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Controlling Chemical Chaos in the Belousov-Zhabotinsky Oscillator

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Artificial Life and Evolutionary Computation (WIVACE 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 830))

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Abstract

Chaos is ubiquitous in Nature and represents one of the most fascinating expressions of real world complexity. Depending on the specific context, the onset of chaotic behaviours can be undesirable, thus, controlling the mechanisms at the basis of chaotic dynamics represents a cutting-edge challenge in many areas, including cardiology, information processing, hydrodynamics and optics, to name a few. In this work we review our recent results showing how, in chemical reactions, the active interplay between a nonlinear kinetics and hydrodynamic instabilities can be exploited as a general mechanism to induce and control chemical chaos. To this end, we consider as a model system the Belousov-Zhabotinsky (BZ) reaction. Thanks to a chemo-hydrodynamic coupling, the reaction can undergo chaotic oscillations when carried out in batch conditions. Chaos appears and disappears by following Ruelle-Takens-Newhouse scenario both in the cerium- and ferroin-catalyzed BZ systems. Here, we present experimental evidence that the transition to chemical chaos can be directly controlled by tuning either kinetic or hydrodynamic parameters of the system. Experiments were simulated by using a reaction-diffusion-convection (RDC) model where the nonlinear reaction kinetics are coupled to the Navier-Stokes equations. Numerical solutions of the RDC model clearly indicate that natural convection can feedback on the spatio-temporal evolution of the concentration fields and, in turn, changes bulk oscillation patterns. Distinct bifurcations in the oscillation patterns are found when the Grashof numbers (governing the entity of convective flows into the system) and the diffusion coefficients of the chemical species are varied. The consumption of the initial reagents is also found to be a critical phenomenon able to modulate the strength of the RDC coupling and drive order-disorder transitions.

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Acknowledgments

FR gratefully acknowledges the University of Salerno for the grants ORSA158121 and ORSA167988. MAB and MR acknowledge financial support from Fondazione Banco di Sardegna.

Author information

Authors and Affiliations

  1. Dipartimento di Chimica e Farmacia, Università di Sassari, Via Vienna 2, 07100, Sassari, Italy

    Marcello A. Budroni & Mauro Rustici

  2. Department of Earth, Environmental and Physical Sciences - DEEP Sciences, University of Siena, Siena, Italy

    Nadia Marchettini

  3. Department of Chemistry and Biology “A. Zambelli”, University of Salerno, Fisciano, Italy

    Federico Rossi

Authors
  1. Marcello A. Budroni
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  2. Mauro Rustici
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  3. Nadia Marchettini
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  4. Federico Rossi
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Corresponding author

Correspondence to Marcello A. Budroni .

Editor information

Editors and Affiliations

  1. Ca’ Foscari University of Venice, Venice, Italy

    Marcello Pelillo

  2. Ca’ Foscari University of Venice, Venice, Italy

    Irene Poli

  3. University of Bologna, Cesena, Italy

    Andrea Roli

  4. University of Modena and Reggio Emilia, Modena, Italy

    Roberto Serra

  5. Ca’ Foscari University of Venice, Venice, Italy

    Debora Slanzi

  6. University of Modena and Reggio Emilia, Modena, Italy

    Marco Villani

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Budroni, M.A., Rustici, M., Marchettini, N., Rossi, F. (2018). Controlling Chemical Chaos in the Belousov-Zhabotinsky Oscillator. In: Pelillo, M., Poli, I., Roli, A., Serra, R., Slanzi, D., Villani, M. (eds) Artificial Life and Evolutionary Computation. WIVACE 2017. Communications in Computer and Information Science, vol 830. Springer, Cham. https://doi.org/10.1007/978-3-319-78658-2_3

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  • DOI: https://doi.org/10.1007/978-3-319-78658-2_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-78657-5

  • Online ISBN: 978-3-319-78658-2

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