Quantum materials for energy-efficient neuromorphic computing: Opportunities and challenges

Published

July 19, 2022

Author(s)

Axel Hoffmann, Shriram Ramanathan, Julie Grollier, Andrew Kent, Marcelo Rozenberg, Ivan Schuller, Oleg Shpyrko, Robert Dynes, Yeshaiahu Fainman, Alex Frano, Eric Fullerton, Giulia Galli, Vitaliy Lomakin, Shyue Ping Ong, Amanda K. Petford-Long, Jonathan A. Schuller, Mark Stiles, Yayoi Takamura, Yimei Zhu

Abstract

Neuromorphic computing approaches become increasingly important as we address future needs for efficiently processing massive amounts of data. The unique attributes of quantum materials can help address these needs by enabling new energy-efficient device concepts that implement neuromorphic ideas at the hardware level. In particular, strong correlations give rise to highly non-linear responses, such as conductive phase transitions that can be harnessed for short and long-term plasticity transitions. Similarly, magnetization dynamics are strongly non-linear and can be utilized for data classification. This paper discusses select examples of these approaches, and provides a perspective for the current opportunities and challenges for assembling quantum-material-based devices for neuromorphic functionalities into larger emergent complex network systems.

Citation

APL Materials

Volume

10

Issue

7

Pub Type

Journals

Download Paper

https://doi.org/10.1063/5.0094205

Local Download

Keywords

Neuromorphic computing, spintronics, quantum materials, memristor, neuristor, metal insulator transition, plasticity, magnetization dynamics

Citation

Hoffmann, A. , Ramanathan, S. , Grollier, J. , Kent, A. , Rozenberg, M. , Schuller, I. , Shpyrko, O. , Dynes, R. , Fainman, Y. , Frano, A. , Fullerton, E. , Galli, G. , Lomakin, V. , Ong, S. , Petford-Long, A. , Schuller, J. , Stiles, M. , Takamura, Y. and Zhu, Y. (2022), Quantum materials for energy-efficient neuromorphic computing: Opportunities and challenges, APL Materials, [online], https://doi.org/10.1063/5.0094205, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=934499 (Accessed February 12, 2025)