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Challenges of Complexity in Chemistry and Beyond

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Complexity in Chemistry and Beyond: Interplay Theory and Experiment

Abstract

The theory of complex dynamical systems is an interdisciplinary methodology to model nonlinear processes in nature and society. In the age of globalization, it is the answer to increasing complexity and sensitivity of human life and civilization (e.g., life science, environment and climate, globalization, information flood). Complex systems consist of many microscopic elements (molecules, cells, organisms, agents, citizens) interacting in nonlinear manner and generating macroscopic order. Self-organization means the emergence of macroscopic states by the nonlinear interactions of microscopic elements. Chemistry at the boundary between physics and biology analyzes the fascinating world of molecular self-organization. Supramolecular chemistry describes the emergence of extremely complex molecules during chemical evolution on Earth. Chaos and randomness, growth and innovations are examples of macroscopic states modeled by phase transitions in critical states. The models aim at explaining and forecasting their dynamics. Information dynamics is an important topic to understand molecular self-organization. In the case of randomness and chaos, there are restrictions to compute the macrodynamics of complex systems, even if we know all laws and conditions of their local activities. Future cannot be forecast in the long run, but dynamical trends (e.g., order parameters) can be recognized and influenced (“bounded rationality”). Besides the methodology of mathematical and computer-assisted models, there are practical and ethical consequences: Be sensible to critical equilibria in nature and society (butterfly effect). Find the balance between self-organization, control, and governance of complex systems in order to support a sustainable future of mankind.

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Notes

  1. 1.

    Interesting in this context is that nonlinear chemical, dissipative mechanisms (distinguished from those of a physical origin) have been proposed as providing a possible underlying process for some aspects of biological self-organization and morphogenesis. Nonlinearities during the formation of microtubular solutions are reported to result in a chemical instability and bifurcation between pathways leading to macroscopically self-organized states of different morphology (Tabony, J. Science, 1994, 264, 245).

  2. 2.

    Defects, in general—not only those related to the surface—affect the physical and chemical (e.g., catalytical) properties of a solid and play a role in its history. They form the basis of its possible complex behaviour.

  3. 3.

    Fluctuation—static or nonstatic, equilibrium or nonequilibrium—usually means the deviation of some quantity from its mean or most probable value. (They played a key role in the evolution.) Most of the quantities that might be interesting for study exhibit fluctuations, at least on a microscopic level. Fluctuations of macroscopic quantities manifest themselves in several ways. They may limit the precision of measurements of the mean value of the quantity, or vice versa, the identification of the fluctuation may be limited by the precision of the measurement. They are the cause of some familiar features of our surroundings, or they may cause spectacular effects, such as the critical opalescence and they play a key role in the nucleation phase of crystal growth (see Sect. 1.8). Fluctuations or their basic principles which are relevant for chemistry have never been discussed on a general basis, though they are very common—for example in the form of some characteristic properties of the very large metal clusters and colloids.

  4. 4.

    During cosmological, chemical, biological, as well as social and cultural evolution, information increased parallel to the generation of structures of higher complexity. The emergence of relevant information during the different stages of evolution is comparable with phase transitions during which structure forms from unordered systems (with concomitant entropy export). Although we can model certain collective features in natural and social sciences by the complex dynamics of phase transitions, we have to pay attention to important differences (see Sect. 1.6).

    In principle, any piece of information can be encoded by a sequence of zeros and ones, a so-called {0,1}-sequence. Its (Kolmogorov) complexity can thus be defined as the length of the minimal {0,1}-sequence in which all that is needed for its reconstruction is included (though, according to well-known undecidability theorems, there is in general no algorithm to check whether a given sequence with such a property is of minimal length). According to the broader definition by C.F. von Weizsäcker, information is a concept intended to provide a scale for measuring the amount of form encountered in a system, a structural unit, or any other information-carrying entity (“Information ist das Maßeiner Menge von Form”). There exists, of course, a great variety of other definitions of information which have been introduced within different theoretical contexts and which relate to different scientific disciplines. Philosophically speaking, a qualitative concept is needed which considers information to be a property neither of structure nor of function alone, but of that inseparable unit called form, which mediates between both.

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Authors and Affiliations

  1. Lehrstuhl für Philosophie und Wissenschaftstheorie, Munich Center for Technology in Society (MCTS), Technische Universität München, Arcisstrasse 21, D-80333, Munich, Germany

    Klaus Mainzer

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Correspondence to Klaus Mainzer .

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  1. Department of Chemistry, Emory University, Atlanta, Georgia, USA

    Craig Hill  & Djamaladdin G. Musaev  & 

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Mainzer, K. (2012). Challenges of Complexity in Chemistry and Beyond. In: Hill, C., Musaev, D.G. (eds) Complexity in Chemistry and Beyond: Interplay Theory and Experiment. NATO Science for Peace and Security Series B: Physics and Biophysics. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-5548-2_1

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