nano-congress-nano-drug-delivery-2018-posters

Volume 4

Nano Research & Applications

ISSN: 2471-9838

Page 80

JOINT EVENT

August 16-18, 2018 | Dublin, Ireland

Edition of International Conference on

Nanopharmaceutics and Advanced Drug Delivery

Nano Congress for

Future Advancements

Nano Congress 2018

Nano Drug Delivery 2018

August 16-18, 2018

Nano Res Appl 2018, Volume 4

DOI: 10.21767/2471-9838-C3-015

An optically tunable STDP synaptic plasticity memristor based on hybrid organic-inorganic materials

Ayoub Hassan Hamdiyah

University of Hull, UK

emristors are one of the most promising nanoscale candidates’ technologies for future applications in data storage, logic

and neuromorphic computing networks. Modulation of their electronic properties by optical stimuli provides a new

level of functional control, enabling the development of new types of optoelectronic devices and circuits, such as photonic

integrated circuits with memory elements controllable by light. Memristors too have important applications in neuromorphic

computing, and in this context, the dynamic and spatial patterning by light opens the route to new optically configurable

and tunable synaptic circuits. Here, we demonstrate a novel optically controllable organic-inorganic hybrid memristor device

consisting of vertically aligned ZnO nanorods embedded within an optically active polymer, poly (disperse red 1 acrylate)

(PDR1A). Illumination by polarization and wavelength-specific light induces trans-cis photo isomerization of the azobenzene

molecules causing an expansion or contraction of the material, which modifies the resistance of the on/off states, their ratio

and retention times. We demonstrate optical control of short-term and long-term memory and tunable learning through

spike timing dependent (synaptic) plasticity (STDP). We believe this has important applications in the dynamic patterning

of memristor networks, whereby both spatial and temporal patterning via light allows the development of new optically

reconfigurable neural networks, adaptive electronic circuits and hierarchical control of artificial intelligent systems.