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Sustainable memristors from shiitake mycelium for high-frequency bioelectronics

Author

Listed:
  • John LaRocco
  • Qudsia Tahmina
  • Ruben Petreaca
  • John Simonis
  • Justin Hill

Abstract

Neuromorphic computing, inspired by the structure of the brain, offers advantages in parallel processing, memory storage, and energy efficiency. However, current semiconductor-based neuromorphic chips require rare-earth materials and costly fabrication processes, whereas neural organoids need complex bioreactor maintenance. In this study, we explored shiitake (Lentinula edodes) fungi as a robust, sustainable alternative, exploiting its adaptive electrical signaling, which is akin to neuronal spiking. We demonstrate fungal computing via mycelial networks interfaced with electrodes, showing that fungal memristors can be grown, trained, and preserved through dehydration, retaining functionality at frequencies up to 5.85 kHz, with an accuracy of 90 ± 1%. Notably, shiitake has exhibited radiation resistance, suggesting its viability for aerospace applications. Our findings show that fungal computers can provide scalable, eco-friendly platforms for neuromorphic tasks, bridging bioelectronics and unconventional computing.

Suggested Citation

  • John LaRocco & Qudsia Tahmina & Ruben Petreaca & John Simonis & Justin Hill, 2025. "Sustainable memristors from shiitake mycelium for high-frequency bioelectronics," PLOS ONE, Public Library of Science, vol. 20(10), pages 1-19, October.
    • Handle: RePEc:plo:pone00:0328965
    DOI: 10.1371/journal.pone.0328965
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    References listed on IDEAS

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    1. Can Li & Lili Han & Hao Jiang & Moon-Hyung Jang & Peng Lin & Qing Wu & Mark Barnell & J. Joshua Yang & Huolin L. Xin & Qiangfei Xia, 2017. "Three-dimensional crossbar arrays of self-rectifying Si/SiO2/Si memristors," Nature Communications, Nature, vol. 8(1), pages 1-9, August.
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