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A programmable chemical computer with memory and pattern recognition

Author

Listed:
  • Juan Manuel Parrilla-Gutierrez

    (University of Glasgow)

  • Abhishek Sharma

    (University of Glasgow)

  • Soichiro Tsuda

    (University of Glasgow)

  • Geoffrey J. T. Cooper

    (University of Glasgow)

  • Gerardo Aragon-Camarasa

    (University of Glasgow)

  • Kevin Donkers

    (University of Glasgow)

  • Leroy Cronin

    (University of Glasgow)

Abstract

Current computers are limited by the von Neumann bottleneck, which constrains the throughput between the processing unit and the memory. Chemical processes have the potential to scale beyond current computing architectures as the processing unit and memory reside in the same space, performing computations through chemical reactions, yet their lack of programmability limits them. Herein, we present a programmable chemical processor comprising of a 5 by 5 array of cells filled with a switchable oscillating chemical (Belousov–Zhabotinsky) reaction. Each cell can be individually addressed in the ‘on’ or ‘off’ state, yielding more than 2.9 × 1017 chemical states which arise from the ability to detect distinct amplitudes of oscillations via image processing. By programming the array of interconnected BZ reactions we demonstrate chemically encoded and addressable memory, and we create a chemical Autoencoder for pattern recognition able to perform the equivalent of one million operations per second.

Suggested Citation

  • Juan Manuel Parrilla-Gutierrez & Abhishek Sharma & Soichiro Tsuda & Geoffrey J. T. Cooper & Gerardo Aragon-Camarasa & Kevin Donkers & Leroy Cronin, 2020. "A programmable chemical computer with memory and pattern recognition," Nature Communications, Nature, vol. 11(1), pages 1-8, December.
    • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-15190-3
    DOI: 10.1038/s41467-020-15190-3
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    Citations

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    Cited by:

    1. Karimov, Artur & Kopets, Ekaterina & Karimov, Timur & Almjasheva, Oksana & Arlyapov, Viacheslav & Butusov, Denis, 2023. "Empirically developed model of the stirring-controlled Belousov–Zhabotinsky reaction," Chaos, Solitons & Fractals, Elsevier, vol. 176(C).
    2. Dmitrii V. Kriukov & Jurriaan Huskens & Albert S. Y. Wong, 2024. "Exploring the programmability of autocatalytic chemical reaction networks," Nature Communications, Nature, vol. 15(1), pages 1-8, December.
    3. Maćešić, Stevan & Čupić, Željko & Kolar-Anić, Ljiljana, 2023. "Effect of diffusion on steady state stability of an oscillatory reaction model," Chaos, Solitons & Fractals, Elsevier, vol. 174(C).
    4. Fabian Schnitter & Benedikt Rieß & Christian Jandl & Job Boekhoven, 2022. "Memory, switches, and an OR-port through bistability in chemically fueled crystals," Nature Communications, Nature, vol. 13(1), pages 1-8, December.
    5. Ahmed A. Agiza & Kady Oakley & Jacob K. Rosenstein & Brenda M. Rubenstein & Eunsuk Kim & Marc Riedel & Sherief Reda, 2023. "Digital circuits and neural networks based on acid-base chemistry implemented by robotic fluid handling," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
    6. Abhishek Sharma & Marcus Tze-Kiat Ng & Juan Manuel Parrilla Gutierrez & Yibin Jiang & Leroy Cronin, 2024. "A programmable hybrid digital chemical information processor based on the Belousov-Zhabotinsky reaction," Nature Communications, Nature, vol. 15(1), pages 1-10, December.

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