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Philos Trans A Math Phys Eng Sci. 2015 Jul 28;373(2046). pii: 20140219. doi: 10.1098/rsta.2014.0219.

Chemical computing with reaction-diffusion processes.

Author information

1
Institute of Physical Chemistry, Polish Academy of Sciences, Kasprzaka 44/52, 01-224 Warsaw, Poland jgorecki@ichf.edu.pl.
2
Institute of Physical Chemistry, Polish Academy of Sciences, Kasprzaka 44/52, 01-224 Warsaw, Poland.
3
Institute of Physics, Polish Academy of Sciences, Aleja Lotnikow 36/42, 02-668 Warsaw, Poland.
4
Department of Mathematics and Computer Science, Friedrich Schiller University Jena, 07743 Jena, Germany.

Abstract

Chemical reactions are responsible for information processing in living organisms. It is believed that the basic features of biological computing activity are reflected by a reaction-diffusion medium. We illustrate the ideas of chemical information processing considering the Belousov-Zhabotinsky (BZ) reaction and its photosensitive variant. The computational universality of information processing is demonstrated. For different methods of information coding constructions of the simplest signal processing devices are described. The function performed by a particular device is determined by the geometrical structure of oscillatory (or of excitable) and non-excitable regions of the medium. In a living organism, the brain is created as a self-grown structure of interacting nonlinear elements and reaches its functionality as the result of learning. We discuss whether such a strategy can be adopted for generation of chemical information processing devices. Recent studies have shown that lipid-covered droplets containing solution of reagents of BZ reaction can be transported by a flowing oil. Therefore, structures of droplets can be spontaneously formed at specific non-equilibrium conditions, for example forced by flows in a microfluidic reactor. We describe how to introduce information to a droplet structure, track the information flow inside it and optimize medium evolution to achieve the maximum reliability. Applications of droplet structures for classification tasks are discussed.

KEYWORDS:

Belousov–Zhabotinsky reaction; evolutionary algorithm; microfuidic reactor; mutual information

PMID:
26078345
DOI:
10.1098/rsta.2014.0219
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