Publications by authors named "Max Uhlmann"
Article Synopsis
- Resistive Random Access Memory (RRAM) is being researched for its benefits in energy efficiency and non-volatility, but designing effective systems is complex and time-consuming for material and device scientists.
- There's a need for a user-friendly modeling framework that helps researchers evaluate device performance early in the design process, focusing on speed, accuracy, and adaptability.
- This paper presents a digital twin (DT)-like framework that generates RRAM device models from measurement data, includes peripheral circuits for better evaluations, and demonstrates its effectiveness in applications like neural network processing of ECG data and Fault Aware Training.
