Kinetic and Thermodynamic Control in Dynamic Covalent Synthesis

Abstract

Dynamic covalent chemistry is an efficient tool for synthesizing complex structures such as molecular cages and covalent organic frameworks. Traditionally, dynamic covalent chemistry was considered to be wholly controlled by thermodynamic factors, but, increasingly, kinetic contributions have been noticed and valued. Complex reaction networks and energy surfaces, as well as contradictory tendencies towards thermodynamic and kinetic control, lead to difficulty in predicting outcomes. Increasingly, researchers are turning to computational models to predict outcomes in dynamic covalent chemistry. In recent years, dynamic covalent chemistry (DCC) has seen the synthesis of increasingly complex cyclooligomers, polymers, and diverse compound libraries. The reversible formation of covalent bonds characteristic of DCC reactions favors thermodynamic product distributions for simple unitopic reactions; however, kinetic effects are increasingly influential in reactions of multitopic precursors. In this review, we explore the interplay between thermodynamic and kinetic considerations when planning a DCC synthesis. Computational models, typically based on reaction thermodynamics, have aided in predicting DCC reaction outcomes with moderate success. A clear direction for the field is to develop more robust computational tools informed by thermodynamic and kinetic driving forces that can predict product distributions in DCC reactions. In recent years, dynamic covalent chemistry (DCC) has seen the synthesis of increasingly complex cyclooligomers, polymers, and diverse compound libraries. The reversible formation of covalent bonds characteristic of DCC reactions favors thermodynamic product distributions for simple unitopic reactions; however, kinetic effects are increasingly influential in reactions of multitopic precursors. In this review, we explore the interplay between thermodynamic and kinetic considerations when planning a DCC synthesis. Computational models, typically based on reaction thermodynamics, have aided in predicting DCC reaction outcomes with moderate success. A clear direction for the field is to develop more robust computational tools informed by thermodynamic and kinetic driving forces that can predict product distributions in DCC reactions. a defined sequence of computational tasks that produces a desired outcome. a reaction that converts monomers to macrocycles with a finite number of components. a computational method used to model the electron density clouds of atoms and molecules in order to investigate their electronic and nuclear structure and predict their energies. a synthetic strategy typically utilizing reversible covalent bonds and multitopic precursors in order to synthesize networks, cages, and other architectures that would be difficult or impossible to synthesize in a stepwise manner. precursors designed to form a variety of different species via reversible covalent bonds are mixed to study the resulting product distribution and its response to perturbation. the concentration of all species is constant because the forward and reverse reactions are proceeding at equal rates. The system is at a thermodynamic minimum. the breakage of a bond that is incompatible with the system’s intended product. This process is vital for the synthesis of complex architectures by DCC. the outcome of the reaction is primarily determined by which product is formed at the fastest rate and has the lowest activation energy of its formation, generally observed when the reaction is irreversible. a type of computational algorithm that uses repeated random sampling and subsequent statistical analysis to obtain results for values that would otherwise be difficult to predict. a precursor with multiple reactive sites that forms multiple bonds in the course of the reaction or synthesis. cavities are present in a molecule or material that does not collapse when the original hosts of the cavity (generally solvent molecules) are removed. the total set of reactants, products, and intermediates in a system and all the reactions that transform one into another. a reaction is reversible if the products react to reform starting material on an reasonable laboratory timescale. a model is defined by a set of rules repeatedly applied to progressive reaction conditions, allowing a complex model to be generated without specifying the system in its entirety. noncovalent interactions between molecules. the outcome of the reaction is primarily determined by which product is lowest in energy, generally observed when the reaction is reversible. Despite the rapid formation of the kinetic product, the thermodynamic product accumulates over time in a reversible reaction because the reverse reaction is slower for a more stable product.