神经形态工程学
记忆电阻器
材料科学
热稳定性
去模糊
纳米技术
理论(学习稳定性)
聚合物
光电子学
计算机科学
电子工程
人工智能
图像处理
图像(数学)
化学工程
人工神经网络
工程类
复合材料
机器学习
图像复原
作者
Ziyu Lv,Minghao Jiang,Huiying Liu,Qing‐Xiu Li,Tao Xie,Jingya Yang,Yan Wang,Yongbiao Zhai,Guanglong Ding,Shirui Zhu,Jiahua Li,Miao Zhang,Ye Zhou,Bobo Tian,Wai‐Yeung Wong,Su‐Ting Han
标识
DOI:10.1002/adfm.202424382
摘要
Abstract Organic memristors have emerged as promising candidates for neuromorphic computing due to their potential for low‐cost fabrication, large‐scale integration, and biomimetic functionality. However, their practical applications are often hindered by limited thermal stability and device‐to‐device variability. Here, an organic polymer‐based memristor using a thiadiazolobenzotriazole (TBZ) and 2,5‐Dioctyl‐3,6‐di(thiophen‐2‐yl)pyrrolo[3,4‐c]pyrrole‐1,4(2H,5H)‐dione (DPP)‐based conjugated polymer is presented that exhibits exceptional thermal stability and reliable resistance switching behavior over a wide temperature range (153–573 K). The device leverages a charge‐transfer mechanism to achieve gradual and uniform resistance switching, overcoming the challenges associated with filamentary‐based mechanisms. The memristor's exceptional thermal stability and consistent performance enable its integration into various applications, including image processing. The device's ability is demonstrated to effectively deblur images, even under varying temperature conditions, showcasing its potential for robust and reliable neuromorphic computing. This study establishes a pathway toward high‐performance, thermally stable organic memristors for advanced neuromorphic computing and artificial intelligence applications.
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