Materials design by evolutionary optimization of functional groups in metal-organic frameworks

A genetic algorithm that efficiently optimizes a desired physical or functional property in metal-organic frameworks (MOFs) by evolving the functional groups within the pores has been developed. The approach has been used to optimize the CO(2) uptake capacity of 141 experimentally characterized MOFs under conditions relevant for postcombustion CO(2) capture. A total search space of 1.65 trillion structures was screened, and 1035 derivatives of 23 different parent MOFs were identified as having exceptional CO(2) uptakes of >3.0 mmol/g (at 0.15 atm and 298 K). Many well-known MOF platforms were optimized, with some, such as MIL-47, having their CO(2) adsorption increase by more than 400%. The structures of the high-performing MOFs are provided as potential targets for synthesis.