Published In

18th ACM International Symposium on Nanoscale Architectures (NANOARCH ’23)

Document Type


Publication Date



Traditional computing is based on an engineering approach that imposes logical states and a computational model upon a physical substrate. Physical or material computing, on the other hand, harnesses and exploits the inherent, naturally-occurring properties of a physical substrate to perform a computation. To do so, reservoir computing is often used as a computing paradigm. In this review and position paper, we take stock of where the field currently stands, delineate opportunities and challenges for future research, and outline steps on how to get material reservoir to the next level. The findings are relevant for beyond CMOS and beyond von Neumann architectures, ML, AI, neuromorphic systems, and computing with novel devices and circuits.


© 2023 Copyright held by the owner/author(s).


This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs International 4.0 License.

DOI 3611315.3633251