Flexible Parylene C-Based RRAM Array for Neuromorphic Applications

被引:11
|
作者
Kim, Jo-Eun [1 ]
Kim, Boram [1 ]
Kwon, Hui Tae [1 ]
Kim, Jaesung [1 ]
Kim, Kyungmin [1 ]
Park, Dong-Wook [1 ]
Kim, Yoon [1 ]
机构
[1] Univ Seoul, Sch Elect & Comp Engn, Seoul 02504, South Korea
来源
IEEE ACCESS | 2022年 / 10卷
基金
新加坡国家研究基金会;
关键词
Neuromorphic; RRAM; parylene C; artificial neural network; memristor; flexible neuromorphic electronics; MEMORY; MECHANISM; DEVICE; MEMRISTORS; TRANSPORT; SYNAPSE; MODEL;
D O I
10.1109/ACCESS.2022.3211956
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Resistive random-access memory (RRAM) has been explored to implement neuromorphic systems to accelerate neural networks. In this study, an RRAM crossbar array using parylene C (PPXC) as both a resistive switching layer and substrate was fabricated. PPXC is a flexible and transparent polymer with excellent chemical stability and biocompatibility. We studied PPXC-based RRAM devices with Ti/PPX-C/Cu and Cu/PPX-C/Ti structures. Devices with the Ti/PPX-C/Cu structure offer stable electrical and mechanical characteristics, such as a low set voltage of <1 V, good retention time of >10(4) s, endurance cycles of >300, conductance ON/OFF ratio >10, and can withstand >350 mechanical bending cycles. Additionally, the switching and conduction mechanisms of the devices were carefully investigated by analyzing their electrical, structural, and chemical properties. Finally, we demonstrated the feasibility of the fabricated RRAM array for neuromorphic applications through system-level simulations using the Modified National Institute of Standards and Technology database. The simulation results reflecting the variations of realistic devices demonstrated that the artificial neural network developed using the PPXC-based RRAM array works satisfactorily in pattern recognition tasks. The findings of this study can aid in the development of future wearable neuromorphic systems.
引用
收藏
页码:109760 / 109767
页数:8
相关论文
共 50 条
  • [21] Investigation of I-V Linearity in TaOx-Based RRAM Devices for Neuromorphic Applications
    Sung, Changhyuck
    Padovani, Andrea
    Beltrando, Bastien
    Lee, Donguk
    Kwak, Myunghoon
    Lim, Seokjae
    Larcher, Luca
    Della Marca, Vincenzo
    Hwang, Hyunsang
    IEEE JOURNAL OF THE ELECTRON DEVICES SOCIETY, 2019, 7 (01): : 404 - 408
  • [22] A WIRELESS FLEXIBLE WEARABLE BIOPOTENTIAL ACQUISITION SYSTEM UTILIZING PARYLENE BASED MICRONEEDLE ARRAY
    Huang, Dong
    Wang, Hancong
    Li, Junshi
    Chen, Yufeng
    Li, Zhihong
    2019 20TH INTERNATIONAL CONFERENCE ON SOLID-STATE SENSORS, ACTUATORS AND MICROSYSTEMS & EUROSENSORS XXXIII (TRANSDUCERS & EUROSENSORS XXXIII), 2019, : 298 - 301
  • [23] Ultrathin Parylene C-based sensitivity-gain nanoplasmonic sensor integrated on VCSEL for Aβ 42 detection
    Lv, Xiaoqing
    Ma, Zhengtai
    Jiang, Wenhui
    Huang, Chengcheng
    Deng, Jun
    Zhang, Huan
    Chang, Pengying
    Xie, Yiyang
    BIOSENSORS & BIOELECTRONICS, 2024, 254
  • [24] A Quantized-Weight-Splitting Method of RRAM Arrays for Neuromorphic Applications
    Park, Kyungchul
    Kim, Sungjoon
    Park, Jong-Hyuk
    Choi, Woo Young
    IEEE ACCESS, 2024, 12 : 59680 - 59687
  • [25] An Inkjet Printed Flexible Electrocorticography (ECoG) Microelectrode Array on a Thin Parylene-C Film
    Kim, Yoontae
    Alimperti, Stella
    Choi, Paul
    Noh, Moses
    SENSORS, 2022, 22 (03)
  • [26] FLEXIBLE TACTILE SENSING ARRAY WITH HIGH SPATIAL DENSITY BASED ON PARYLENE MEMS TECHNIQUE
    Zhang, Meixuan
    Wang, Zetian
    Xu, Han
    Chen, Lang
    Jin, Yufeng
    Wang, Wei
    2023 IEEE 36TH INTERNATIONAL CONFERENCE ON MICRO ELECTRO MECHANICAL SYSTEMS, MEMS, 2023, : 243 - 246
  • [27] Circuit Modeling for RRAM-Based Neuromorphic Chip Crossbar Array With and Without Write-Verify Scheme
    Tao, Tuomin
    Ma, Hanzhi
    Chen, Quankun
    Gu, Zhe-Ming
    Jin, Hang
    Ahmed, Manareldeen
    Tan, Shurun
    Wang, Aili
    Liu, En-Xiao
    Li, Er-Ping
    IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS, 2021, 68 (05) : 1906 - 1916
  • [28] Investigation of Non-Linear Selection Effect on RRAM based Neuromorphic Computing Array with Passive Selective Element
    Bao, Shengyu
    Wang, Zongwei
    Ling, Yaotian
    Yu, Zhizhen
    Qin, Yabo
    Cai, Yimao
    Huang, Ru
    2021 5TH IEEE ELECTRON DEVICES TECHNOLOGY & MANUFACTURING CONFERENCE (EDTM), 2021,
  • [29] Understanding and Optimization of Pulsed SET Operation in HfOx-Based RRAM Devices for Neuromorphic Computing Applications
    Padovani, Andrea
    Woo, Jiyong
    Hwang, Hyunsang
    Larcher, Luca
    IEEE ELECTRON DEVICE LETTERS, 2018, 39 (05) : 672 - 675
  • [30] Graphite-based selectorless RRAM: improvable intrinsic nonlinearity for array applications
    Chen, Ying-Chen
    Hu, Szu-Tung
    Lin, Chih-Yang
    Fowler, Burt
    Huang, Hui-Chun
    Lin, Chao-Cheng
    Kim, Sungjun
    Chang, Yao-Feng
    Lee, Jack C.
    NANOSCALE, 2018, 10 (33) : 15608 - 15614