On one dimensional chemical diode and frequency generator constructed with an excitable surface reaction

Górecka, J.; Górecki, Jerzy

doi:10.1039/b504621a

Cited by 7 publications

(5 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…are highly nonlinear and show oscillations, excitability and complex spatio-temporal evolution. These phenomena can be used for information processing [60]. Therefore, one can imagine a smart catalyst that, besides its primary function, has the ability to control the conditions under which it operates and sends a warning signal when necessary.…”

Section: Resultsmentioning

confidence: 99%

Chemical computing with reaction–diffusion processes

Górecki

Guzowski

Górecka

et al. 2015

Phil. Trans. R. Soc. A.

Self Cite

View full text Add to dashboard Cite

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 selfgrown 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 lipidcovered 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.

show abstract

Section: Resultsmentioning

confidence: 99%

Chemical computing with reaction–diffusion processes

Górecki

Guzowski

Górecka

et al. 2015

Phil. Trans. R. Soc. A.

Self Cite

View full text Add to dashboard Cite

show abstract

“…The mutual information 40 between all predictors and the output class distribution is 0.93 bit. The analysis of the dataset shows that the mutual information between a pair of predictors and the dataset output reaches its maximum at 0.841 bit for predictors (2,6). Adding the third predictor significantly increases the maximum mutual information.…”

Section: Introductionmentioning

confidence: 99%

“…Adding the third predictor significantly increases the maximum mutual information. It becomes 0.916 bit for the predictor triple (1,2,6). Therefore, these predictors have been used in this paper.…”

Section: Introductionmentioning

confidence: 99%

“…high temperatures, alternative computing strategies can lead to more efficient information processing. 1,2 For instance it is difficult to apply conventional computers at a cellular level in living organisms due to problems such as introduction of electronic components inside the cells, their potential influence on biological processes, electrical energy supply etc. Nevertheless nature has developed computing mechanisms that allow for information processing in cells.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Cancer classification with a network of chemical oscillators

Giżyński

2017

Phys. Chem. Chem. Phys.

View full text Add to dashboard Cite

We discuss chemical information processing considering dataset classifiers formed with a network of interacting droplets. Our arguments are based on computer simulations of droplets in which a photosensitive variant of the Belousov-Zhabotinsky (BZ) reaction proceeds. By applying optical control we can adjust the time evolution of individual droplets and prepare the network to perform a specific computational task. We demonstrate that chemical classifiers made of droplets can be designed in computer simulations based on evolutionary algorithms. The mutual information between the dataset and the observed time evolution of droplets in the network is taken as the fitness function in the optimization process. We show that a classifier of the Wisconsin Breast Cancer Dataset made of a relatively small number of droplets can distinguish between malignant and benign forms of cancer with an accuracy exceeding 97%. The reliability of the optimized chemical classifiers of this dataset as a function of optimization time, number of droplets involved in data processing and the method of extracting the output information is discussed.

show abstract

“…Gorecki et al proposed a technique based on inorganic excitable channels utilizing various patterns of pathways of excitable channels. They constructed diodes (Gorecka and Gorecki, 2005;Gorecka et al, 2007;Igarashi et al, 2008), memory units (Górecki et al, 2009), clock generators (Gorecka and Gorecki, 2005), distance detectors (Bagyan et al, 2005;Górecki et al, 2009), band filter (Górecka and Górecki, 2003), logic gates (Sielewiesiuk and Górecki, 2001), and neuronlike structures (Górecka and Górecki, 2006). Such techniques have a great potential especially due to their universality.…”

Section: Discussionmentioning

confidence: 99%

Advanced Chemical Computing Using Discrete Turing Patterns in Arrays of Coupled Cells

2020

View full text Add to dashboard Cite

We examine dynamical switching among discrete Turing patterns that enable chemical computing performed by mass-coupled reaction cells arranged as arrays with various topological configurations: three coupled cells in a cyclic array, four coupled cells in a linear array, four coupled cells in a cyclic array, and four coupled cells in a branched array. Each cell is operating as a continuous stirred tank reactor, within which the glycolytic reaction takes place, represented by a skeleton inhibitor-activator model where ADP plays the role of activator and ATP is the inhibitor. The mass coupling between cells is assumed to be operating in three possible transport regimes: (i) equal transport coefficients of the inhibitor and activator (ii) slightly faster transport of the activator, and (iii) strongly faster transport of the inhibitor. Each cellular array is characterized by two pairs of tunable parameters, the rate coefficients of the autocatalytic and inhibitory steps, and the transport coefficients of the coupling. Using stability and bifurcation analysis we identified conditions for occurrence of discrete Turing patterns associated with non-uniform stationary states. We found stable symmetric and/or asymmetric discrete Turing patterns coexisting with stable uniform periodic oscillations. To switch from one of the coexisting stable regimes to another we use carefully targeted perturbations, which allows us to build systems of logic gates specific to each topological type of the array, which in turn enables to perform advanced modes of chemical computing. By combining chemical computing techniques in the arrays with glycolytic excitable channels, we propose a cellular assemblage design for advanced chemical computing.

show abstract

On one dimensional chemical diode and frequency generator constructed with an excitable surface reaction

Cited by 7 publications

References 24 publications

Chemical computing with reaction–diffusion processes

Chemical computing with reaction–diffusion processes

Cancer classification with a network of chemical oscillators

Advanced Chemical Computing Using Discrete Turing Patterns in Arrays of Coupled Cells

Contact Info

Product

Resources

About