Angewandte Chemie International Edition · 2013 · 627 citations · 105 references
Natural SciencesChemistryChemical KineticsComplex SystemsDynamical SystemsChemical EquilibriumChemical EvolutionChemical ReactionsNetwork DynamicsNetwork TheoryReaction DynamicsAdaptive SystemsAntagonistic InteractionsComplexityComponent SelectionDynamic Systems ApproachStates Of Matter ModelsSystems ChemistryWeighted Networks
Chemistry is increasingly exploring how matter evolves toward higher complexity through self‑organization driven by information, progressing from molecular to supramolecular to adaptive chemistry via constitutional dynamics that enable component selection in equilibrating sets. The study aims to develop adaptive chemical systems capable of higher‑level functions such as training, learning, and decision making. Dynamic systems are modeled as weighted networks that capture agonistic and antagonistic interactions among constituents, with network states switched by amplifying the best‑adapted constituents.
Abstract Chemistry is progressively unraveling the processes that underlie the evolution of matter towards states of higher complexity and the generation of novel features along the way by self‐organization under the pressure of information. Chemistry has evolved from molecular to supramolecular to become adaptive chemistry by way of constitutional dynamics, which allow for adaptation, through component selection in an equilibrating set. Dynamic systems can be represented by weighted dynamic networks that define the agonistic and antagonistic relationships between the different constituents linked through component exchange. Such networks can be switched through amplification/up‐regulation of the best adapted/fittest constituent(s) in a dynamic set. Accessing higher level functions such as training, learning, and decision making represent future lines of development for adaptive chemical systems.
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