Implementation of Genetic Algorithms to Optimize Metal–Organic Frameworks for CO2 Capture

Pham, Thang D.; Snurr, Randall Q.

doi:10.1021/acs.langmuir.4c04386

Implementation of Genetic Algorithms to Optimize Metal–Organic Frameworks for CO₂ Capture

Journal Article · Thu Feb 13 23:00:00 EST 2025 · Langmuir

DOI:https://doi.org/10.1021/acs.langmuir.4c04386· OSTI ID:2587659

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Northwestern University, Evanston, IL (United States)

Metal-organic frameworks (MOFs) are promising materials for CO₂ capture with the potential to use less energy than current industrial CO₂ capture methods. MOFs are highly versatile sorbents, and there is an almost unlimited number of MOFs that could be synthesized. In this work, we used a genetic algorithm (GA) and grand canonical Monte Carlo (GCMC) simulations to efficiently search for high-performing MOFs for CO₂ capture. We analyzed the effects of important GA parameters, including the mutation probability, the number of MOFs per generation and the number of GA generations, on the GA performance. Here, we performed GCMC simulations on-the-fly during the GA procedure to determine the performance of proposed MOFs and optimized their structures using multiple objective functions across different topologies. The GA was able to determine top-performing MOFs balancing CO₂ selectivity versus working capacity and reduced the cost of molecular simulations by a factor of 25 versus brute-force screening of an entire database of structures.

View Accepted Manuscript (DOE)

Research Organization:: Northwestern University, Evanston, IL (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Basic Energy Sciences (BES). Chemical Sciences, Geosciences & Biosciences Division (CSGB); USDOE Office of Science (SC), Basic Energy Sciences (BES). Scientific User Facilities (SUF); National Energy Research Scientific Computing Center (NERSC)

Grant/Contract Number:: SC0023454; AC02-05CH11231

OSTI ID:: 2587659

Journal Information:: Langmuir, Journal Name: Langmuir Journal Issue: 7 Vol. 41; ISSN 0743-7463; ISSN 1520-5827

Publisher:: American Chemical SocietyCopyright Statement

Country of Publication:: United States

Language:: English

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Implementation of Genetic Algorithms to Optimize Metal–Organic Frameworks for CO2 Capture

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