Low-Power Memristor for Neuromorphic Computing: From Materials to Applications DOI Creative Commons
Zhipeng Xia, Xiao Wei Sun, Zhenlong Wang

и другие.

Nano-Micro Letters, Год журнала: 2025, Номер 17(1)

Опубликована: Апрель 14, 2025

Abstract As an emerging memory device, memristor shows great potential in neuromorphic computing applications due to its advantage of low power consumption. This review paper focuses on the application low-power-based memristors various aspects. The concept and structure devices are introduced. selection functional materials for low-power is discussed, including ion transport materials, phase change magnetoresistive ferroelectric materials. Two common types arrays, 1T1R 1S1R crossbar arrays introduced, physical diagrams edge chips discussed detail. Potential advanced multi-value storage, digital logic gates, analogue summarized. Furthermore, future challenges outlook based deeply discussed.

Язык: Английский

Low-Power Memristor for Neuromorphic Computing: From Materials to Applications DOI Creative Commons
Zhipeng Xia, Xiao Wei Sun, Zhenlong Wang

и другие.

Nano-Micro Letters, Год журнала: 2025, Номер 17(1)

Опубликована: Апрель 14, 2025

Abstract As an emerging memory device, memristor shows great potential in neuromorphic computing applications due to its advantage of low power consumption. This review paper focuses on the application low-power-based memristors various aspects. The concept and structure devices are introduced. selection functional materials for low-power is discussed, including ion transport materials, phase change magnetoresistive ferroelectric materials. Two common types arrays, 1T1R 1S1R crossbar arrays introduced, physical diagrams edge chips discussed detail. Potential advanced multi-value storage, digital logic gates, analogue summarized. Furthermore, future challenges outlook based deeply discussed.

Язык: Английский

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