tinyML Talks Phoenix: Novel Device and Materials in Emerging Memory for Neuromorphic Computing – Ying-Chen (Daphne) Chen

Novel Device and Materials in Emerging Memory for Neuromorphic Computing
Ying-Chen (Daphne) Chen
Assistant Professor
School of Informatics, Computing and Cyber Systems, Department of Electrical Engineering at Northern Arizona University

Towards the end of Moore’s law scaling limit, a critical need for novel device technologies is developed to break the limits of computing performance at the nanoscale meanwhile enabling better energy efficiency and power reduction. A new approach with the new materials and new device designs for exploring new computing paradigms attracts attention. To enable the highly efficient data-driven computing while with high reliability of memory storage, the new hardware technology on materials and devices are developed. This talk introduces the current development of novel materials in emerging electronics, such as highly scalable self-rectified memory, two-dimensional memory, self-aligned helical-structured materials, thermal stability investigation for next-generation memory, and neuromorphic computational applications.


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