Spiking neurons from tunable Gaussian heterojunction transistors

Autor: Megan E. Beck, Ahish Shylendra, Vinod K. Sangwan, Silu Guo, William A. Gaviria Rojas, Hocheon Yoo, Hadallia Bergeron, Katherine Su, Amit R. Trivedi, Mark C. Hersam
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: Nature Communications, Vol 11, Iss 1, Pp 1-8 (2020)
Druh dokumentu: article
ISSN: 2041-1723
DOI: 10.1038/s41467-020-15378-7
Popis: Designing high performance, scalable, and energy efficient spiking neural networks remains a challenge. Here, the authors utilize mixed-dimensional dual-gated Gaussian heterojunction transistors from single-walled carbon nanotubes and monolayer MoS2 to realize simplified spiking neuron circuits.
Databáze: Directory of Open Access Journals