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

• Published in: ACS nano Vol. 16; no. 8; pp. 12979 - 12990
• Main Authors: Su, Tsung-Kai, Cheng, Wei-Kai, Chen, Cheng-Yueh, Wang, Wei-Chun, Chuang, Yung-Tang, Tan, Guang-Hsun, Lin, Hao-Cheng, Hou, Cheng-Hung, Liu, Ching-Min, Chang, Ya-Chu, Shyue, Jing-Jong, Wu, Kai-Chiang, Lin, Hao-Wu
• Format: Journal Article
• Language: English
• Published: American Chemical Society 23.08.2022
• Subjects: nonvolatile; perovskite; metal halide; in-memory computing; memristor; multilevel
• ISSN: 1936-0851; 1936-086X; 1936-086X
• DOI: 10.1021/acsnano.2c05436

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 MoO X 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.