Controlling the Degree of Forming Soft-Breakdown and Producing Superior Endurance Performance by Inserting BN-Based Layers in Resistive Random Access Memory

2017 ◽  
Vol 38 (4) ◽  
pp. 445-448 ◽  
Author(s):  
Tsung-Ming Tsai ◽  
Cheng-Hsien Wu ◽  
Kuan-Chang Chang ◽  
Chih-Hung Pan ◽  
Po-Hsun Chen ◽  
...  
2020 ◽  
Vol 12 (2) ◽  
pp. 02008-1-02008-4
Author(s):  
Pramod J. Patil ◽  
◽  
Namita A. Ahir ◽  
Suhas Yadav ◽  
Chetan C. Revadekar ◽  
...  

Nanomaterials ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1401
Author(s):  
Te Jui Yen ◽  
Albert Chin ◽  
Vladimir Gritsenko

Large device variation is a fundamental challenge for resistive random access memory (RRAM) array circuit. Improved device-to-device distributions of set and reset voltages in a SiNx RRAM device is realized via arsenic ion (As+) implantation. Besides, the As+-implanted SiNx RRAM device exhibits much tighter cycle-to-cycle distribution than the nonimplanted device. The As+-implanted SiNx device further exhibits excellent performance, which shows high stability and a large 1.73 × 103 resistance window at 85 °C retention for 104 s, and a large 103 resistance window after 105 cycles of the pulsed endurance test. The current–voltage characteristics of high- and low-resistance states were both analyzed as space-charge-limited conduction mechanism. From the simulated defect distribution in the SiNx layer, a microscopic model was established, and the formation and rupture of defect-conductive paths were proposed for the resistance switching behavior. Therefore, the reason for such high device performance can be attributed to the sufficient defects created by As+ implantation that leads to low forming and operation power.


2021 ◽  
Vol 23 (10) ◽  
pp. 5975-5983
Author(s):  
Jie Hou ◽  
Rui Guo ◽  
Jie Su ◽  
Yawei Du ◽  
Zhenhua Lin ◽  
...  

In this study, at least three kinds of VOs and conductive filaments with low resistance states and forming and set voltages are found for β-Ga2O3 memory. This suggests the great potential of β-Ga2O3 memory for multilevel storage application.


2008 ◽  
Vol 93 (22) ◽  
pp. 223505 ◽  
Author(s):  
Jung Won Seo ◽  
Jae-Woo Park ◽  
Keong Su Lim ◽  
Ji-Hwan Yang ◽  
Sang Jung Kang

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