Unveiling ECRAM switching mechanisms using variable temperature Hall measurements for accelerated AI computation

利用变温霍尔测量揭示ECRAM开关机制,加速人工智能计算

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Abstract

Electrochemical random-access memory devices are promising for analog cross-point array-based artificial intelligence accelerators due to their high stability and programmability. However, understanding their switching mechanism is challenging due to complex multilayer structures and the high resistivity of oxide materials. Here, we fabricate multi-terminal Hall-bar devices and conduct alternating current magnetic parallel dipole line Hall measurements to extract transport parameters. Through variable-temperature Hall measurements, we determine the oxygen donor level at approximately 0.1 eV in tungsten oxide and reveal that conductance potentiation even at low temperatures results from increased mobility and carrier density. This behavior is linked to reversible electronic and atomic structure changes, supported by density functional theory calculations. Our findings enhance the understanding of electrochemical random-access memory switching mechanisms and provide insights for improving high-performance, energy-efficient artificial intelligence computation in analog hardware.

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