Date: Friday, May 9, 2025
Time: 11 a.m. – 1 p.m.
Location: Pettit 102A
Speaker: Rivka-Galya Nir-Harwood
Speaker’s Affiliation: Technion – Israel Institute of Technology
Abstract:
Phase-change memory (PCM) devices are promising candidates for multi-level storage and neuromorphic computing, yet their reliability is challenged by resistance drift. Traditionally attributed to bulk mechanisms, our study reexamines this effect in sub-100-nm Ge₂Sb₂Te₅ (GST) devices, revealing that interface phenomena—particularly the Schottky barrier height at electrical contacts—play a dominant role. Through temperature-dependent and transient electrical measurements, we show that drift arises from a time-dependent increase in this barrier. This underscores the significance of contacts (interfaces) in the electrical manifestation of drift in PCM devices. We further explore Ovonic threshold switches (OTS) as high-speed, low-power selectors. These devices exhibit sharp, field-induced switching behavior, and within the selector-only memory (SOM) scheme, their threshold voltages can be dynamically tuned via pre-conditioning pulses. Preliminary results seek to examine bulk vs interface effects in SOM operation, through temperature-dependent and high-speed measurements. Together, these findings deepen our understanding of interface-driven phenomena in memory devices and point toward scalable, drift-resilient memory architectures.
Biographical Sketch of the Speaker:
Rivka-Galya Nir-Harwood is a Ph.D. student at the Andrew and Erna Viterbi Faculty of Electrical & Computer Engineering, Technion – Israel Institute of Technology. She received her B.Sc. degree in Electrical & Computer Engineering from the Technion as well. Rivka-Galya received the Israel Council for Higher Education Women Scholarship for Outstanding PhD Students in High-Tech Profession (2025), the Russell Berrie Nanotechnology Institute Scholarship for excellence (2024) along with other scholarships and awards. Her main research topic is bulk vs interface characterization in phase change memory for neuromorphic computing applications.