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Computational elements based on coupled VO2 oscillators via tunable thermal triggering.
Li, Guanmin; Wang, Zhong; Chen, Yuliang; Jeon, Jae-Chun; Parkin, Stuart S P.
Afiliação
  • Li G; Max Planck Institute of Microstructure Physics, Weinberg 2, 06120, Halle (Saale), Germany.
  • Wang Z; Max Planck Institute of Microstructure Physics, Weinberg 2, 06120, Halle (Saale), Germany.
  • Chen Y; Max Planck Institute of Microstructure Physics, Weinberg 2, 06120, Halle (Saale), Germany.
  • Jeon JC; Max Planck Institute of Microstructure Physics, Weinberg 2, 06120, Halle (Saale), Germany. jae-chun.jeon@mpi-halle.mpg.de.
  • Parkin SSP; Max Planck Institute of Microstructure Physics, Weinberg 2, 06120, Halle (Saale), Germany. stuart.parkin@mpi-halle.mpg.de.
Nat Commun ; 15(1): 5820, 2024 Jul 11.
Article em En | MEDLINE | ID: mdl-38987537
ABSTRACT
Computational technologies based on coupled oscillators are of great interest for energy efficient computing. A key to developing such technologies is the tunable control of the interaction among oscillators which today is accomplished by additional electronic components. Here we show that the synchronization of closely spaced vanadium dioxide (VO2) oscillators can be controlled via a simple thermal triggering element that itself is formed from VO2. The net energy consumed by the oscillators is lower during thermal coupling compared with the situation where they are oscillating independently. As the size of the oscillator shrinks from 6 µm to 200 nm both the energy efficiency and the oscillator frequency increases. Based on such oscillators with active tuning, we demonstrate AND, NAND, and NOR logic gates and various firing patterns that mimic the behavior of spiking neurons. Our findings demonstrate an innovative approach towards computational techniques based on networks of thermally coupled oscillators.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article