Beyond CMOS: Materials, Emerging Memory and Applications

Event Date: February 1, 2022
Time: 1:30 pm
Location: WANG 1004
Priority: No
School or Program: Electrical and Computer Engineering
College Calendar: Show
Ying-Chen Chen
Assistant Professor
Northern Arizona University

As Moore's law nears its physical limits, a next generation device technology which break the limits of computing performance and merge the memory hierarchy gap enables high speed and low power computations. The microelectronics composed of the new materials and new devices for exploring the advanced paradigms of computing is in a high demand. Among the emerging semiconductor electronics technologies, non-volatile memory become the candidate for enabling the highly efficient computing while with nonvolatility for reliable low power information storage applications in the era of in-memory computing and artificial intelligent applications. Among non-volatile memories, resistive random-access memory holds great potential because of its simple design, high-speed operation, excellent scalability, and low power consumption. However, the sneak-path current (SPC) through unselected neighboring cells is a major challenge occurring in crossbar RRAM configuration, especially for large memory arrays. To address the sneak path current issue, a selector device (or a threshold switch) integrated with a memory device has been developed. Several bidirectional selector devices have been proposed for bipolar RRAM, such as transistor device, tunneling diode, Schottky diode, and threshold switches.
Unfortunately, these additional selector devices i.e. 1S-1R or 1T-1R configuration considerably increase the process complexity and cost. My research focused on the one-resistor-only (1R-only) memory cell with self-selectivity and which is applicable without additional selector device integration and solves the sneak-path issue for high storage class crossbar array configuration for future applications in AI and IoT. This talk also include the current developments on emerging memory electronics, such as brain-inspired application, one-time programmable memory, security, and dual functional hybrid components for next generation storage and computational applications.
Dr. Ying-Chen (Daphne) Chen is currently the assistant professor in School of Informatics, Computing and Cyber Systems (Electrical and Computing Engineering) at Northern Arizona University. She received the Ph.D. degree in Electrical and Computer Engineering (ECE) at The University of Texas at Austin in 2019, B.S. and M.S. degree from National Chiao Tung University (Taiwan). Prior to joining NAU, she was the R&D Pathfinding Emerging Memory Engineer at Micron Technology working on emerging memory and future applications. Her primary research focuses on emerging electronics and memory devices for high density storage, new computing, and energy-efficient integrated systems. She has authored/co-authored over 32 journal publications and 25 conference proceedings with the widely citations. She was also the recipient of Sandia National Laboratory Research Award 2019, and Rising Stars 2017 in EECS.
Professor Joerg Appenzeller,

2022-02-01 13:30:00 2022-02-01 14:30:00 US/East-Indiana Beyond CMOS: Materials, Emerging Memory and Applications Ying-Chen Chen Assistant Professor Northern Arizona University WANG 1004