Effect of SiCN thin film interlayer for ZnO-based RRAM

This study investigates the effect of silicon carbon nitride (SiCN) as an interlayer for ZnO-based resistive random access memory (RRAM). SiCN was deposited using plasma-enhanced chemical vapor deposition with controlled carbon content, achieved by varying the partial pressure of tetramethylsilane (4MS). Our results indicate that increasing the carbon concentration enhances the endurance of RRAM devices but reduces the on/off ratio. Devices with SiCN exhibited lower operating voltages and more uniform resistive switching behavior. Oxygen migration from ZnO to SiCN is examined by x-ray diffraction and x-ray photoelectron spectroscopy analyses, promoting the formation of conductive filaments and lowering set voltages. Additionally, we examined the impact of top electrode oxidation on RRAM performance. The oxidation of the Ti top electrode was found to reduce endurance and increase low resistive state resistance, potentially leading to device failure through the formation of an insulating layer between the electrode and resistive switching material. The oxygen storage capability of SiCN was further confirmed through high-temperature stress tests, demonstrating its potential as an oxygen reservoir. Devices with a 20 nm SiCN interlayer showed significantly improved endurance, with over 500 switching cycles, compared to 62 cycles in those with a 5 nm SiCN layer. However, the thicker SiCN layer resulted in a notably lower on/off ratio due to reduced capacitance. These findings suggest that SiCN interlayers can effectively enhance the performance and endurance of ZnO-based RRAM devices by acting as an oxygen reservoir and mitigating the top electrode oxidation effect.

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Publication Details

Journal
Nanotechnology
Published
2024-10-07
DOI
https://doi.org/10.1088/1361-6528/ad83d9
Citations
2
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.42

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article

Effect of SiCN thin film interlayer for ZnO-based RRAM

Do-Yeon Lee, Jun-Ho Byun, Ga‐Won Lee, Dong-Hyeuk Choi et al.
2 citations
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Advanced Memory and Neural Computing
0.42
article

Effect of SiCN thin film interlayer for ZnO-based RRAM

Do-Yeon Lee, Jun-Ho Byun, Ga‐Won Lee, Dong-Hyeuk Choi, Myeongho Song, So-Yeon Kwon, Woon-San Ko, Jong-Sin Hyun
article en
2 citations

Abstract

This study investigates the effect of silicon carbon nitride (SiCN) as an interlayer for ZnO-based resistive random access memory (RRAM). SiCN was deposited using plasma-enhanced chemical vapor deposition with controlled carbon content, achieved by varying the partial pressure of tetramethylsilane (4MS). Our results indicate that increasing the carbon concentration enhances the endurance of RRAM devices but reduces the on/off ratio. Devices with SiCN exhibited lower operating voltages and more uniform resistive switching behavior. Oxygen migration from ZnO to SiCN is examined by x-ray diffraction and x-ray photoelectron spectroscopy analyses, promoting the formation of conductive filaments and lowering set voltages. Additionally, we examined the impact of top electrode oxidation on RRAM performance. The oxidation of the Ti top electrode was found to reduce endurance and increase low resistive state resistance, potentially leading to device failure through the formation of an insulating layer between the electrode and resistive switching material. The oxygen storage capability of SiCN was further confirmed through high-temperature stress tests, demonstrating its potential as an oxygen reservoir. Devices with a 20 nm SiCN interlayer showed significantly improved endurance, with over 500 switching cycles, compared to 62 cycles in those with a 5 nm SiCN layer. However, the thicker SiCN layer resulted in a notably lower on/off ratio due to reduced capacitance. These findings suggest that SiCN interlayers can effectively enhance the performance and endurance of ZnO-based RRAM devices by acting as an oxygen reservoir and mitigating the top electrode oxidation effect.

NanotechnologyVol. 36(6)
Chungnam National University (KR), Hyupsung University (KR), Suwon Science College (KR), National NanoFab Center (KR)
National Research Foundation of Korea, Korea Technology and Information Promotion Agency for SMEs
Clean water and sanitation
Openalex Percentile: Top 38%
Advanced Memory and Neural Computing
0.42
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