Elucidating CO 2 Dynamics in High-Entropy MOF-74 via Machine Learning Interatomic Potentials

Key Points

• The aim is to investigate whether homogeneous metal mixing in high-entropy MOF-74 enhances CO2 transport dynamics compared to single metal variants.
• Utilized machine learning to develop interatomic potentials for MOF-74 materials.
• Analyzed CO2 adsorption performance across various high-entropy MOF-74 variants.
• Compared the transport dynamics with single metal counterparts.
• Observed significant improvement in CO2 adsorption performance in high-entropy variants.
• Found that metal mixing provides intrinsic enhancements in transport properties beyond single metal behaviors.
• Highlighted that the machine learning model accurately predicts interatomic interactions.