Developing complexity using networks of synthetic replicators
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Molecular recognition plays an essential role in the self-assembly and self-organisation of biological and chemical systems alike—allowing individual components to form complex interconnected networks. Within these systems, the nature of the recognition and reactive processes determines their functional and structural properties, and even small changes in their identity or orientation can exert a dramatic effect on the observed properties. The rapidly developing field of systems chemistry aims to move away from the established paradigm in which molecules are studied in isolation, towards the study of networks of molecules that interact and react with each other. Taking inspiration from complex natural systems, where recognition processes never operate in isolation, systems chemistry aims to study chemical networks with the view to examining the system-level properties that arise from the interactions and reactions between the components within these systems. The work presented in this thesis aims to advance the nascent field of systems chemistry by bringing together small organic molecules that can react and interact together to form interconnected networks, exhibiting complex behaviour, such as self-replication, as a result. Three simple building blocks are used to construct a network of two structurally similar replicators and their kinetic behaviour is probed through a comprehensive kinetic analysis. The selectivity for one of the recognition-mediated reactive processes over another is examined within the network in isolation as well as in a scenario where the network is embedded within a pool of exchanging components. The interconnected, two-replicator network is examined under far-from-equilibrium reaction-diffusion conditions, showing that chemical replicating networks can exhibit signs of selective replication—a complex phenomenon normally associated with biological systems. Finally, a design of a well-characterised replicator is exploited for the construction of a network integrating self-replication with a another recognition-directed process, leading to the formation of a mechanically-interlocked architecture—a rotaxane.
Thesis, PhD Doctor of Philosophy
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