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Investigation of key performance metrics in TiOX/TiN based resistive random-access memory cells
Brandon R Zink1, William A Borders2, Advait Madhavan2
1Physical Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, 20899, USA. brandon.zink@nist.gov.
Scientific Reports
|July 3, 2025
Summary
Resistive random-access memory (RRAM) shows promise for new computing, but faces uniformity challenges. This study optimizes RRAM performance by analyzing layer thickness and oxygen effects on key metrics.
Area of Science:
- Materials Science
- Electrical Engineering
- Solid-State Physics
Background:
- Resistive random-access memory (RRAM) is a key beyond-CMOS technology offering non-volatility, scalability, and high ON/OFF ratios.
- RRAM's analog resistive nature enables novel applications like tunable synapses in neuromorphic computing.
- Persistent challenges in RRAM include poor uniformity and low manufacturing yield, hindering widespread adoption.
Purpose of the Study:
- To systematically investigate the influence of layer thicknesses and background oxygen on RRAM performance.
- To analyze how testing parameters affect switching probabilities, failure mechanisms, and operating voltage.
- To determine the viability of TiOX/TiN RRAM as multi-state memory cells by evaluating ON/OFF ratio, variation, and tunability.
Main Methods:
- A systematic study was conducted on six different TiOX/TiN RRAM samples with varied layer thicknesses.
- Key performance metrics including switching probabilities, failure mechanisms, operating voltage, ON/OFF ratio, device-to-device variation, and tunable resistance were analyzed.
- The impact of layer thicknesses, background oxygen presence, and testing parameters on these metrics was investigated for each sample.
Main Results:
- Clear trade-offs exist between achieving a high ON/OFF ratio, high resistance tunability, and minimizing device-to-device variations.
- Optimal operating conditions for maximizing the ON/OFF ratio often differ from those yielding low variations and high switching probabilities.
- Device performance is significantly influenced by intrinsic material properties and specific operating conditions.
Conclusions:
- Understanding the interplay between intrinsic device properties and operating conditions is crucial for RRAM design.
- The findings provide insights for optimizing RRAM performance and addressing uniformity and yield issues.
- TiOX/TiN RRAM exhibits potential for multi-state memory applications, but careful parameter tuning is required.
