TY - JOUR
T1 - Screening and preparation of functionalized TpBD-COFs for CO2 capture
AU - Qu, Qinghua
AU - Jiang, Yuqiao
AU - Cheng, Linyan
AU - Xue, Qingyuan
AU - Li, Ranran
AU - Fang, Cheng
AU - Li, Hongping
AU - Ding, Jing
AU - Wan, Hui
AU - Guan, Guofeng
N1 - Publisher Copyright:
© 2024
PY - 2025/1/5
Y1 - 2025/1/5
N2 - Covalent organic frameworks (COFs) with high specific surface area, ordered pore wall, modified porous surface and customizable chemical structure have been widely used in CO2 capture. However, the screening of functionalized COFs suitable for CO2 capture still relies on experiments, which will require a long experimental period with blindness and randomness. Herein, we chosed three electron withdrawing groups (–NO2, –CN and −Br) and three electron donating groups (–CH2NH2, –CH3, –OCH3) to explore the effect of electron withdrawing ability of functional groups on the CO2 adsorption capacity. Grand canonical Monte Carlo (GCMC) method was used to simulate the adsorption capacity of CO2 over X-TpBD-COFs (X=–NO2, –CN, −Br, –CH2NH2, –CH3, –OCH3). As the result, NO2-TpBD-COF had the highest adsorption capacity among the six functionalized X-TpBD-COFs at 100 kPa and 25 ℃ (49.37 cm3/g), while OCH3-TpBD-COF had the lowest adsorption capacity among them (23.51 cm3/g at 25 ℃ and 100 kPa). The order of binding energy was basically the same as the order of adsorption capacity when the synergistic interactions between functional groups and oxygen atoms in Tp were considered according to density functional theory (DFT). Molecular dynamics (MD) showed that the diffusion and distribution of CO2 were mainly effected by pore structures. To verify the simulation results, NO2-TpBD-COF and OCH3-TpBD-COF were successfully prepared by solvothermal method. The CO2 adsorption capacities of these two COFs were basically consistent with the conclusion obtained by the simulations. This study provided a way for simulation to guide accurate and rapid experimental design of COF materials for CO2 capture.
AB - Covalent organic frameworks (COFs) with high specific surface area, ordered pore wall, modified porous surface and customizable chemical structure have been widely used in CO2 capture. However, the screening of functionalized COFs suitable for CO2 capture still relies on experiments, which will require a long experimental period with blindness and randomness. Herein, we chosed three electron withdrawing groups (–NO2, –CN and −Br) and three electron donating groups (–CH2NH2, –CH3, –OCH3) to explore the effect of electron withdrawing ability of functional groups on the CO2 adsorption capacity. Grand canonical Monte Carlo (GCMC) method was used to simulate the adsorption capacity of CO2 over X-TpBD-COFs (X=–NO2, –CN, −Br, –CH2NH2, –CH3, –OCH3). As the result, NO2-TpBD-COF had the highest adsorption capacity among the six functionalized X-TpBD-COFs at 100 kPa and 25 ℃ (49.37 cm3/g), while OCH3-TpBD-COF had the lowest adsorption capacity among them (23.51 cm3/g at 25 ℃ and 100 kPa). The order of binding energy was basically the same as the order of adsorption capacity when the synergistic interactions between functional groups and oxygen atoms in Tp were considered according to density functional theory (DFT). Molecular dynamics (MD) showed that the diffusion and distribution of CO2 were mainly effected by pore structures. To verify the simulation results, NO2-TpBD-COF and OCH3-TpBD-COF were successfully prepared by solvothermal method. The CO2 adsorption capacities of these two COFs were basically consistent with the conclusion obtained by the simulations. This study provided a way for simulation to guide accurate and rapid experimental design of COF materials for CO2 capture.
KW - CO capture
KW - Density functional theory
KW - Grand canonical Monte Carlo
KW - Molecular dynamic
KW - TpBD-COF
UR - http://www.scopus.com/inward/record.url?scp=85203513543&partnerID=8YFLogxK
U2 - 10.1016/j.ces.2024.120702
DO - 10.1016/j.ces.2024.120702
M3 - 文章
AN - SCOPUS:85203513543
SN - 0009-2509
VL - 301
JO - Chemical Engineering Science
JF - Chemical Engineering Science
M1 - 120702
ER -