Unknown

Dataset Information

Understanding CO adsorption in MOFs combining atomic simulations and machine learning.


ABSTRACT: This study introduces a computational method integrating molecular simulations and machine learning (ML) to assess the CO adsorption capacities of synthesized and hypothetical metal-organic frameworks (MOFs) at various pressures. After extracting structural, chemical, and energy-based features of the synthesized and hypothetical MOFs (hMOFs), we conducted molecular simulations to compute CO adsorption in synthesized MOFs and used these simulation results to train ML models for predicting CO adsorption in hMOFs. Results showed that CO uptakes of synthesized MOFs and hMOFs are between 0.02-2.28 mol/kg and 0.45-3.06 mol/kg, respectively, at 1 bar, 298 K. At low pressures (0.1 and 1 bar), Henry's constant of CO is the most dominant feature, whereas structural properties such as surface area an

SUBMITTER: Ercakir G 

PROVIDER: S-EPMC11496673 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature