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George Froudakis
University of Crete
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Efficient machine-learning based approach for the identification of top-performing metal-organic frameworks for CO2 storage
Nanoporous materials and in particular metal–organic frameworks (MOFs) are considered
Presenter
George Froudakis
University of Crete
Carbon Separation and Capture at the Atomistic Level: Theory and Experiment:
Division/Committee: [PHYS] Division of Physical Chemistry
Organizers
Sheng Dai
University of Tennessee
Konstantinos Vogiatzis
University of Tennessee
Presider
George Froudakis
University of Crete
Efficient machine-learning based approach for the identification of top-performing metal-organic frameworks for CO2 storage
Date
March 27, 2023
Nanoporous materials and in particular metal–organic frameworks (MOFs) are considered promising materials for the capture and storage of CO2 due to their exceptional guest-host properties…
Presenter
George Froudakis
University of Crete
Carbon Separation and Capture at the Atomistic Level: Theory and Experiment:
Date
March 27, 2023
DIVISION/COMMITTEE: [PHYS] Division of Physical Chemistry
Organizers
Sheng Dai
University of Tennessee
Konstantinos Vogiatzis
University of Tennessee
Presider
George Froudakis
University of Crete