Brain-Inspired Organic Electronics: Merging Neuromorphic Computing and Bioelectronics Using Conductive Polymers

Imke Krauhausen, Charles-Théophile Coen, Simone Spolaor (Corresponding author), Paschalis Gkoupidenis (Corresponding author), Yoeri B. van de Burgt (Corresponding author)

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Neuromorphic computing offers the opportunity to curtail the huge energy demands of modern artificial intelligence (AI) applications by implementing computations into new, brain-inspired computing architectures. However, the lack of fabrication processes able to integrate several computing units into monolithic systems and the need for new, hardware-tailored training algorithms still limit the scope of application and performance of neuromorphic hardware. Recent advancements in the field of organic transistors present new opportunities for neuromorphic systems and smart sensing applications, thanks to their unique properties such as neuromorphic behavior, low-voltage operation, and mixed ionic-electronic conductivity. Organic neuromorphic transistors push the boundaries of energy efficient brain-inspired hardware AI, facilitating decentralized on-chip learning and serving as a foundation for the advancement of closed-loop intelligent systems in the next generation. The biocompatibility and dual ionic-electronic conductivity of organic materials introduce new prospects for biointegration and bioelectronics. Their ability to sense and regulate biosystems, as well as their neuro-inspired functions can be combined with neuromorphic computing to create the next-generation of bioelectronics. These systems will be able to seamlessly interact with biological systems and locally compute biosignals in a relevant matter.
Original languageEnglish
Article number2307729
Number of pages30
JournalAdvanced Functional Materials
Issue number15
Early online date22 Oct 2023
Publication statusPublished - 10 Apr 2024


I.K., C.‐T.C., and S.S. contributed equally to this work. The authors acknowledged Koen Pieterse and Milan van Wezel from the ICMS Animation Studio for their significant contributions in the design and realization of the illustrations. This work was funded by a joint project between the Max Planck Institute for Polymer Research and the Institute for Complex Molecular Systems (ICMS), Eindhoven University of Technology, grant number MPIPICMS2019001 (to Y.v.d.B., I.K., and P.G.); European Union's Horizon 2020 Research and Innovation Programme, grant agreement no. 802615 (to Y.v.d.B., C.T.C., and S.S.); the Carl‐Zeiss Foundation (to P.G.).

FundersFunder number
Institute for Complex Molecular Systems
Eindhoven University of TechnologyMPIPICMS2019001
Horizon 2020802615
Max Planck Institute for Polymer Research


    • Conductive polymer
    • Brain-inspired computing
    • organic neuromorphic devices
    • organic electrochemical transistor
    • organic bioelectronics
    • neuro-inspired
    • brain-inspired
    • organic neuromorphic computing
    • conductive polymers
    • hardware computing
    • organic electrochemical transistors


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