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Optimising Weakly Connected Chemical Oscillators in a Hybrid Digital-Chemical Platform via Generative AI Surrogate
Juan Manuel Parrilla Gutierrez1, Abhishek Sharma2, Soichiro Tsuda3
1Glasgow Caledonian University School of Science and Engineering The University of Glasgow School of Chemistry juanma.parrilla@gcu.ac.uk.
Artificial Life
|July 28, 2026
Summary
Researchers developed a 3D-printed platform using the Belousov-Zhabotinsky (BZ) reaction for chemical computation. This novel system, enhanced by Generative AI, demonstrates potential for advanced Artificial Life applications.
Area of Science:
- Chemical Engineering
- Computational Science
- Artificial Life
Background:
- The Belousov-Zhabotinsky (BZ) reaction exhibits oscillatory dynamics, mimicking binary states relevant to digital electronics.
- Interconnected chemical systems offer potential for novel computational paradigms beyond traditional silicon-based electronics.
Purpose of the Study:
- To present a 3D-printed platform integrating the BZ reaction for heterotic computations.
- To demonstrate the simulation of logic gates (AND, OR, XOR) using this platform.
- To explore the use of Generative AI and Genetic Algorithms for optimizing chemical computation.
Main Methods:
- Fabrication of a 3D-printed platform with an array of interconnected cells containing the BZ reaction.
- Individual magnetic stirring within cells to control local BZ oscillations.
- Simulation of logic gates by controlling oscillation propagation.
- Development of a Generative AI surrogate model combined with a Genetic Algorithm for optimization.
Main Results:
- Successful simulation of "AND", "OR", and "XOR" logic gates using the 3D-printed BZ reaction platform.
- Demonstration of heterotic computation through collective oscillatory dynamics.
- Validation of Generative AI as an effective in-silico surrogate for optimizing the platform's behavior.
Conclusions:
- The study provides a proof of concept for hybrid digital-chemical platforms combined with Generative AI for unconventional computation.
- This approach shows potential for enhancing Artificial Life implementations.
- The developed platform offers a novel avenue for exploring complex computational systems.
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