A Drive towards Thermodynamic Efficiency for Dissipative Structures in Chemical Reaction Networks
Dissipative accounts of structure formation show that the self-organisation of complex structures is thermodynamically favoured, whenever these structures dissipate free energy that could not be accessed otherwise. These structures therefore open transition channels for the state of the universe to...
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doaj-1d29b20e77c4490fac7bcae9f11d45d72021-09-26T00:06:34ZengMDPI AGEntropy1099-43002021-08-01231115111510.3390/e23091115A Drive towards Thermodynamic Efficiency for Dissipative Structures in Chemical Reaction NetworksKai Ueltzhöffer0Lancelot Da Costa1Daniela Cialfi2Karl Friston3Wellcome Centre for Human Neuroimaging, Queen Square Institute of Neurology, University College London, London WC1N 3AR, UKWellcome Centre for Human Neuroimaging, Queen Square Institute of Neurology, University College London, London WC1N 3AR, UKDepartment of Philosophical, Pedagogical and Economic-Quantitative Sciences, Economic and Quantitative Methods Section, University of Studies Gabriele d’Annunzio Chieti-Pescara, 65127 Pescara, ItalyWellcome Centre for Human Neuroimaging, Queen Square Institute of Neurology, University College London, London WC1N 3AR, UKDissipative accounts of structure formation show that the self-organisation of complex structures is thermodynamically favoured, whenever these structures dissipate free energy that could not be accessed otherwise. These structures therefore open transition channels for the state of the universe to move from a frustrated, metastable state to another metastable state of higher entropy. However, these accounts apply as well to relatively simple, dissipative systems, such as convection cells, hurricanes, candle flames, lightning strikes, or mechanical cracks, as they do to complex biological systems. Conversely, interesting computational properties—that characterize complex biological systems, such as efficient, predictive representations of environmental dynamics—can be linked to the thermodynamic efficiency of underlying physical processes. However, the potential mechanisms that underwrite the selection of dissipative structures with thermodynamically efficient subprocesses is not completely understood. We address these mechanisms by explaining how bifurcation-based, work-harvesting processes—required to sustain complex dissipative structures—might be driven towards thermodynamic efficiency. We first demonstrate a simple mechanism that leads to self-selection of efficient dissipative structures in a stochastic chemical reaction network, when the dissipated driving chemical potential difference is decreased. We then discuss how such a drive can emerge naturally in a hierarchy of self-similar dissipative structures, each feeding on the dissipative structures of a previous level, when moving away from the initial, driving disequilibrium.https://www.mdpi.com/1099-4300/23/9/1115stochastic thermodynamicsdissipative structuresthermodynamic efficiencychemical reaction networks |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Kai Ueltzhöffer Lancelot Da Costa Daniela Cialfi Karl Friston |
spellingShingle |
Kai Ueltzhöffer Lancelot Da Costa Daniela Cialfi Karl Friston A Drive towards Thermodynamic Efficiency for Dissipative Structures in Chemical Reaction Networks Entropy stochastic thermodynamics dissipative structures thermodynamic efficiency chemical reaction networks |
author_facet |
Kai Ueltzhöffer Lancelot Da Costa Daniela Cialfi Karl Friston |
author_sort |
Kai Ueltzhöffer |
title |
A Drive towards Thermodynamic Efficiency for Dissipative Structures in Chemical Reaction Networks |
title_short |
A Drive towards Thermodynamic Efficiency for Dissipative Structures in Chemical Reaction Networks |
title_full |
A Drive towards Thermodynamic Efficiency for Dissipative Structures in Chemical Reaction Networks |
title_fullStr |
A Drive towards Thermodynamic Efficiency for Dissipative Structures in Chemical Reaction Networks |
title_full_unstemmed |
A Drive towards Thermodynamic Efficiency for Dissipative Structures in Chemical Reaction Networks |
title_sort |
drive towards thermodynamic efficiency for dissipative structures in chemical reaction networks |
publisher |
MDPI AG |
series |
Entropy |
issn |
1099-4300 |
publishDate |
2021-08-01 |
description |
Dissipative accounts of structure formation show that the self-organisation of complex structures is thermodynamically favoured, whenever these structures dissipate free energy that could not be accessed otherwise. These structures therefore open transition channels for the state of the universe to move from a frustrated, metastable state to another metastable state of higher entropy. However, these accounts apply as well to relatively simple, dissipative systems, such as convection cells, hurricanes, candle flames, lightning strikes, or mechanical cracks, as they do to complex biological systems. Conversely, interesting computational properties—that characterize complex biological systems, such as efficient, predictive representations of environmental dynamics—can be linked to the thermodynamic efficiency of underlying physical processes. However, the potential mechanisms that underwrite the selection of dissipative structures with thermodynamically efficient subprocesses is not completely understood. We address these mechanisms by explaining how bifurcation-based, work-harvesting processes—required to sustain complex dissipative structures—might be driven towards thermodynamic efficiency. We first demonstrate a simple mechanism that leads to self-selection of efficient dissipative structures in a stochastic chemical reaction network, when the dissipated driving chemical potential difference is decreased. We then discuss how such a drive can emerge naturally in a hierarchy of self-similar dissipative structures, each feeding on the dissipative structures of a previous level, when moving away from the initial, driving disequilibrium. |
topic |
stochastic thermodynamics dissipative structures thermodynamic efficiency chemical reaction networks |
url |
https://www.mdpi.com/1099-4300/23/9/1115 |
work_keys_str_mv |
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1717367003953496064 |