in the past. The recently developed hafnia-based ferroelectric materials have attracted immense attention in the development of advanced semiconductor devices. Because hafnia is typically used in CMOS processes, it can be directly incorporated into current semiconductor technologies. Additionally, hafnia-based ferroelectrics show high scalability and large coercive fields that are advantageous for high-density memory devices. This review summarizes the recent developments in ferroelectric devices, especially ferroelectric transistors, for next-generation memory and neuromorphic applications. First, the types of ferroelectric memories and their operation mechanisms are reviewed. Then, issues limiting the realization of high-performance ferroelectric transistors and possible solutions are discussed. The experimental demonstration of ferroelectric transistor arrays, including 3D ferroelectric NAND and its operation characteristics, are also reviewed. Finally, challenges and strategies toward the development of next-generation memory and neuromorphic applications based on ferroelectric transistors are outlined.

Topics & Concepts

Neuromorphic engineeringMaterials scienceFerroelectricityTransistorMemristorOptoelectronicsNanotechnologyNon-volatile memoryElectronic engineeringElectrical engineeringComputer scienceArtificial neural networkArtificial intelligenceVoltageDielectricEngineeringFerroelectric and Negative Capacitance DevicesAdvanced Memory and Neural ComputingSemiconductor materials and devices