Scholay

学术搜索 · AI 审稿 · LaTeX 协作

Ag-doped non–imperfection-enabled uniform memristive neuromorphic device based on van der Waals indium phosphorus sulfide

作者:Yesheng Li, Yao Xiong, Baoxing Zhai, Lei Yin, Yiling Yu, Hao Wang, Jun He · 发表于:Science Advances · 年份:2024 · DOI:10.1126/sciadv.adk9474 · 被引用次数:29 · 研究领域:Advanced Memory and Neural Computing、Ferroelectric and Negative Capacitance Devices、Perovskite Materials and Applications

Memristors are considered promising energy-efficient artificial intelligence hardware, which can eliminate the von Neumann bottleneck by parallel in-memory computing. The common imperfection-enabled memristors are plagued with critical variability issues impeding their commercialization. Reported approaches to reduce the variability usually sacrifice other performances, e.g., small on/off ratios and high operation currents. Here, we demonstrate an unconventional Ag-doped nonimperfection diffusion channel–enabled memristor in van der Waals indium phosphorus sulfide, which can combine ultralow variabilities with desirable metrics. We achieve operation voltage, resistance, and on/off ratio variations down to 3.8, 2.3, and 6.9% at their extreme values of 0.2 V, 10 11 ohms, and 10 8 , respectively. Meanwhile, the operation current can be pushed from 1 nA to 1 pA at the scalability limit of 6 nm after Ag doping. Fourteen Boolean logic functions and convolutional image processing are successfully implemented by the memristors, manifesting the potential for logic-in-memory devices and efficient non–von Neumann accelerators.