Organic neuromorphic electronics for learning, sensing and biointerfacing
Paschalis Gkoupidenis a
a Max Planck Institute for Polymer Research, Ackermannweg, 10A, Mainz, Germany
Proceedings of Neuromorphic Materials, Devices, Circuits and Systems (NeuMatDeCaS)
VALÈNCIA, Spain, 2023 January 23rd - 25th
Organizers: Rohit Abraham John, Irem Boybat, Jason Eshraghian and Simone Fabiano
Invited Speaker, Paschalis Gkoupidenis, presentation 017
DOI: https://doi.org/10.29363/nanoge.neumatdecas.2023.017
Publication date: 9th January 2023

Artificial intelligence applications have demonstrated their enormous potential for computation and processing over the last decade. However, they are mainly based on digital operating principles while being part of an analogue world. They also still lack the efficiency and computing capacity of biological systems. Neuromorphic electronics emulate the analogue information processing of biological nervous systems. Neuromorphic electronics based on organic materials have the ability to emulate efficiently and with fidelity a wide range of bio-inspired functions. A prominent example of a neuromorphic device is based on organic mixed conductors (ionic-electronic). Neuromorphic devices based on organic mixed conductors show volatile, non-volatile and tunable dynamics suitable for the emulation of synaptic plasticity and neuronal functions, and for the mapping of artificial neural networks in physical circuits. Finally, organic neuromorphic circuits enable the local sensorimotor control/learning in robotics as well as more efficient and realistic neuroelectronic interfaces.

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