Investigation of key performance metrics in TiOX/TiN based resistive random-access memory cells

Published

July 3, 2025

Author(s)

Brandon Zink, William Borders, Advait Madhavan, Brian Hoskins, Jabez McClelland

Abstract

Resistive random-access memory (RRAM) is a promising beyond-CMOS technology due to its non-volatility, scalability, and high ON/OFF ratio. Furthermore, a single RRAM cell can operate as an analog resistor, meaning that it can be used in more novel computing applications such as tunable synapses in neuromorphic computing. However, issues of poor uniformity and poor yield persist in RRAM. In this work, we performed a systematic study on six different TiOX/TiN RRAM samples with varying layer thicknesses. For each sample, we investigate how the layer thicknesses, presence of background oxygen, and testing parameters influence key performance metrics in each sample. These metrics include switching probabilities, failure mechanisms, operating voltage, ON/OFF ratio, device-to-device variation, and tunable resistance capabilities to determine their viability as multi-state memory cells. Our results reveal clear trade-offs between high ON/OFF ratio, high resistance tunability and high device-to-device variations. Furthermore, operating conditions within the same sample that produce large ON/OFF ratios are often not the same as those that produce low variations and high switching probabilities. The results presented in this paper provide a detailed insight into how intrinsic device properties and operating conditions influence RRAM performance and could be used for considerations in designing future RRAM technologies.

Citation

Scientific Reports

Volume

15

Issue

1

Pub Type

Journals

Download Paper

https://doi.org/10.1038/s41598-025-07925-3

Local Download

Keywords

Resistive Random-Access Memory, Non-Volatile Memory, Tunable Resistance

Citation

Zink, B. , Borders, W. , Madhavan, A. , Hoskins, B. and McClelland, J. (2025), Investigation of key performance metrics in TiOX/TiN based resistive random-access memory cells, Scientific Reports, [online], https://doi.org/10.1038/s41598-025-07925-3, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=959130 (Accessed July 12, 2025)