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Inorganic Halide Perovskite Quantum Dots for Memristors

Hyo Min Cho, Ho Won Jang

2025Electronic Materials Letters16 citationsDOIOpen Access PDF

Abstract

Abstract Memristor, a combination of memory and resistor, was first proposed as the fourth fundamental passive circuit element. While halide perovskites have emerged as promising materials for memristor devices, organic-inorganic hybrid perovskites face challenges such as hygroscopicity and thermal instability, limiting their long-term applicability. This paper focuses on inorganic halide perovskite quantum dots (IHPQDs), which offer enhanced environmental stability and unique properties, including high tolerance to native defects and ion migration capability. This paper provides a comprehensive review of recent advancements in IHPQDs, covering their crystal structures, synthesis techniques, and operational mechanisms in memristor devices. Unlike previous studies that predominantly explored bulk halide perovskites, we emphasize the role of IHPQDs in resistive switching memory and neuromorphic computing, highlighting their potential for multilevel resistance states and low-power operation. Additionally, this review addresses practical challenges, including thin-film uniformity, charge transport layer integration, and lead-free alternatives, which are critical for the commercialization of IHPQDs-based memristors. By proposing actionable strategies and future research directions, we aim to bridge the gap between fundamental research and real-world applications, positioning IHPQDs as key materials for next-generation electronic devices. Graphical Abstract

Topics & Concepts

MemristorNeuromorphic engineeringPerovskite (structure)Materials scienceResistive random-access memoryHalideNanotechnologyQuantum dotOptoelectronicsEngineering physicsComputer scienceElectronic engineeringElectrical engineeringVoltagePhysicsEngineeringChemistryArtificial neural networkChemical engineeringInorganic chemistryMachine learningPerovskite Materials and ApplicationsAdvanced Memory and Neural ComputingConducting polymers and applications
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