(305c) Application of Classical DFT for Screening of MOFs for CO2 Capture

Application
of Classical DFT for Screening of MOFs for CO₂ Capture

Yun
Tian, Jia Fu, Shijie Sheng and Jianzhong Wu

Department
of Chemical and Environmental Engineering, University of California, Riverside,
California 92521, USA

ABSTRACT

Due to the widespread public
concern of increasing CO₂ emission in the atmosphere, CO₂
capture has been one of the most urgent issues. With the large gas adsorption
capacity and tunable structural properties of MOFs, numerous computational
efforts have been dedicated in recent years to examine the performance of MOFs
for carbon capture and sequestration from different gas mixtures. Compared with
adsorption of LJ fluids (e.g. noble gases, hydrogen and methane) with no charge
interactions with MOFs, the long-range Coulombic interactions are crucial for
CO₂. Despite various methods for extracting atomic charges from the
results of quantum mechanical (QM) calculations, performing the GCMC explicitly
dealing with long-range Coulombic interactions at each step of simulation for
thousands or even millions of MOFs may not be feasible.

To achieve the high-throughput
screening of MOFs for CO₂ adsorption, we apply the classical density
functional theory (DFT) combined with MHNC-RISM to efficiently solve for the
site direct correlation functions as the input for DFT calculation. DFT methods
have been proven to be much more efficient than simulations in the material
screening for hydrogen and methane storage in MOFs with comparable accuracy
with GCMC. Within the framework of site-DFT calculations developed for
solvation, the long-range electrostatic interaction with full Ewald treatment
will only need to be considered once for each material at zero loading, which
will be much more efficient than the conventional GCMC calculations. In
combination of semi-empirical schemes for the assignment of partial charges and
molecular force fields, the computational efficiency of classical DFT makes it
a promising tool for design of new MOFs in application to CO₂
capture.