Artificial Synapses: Low‐Power, Electrochemically Tunable Graphene Synapses for Neuromorphic Computing (Adv. Mater. 36/2018). Issue 36 (3rd September 2018)

• Record Type: Journal Article
• Authors: Sharbati, Mohammad Taghi; Du, Yanhao; Torres, Jorge; Ardolino, Nolan D.; Yun, Minhee; Xiong, Feng
• Is Part Of: Advanced materials. Volume 30:Issue 36(2018)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2018-09-03
• Subjects: artificial synapse -- electrochemical intercalation -- graphene -- neuromorphic computing; Materials -- Periodicals; Chemical vapor deposition -- Periodicals; 620.11
• DOI: 10.1002/adma.201870273
• Languages: English
• ISSNs: 0935-9648

Abstract

Abstract : By reversibly intercalating ions between the layers of two‐dimensional graphene, Feng Xiong and co‐workers at Pitt develop a novel artificial synapse for neuromorphic computing, as described in article number1802353 . With over 250 tunable analog states, good energy efficiency, and promising scalability, these electrochemical synapses can lead to the hardware implementation of neural networks and hence the prevalent use of artificial intelligence.