This work demonstrates optimized ferroelectric tunnel junctions achieving high-performance in-memory computing, suggesting efficient memory solutions.
Strategic optimization of ferroelectric tunnel junctions (FTJs) is critical for advancing nonvolatile memory and neuromorphic computing technologies. In this work, we present a comprehensive study on materials and structural engineering to enable scalable hybrid-switching FTJ arrays. We systematically manipulated oxygen vacancy (VO) concentrations in HfZrO₂ (HZO) films through strategic choices of bottom electrodes and interfacial layers, achieving three distinct operational modes: pure ferroelectric switching, defect-modulated switching, and combined hybrid switching. Our optimized devices demonstrate exceptional tunneling electroresistance (TER) performance: Mo bottom electrodes achieve a TER ratio of around 10², while Mo/Ti bottom electrodes attain TER to over 10⁴. Lower-leakage ferroelectric switching and enhanced polarization stability are observed with Mo bottom and ZrO₂ interlayers, while VO-driven resistive contributions from Ti electrodes amplify TER in hybrid devices. Utilizing these optimized parameters, we fabricated a 42 × 42 FTJ array demonstrating uniform multi-level conductance modulation. The fabricated FTJ array was integrated into an in-memory Vision Transformer (ViT) architecture, successfully performing stable and energy-efficient parallel vector-matrix multiplication (VMM) operations despite device variability. This work shows that precisely engineered, large-area hybrid-switching FTJ arrays can provide a scalable and energy-efficient hardware platform for next-generation memory and neuromorphic systems.
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