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

ABSTRACT: 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 CO₂ uptake capacity of 141 experimentally characterized MOFs under conditions relevant for postcombustion CO₂ 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 CO₂ 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 CO₂ adsorption increase by more than 400%. The structures of the high-performing MOFs are provided as potential targets for synthesis.

SUBMITTER: Collins SP

PROVIDER: S-EPMC5262444 | biostudies-literature | 2016 Nov

REPOSITORIES: biostudies-literature

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

Collins Sean P SP Daff Thomas D TD Piotrkowski Sarah S SS Woo Tom K TK

Science advances 20161123 11

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<sub>2</sub> uptake capacity of 141 experimentally characterized MOFs under conditions relevant for postcombustion CO<sub>2</sub> capture. A total search space of 1.65 trillion structures was screened, and 1035 derivatives of 23 different parent MOFs were iden ...[more]

PMID: 28138523

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