Forming-free flexible memristor with multilevel storage for neuromorphic computing by full PVD technique
有为由完整的 PVD 技术计算的 neuromorphic 的 multilevel 存储的没有形式的灵活 memristor作者机构:State Key Laboratory of ASIC and SystemSchool of MicroelectronicsFudan UniversityShanghai 200433China
出 版 物:《Journal of Materials Science & Technology》 (材料科学技术(英文版))
年 卷 期:2021年第60卷第1期
页 面:21-26页
核心收录:
学科分类:08[工学] 081201[工学-计算机系统结构] 0812[工学-计算机科学与技术(可授工学、理学学位)]
基 金:supported by the National Natural Science Foundation of China(Nos.61704030 and 61522404) the Shanghai Rising-Star Program(No.19QA1400600) the Program of Shanghai Subject Chief Scientist(No.18XD1402800) the Support Plans for the Youth Top-Notch Talents of China
主 题:Full PVD process Flexible memristor Forming-free Multilevel storage Neuromorphic application
摘 要:Flexible resistive random access memory(RRAM) has shown great potential in wearable *** tunable multilevel resistance states,flexible memristors could be used to mimic the bio-synapses for constructing high-efficient wearable neuromorphic computing ***,the flexible substrate has intrinsic disadvantages including low-tempe rature tolerance and poor complementary metal-oxidesemiconductor(CMOS) compatibility,which limit the development of flexible *** physical vapor deposition(PVD) fabrication process could prepare RRAM without requirement of further treatment,which greatly simplified preparation steps and reduced the production *** the other hand,forming process,as a common pre-programing operation in RRAM,increases the energy consumption and limits the application scenarios of ***,a NiO-based forming-free RRAM with low set voltage was fabricated via full PVD *** flexible device exhibited reliable re sistive switching characteristics under flat state even compre s sive and tensile states(R=10 mm).The tunable multilevel resistance states(5 levels) could be obtained by controlling the compliance ***,synaptic plasticities also were verified in this *** flexible NiO-based RRAM shows great potential in wearable forming-free multibit memo ry and neuromorphic computing electronics.