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Room-Temperature Fabricated Multilevel Nonvolatile Lead-Free Cesium Halide Memristors for Reconfigurable In-Memory Computing
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Room-Temperature Fabricated Multilevel Nonvolatile Lead-Free Cesium Halide Memristors for Reconfigurable In-Memory Computing

Tsung-Kai Su, Wei-Kai Cheng, Cheng-Yueh Chen, Wei-Chun Wang, Yung-Tang Chuang, Guang-Hsun Tan, Hao-Cheng Lin, Cheng-Hung Hou, Ching-Min Liu, Ya-Chu Chang, …
ACS Nano
2022

摘要

in-memory computing memristor metal halide multilevel nonvolatile perovskite Materials Science (all) Engineering (all) Physics and Astronomy (all)
Recently, conductive-bridging memristors based on metal halides, such as halide perovskites, have been demonstrated as promising components for brain-inspired hardware-based neuromorphic computing. However, realizing devices that simultaneously fulfill all of the key merits (low operating voltage, high dynamic range, multilevel nonvolatile storage capability, and good endurance) remains a great challenge. Herein, we describe lead-free cesium halide memristors incorporating a MoOX interfacial layer as a type of conductive-bridging memristor. With this design, we obtained highly uniform and reproducible memristors that exhibited all-around resistive switching characteristics: ultralow operating voltages (<0.18 V), low variations (<30 mV), long retention times (>106 s), high endurance (>105, full on/off cycles), record-high on/off ratios (>1010, smaller devices having areas <5 × 10-4 mm2), fast switching (<200 ns), and multilevel programming abilities (>64 states). With these memristors, we successfully implemented stateful logic functions in a reconfigurable architecture and accomplished a high classification accuracy (ca. 90%) in the simulated hand-written-digits classification task, suggesting their versatility in future in-memory computing applications. In addition, we exploited the room-temperature fabrication of the devices to construct a fully functional three-dimensional stack of memristors, which demonstrates their potential of high-density integration desired for data-intensive neuromorphic computing. High-performance, environmentally friendly cesium halide memristors provide opportunities toward next-generation electronics beyond von Neumann architectures.

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