Mimicking the brain using SnOx nanoparticles

Researchers from the School of Engineering & the School of Science (Dr Phoung Le & Dr Jim Partridge) have used a suite of surface-sensitive techniques (SEM, XPS, AFM) to investigate the formation of artificial neural networks from memristive SnOx nanoparticles.

The recurrent electrical connections and dynamic resistive switching properties allow the nanoparticle networks to be used as a reservoir computer – an emerging, low-computational cost technique for cognitive temporal/sequential data processing.

Le, P.Y., Murdoch, B.J., Barlow, A.J., Holland, A.S., McCulloch, D.G., McConville, C.F. and Partridge, J.G., Electroformed, Self‐Connected Tin Oxide Nanoparticle Networks for Electronic Reservoir Computing. Advanced Electronic Materials, p.2000081.

https://doi.org/10.1002/aelm.202000081    

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torres strait flag

Acknowledgement of country

RMIT University acknowledges the people of the Woi wurrung and Boon wurrung language groups of the eastern Kulin Nation on whose unceded lands we conduct the business of the University. RMIT University respectfully acknowledges their Ancestors and Elders, past and present. RMIT also acknowledges the Traditional Custodians and their Ancestors of the lands and waters across Australia where we conduct our business.