Improved Device Distribution in High-Performance SiNx Resistive Random Access Memory via Arsenic Ion Implantation
| Autor: | Albert Chin, Te Jui Yen, Vladimir A. Gritsenko |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
010302 applied physics
Materials science business.industry General Chemical Engineering neuron mimicking device 02 engineering and technology SiNx RRAM 021001 nanoscience & nanotechnology Thermal conduction 01 natural sciences Stability (probability) Ion Power (physics) Resistive random-access memory Chemistry Ion implantation 0103 physical sciences Optoelectronics General Materials Science ion implantation 0210 nano-technology business Layer (electronics) QD1-999 Voltage |
| Zdroj: | Nanomaterials, Vol 11, Iss 1401, p 1401 (2021) Nanomaterials Volume 11 Issue 6 |
| ISSN: | 2079-4991 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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