Multiscale Simulation of Pollution Gases Adsorption
in Porous Organic Cage CC3
Supporting Information
Wenliang Li and Jingping Zhang*
Faculty of Chemistry, Northeast Normal University, Changchun, China
*Prof. J.P. Zhang Email: jpzhang@nenu.edu.cn
The supplementary material contains:
 Details of GCMC simulation (Page S2)
 Comparison of interaction energies for gas-benzene at CCSD(T) and B2PLYP-D3
level (Page S3)
 Comparison of PES for gas-CC3Frag and gas-gas at B2PLYP-D3 and vdW3 level
(Page S4)
 Optimized parameters of vdW3 (Page S12)
S1
 Details of GCMC simulation
The gas loadings in a fixed cell of CC3[1] with the size of 24.8*24.8*24.8 Å3
were computed from the GCMC simulations. For all gases we used rotation,
translation, insertion and deletion as possible Monte Carlo steps. Each simulation
started with a one-million step equilibration period followed by a one-million step
production run. Non-covalent interactions of two molecules with the distance of
their centers of mass less than 12.4 Å were taken into consideration. The gas-gas
and gas-CC3 interaction energies were evaluated from fitted vdW3 FF. And all
absolute loadings Nad were converted to excess loadings Nex to allow direct
comparison of the results with experimental data by
Nex=Nad-ρbVfree
(1)
where ρb is the bulk density obtained by PR EOS, and Vfree is the available
volume for fluid molecules.
For LJ based GCMC simulation, a 5×106 step equilibration period followed by
a 5×106 step production run. The CO2 is modeled as a three site molecule with
-0.35 e on oxygen and 0.7 e on carbon.[2] The partial charges for atoms of the
CC3 were derived from QEq method in Materials Studio.[3] The LJ parameters
used for CC3 are taken from UFF[4] and listed together with the parameters of
CO2 in Table S1.
Table S1. Parameters for Gases and Frameworks for LJ based GCMC simulation
ε(K)
б(Å)
q(e)
C
52.84
3.43
CC3
H
22.14
2.57
N
34.72
3.26
O_CO2
79.00
3.05
-0.35
CO2
C_CO 2
27.00
2.80
0.70
S2
 Comparison of PES for gas-benzene at CCSD(T) and B2PLYP-D3 level
Figure S1 Comparison of interaction energies of gas-benzene for the CCSD(T)/CBS
and B2PLYP-D3/def2-tZVPP methods.
S3
 Comparison of PES for gas-CC3Frag and gas-gas at B2PLYP-D3 and vdW3 level
Figure S2 Comparison of the vdW3 interaction energies (red triangles) with
B2PLYP-D3/def2-TZVPP energies (black triangles) for CO2-CC3. The lines are
drawn to guide the eye.
S4
Figure S3 Comparison of the vdW3 interaction energies (red triangles) with
B2PLYP-D3/def2-TZVPP energies (black triangles) for CO2-CO2. The lines are
drawn to guide the eye.
S5
Figure S4 Comparison of the vdW3 interaction energies (red triangles) with
B2PLYP-D3/def2-TZVPP energies (black triangles) for SO2-CC3. The lines are
drawn to guide the eye.
S6
Figure S5 Comparison of the vdW3 interaction energies (red triangles) with
B2PLYP-D3/def2-TZVPP energies (black triangles) for SO2- SO2. The lines are
drawn to guide the eye.
S7
Figure S6 Comparison of the vdW3 interaction energies (red triangles) with
B2PLYP-D3/def2-TZVPP energies (black triangles) for H2S-CC3. The lines are
drawn to guide the eye.
S8
Figure S7 Comparison of the vdW3 interaction energies (red triangles) with
B2PLYP-D3/def2-TZVPP energies (black triangles) for H2S-H2S. The lines are drawn
to guide the eye.
S9
Figure S8 Comparison of the vdW3 interaction energies (red triangles) with
B2PLYP-D3/def2-TZVPP energies (black triangles) for CO-CC3. The lines are drawn
to guide the eye.
S10
Figure S9 Comparison of the vdW3 interaction energies (red triangles) with
B2PLYP-D3/def2-TZVPP energies (black triangles) for CO-CO. The lines are drawn
to guide the eye.
S11
Table S2 Parameterizations of vdW3 optimized for the dimer interactions of CC3 Frag
with CO2, SO2, H2S and CO. The last line contains the resulting minimum root mean
square deviations (RMS) in kcal ·mol−1. The reference method is
B2PLYP-D3/def2-TZVPP as described in the main text.
pd6
pd8
pr
pes
pDipole
p2nd
prep1
prep2
pH
pVOIP
RMS
CC3-CO2
CO2-CO2
CC3-SO2
SO2-SO2
CC3-H2S
H2S-H2S
CC3-CO
CO-CO
1.06048
1.45515
2.62517
0.76955
0.31526
1.04993
0.234028
0.185822
2.098630
0.690398
0.11
1.12772
1.19887
2.53233
0.97864
0.03644
1.53066
0.22113
0.17344
2.05645
0.56695
0.58
1.07282
1.40070
3.08608
3.59801
0.09990
2.26819
0.22621
0.10180
2.97585
1.81831
0.22
1.00736
1.12320
3.97377
2.67236
0.43656
0.02257
0.41166
0.04268
3.49848
2.43552
0.84
1.10417
1.31770
1.95488
0.03775
0.91894
1.97018
0.23343
0.18186
2.42833
0.90988
0.47
1.09806
2.10764
2.40084
0.04027
0.62050
2.85752
0.22260
0.27050
2.21655
0.85358
0.23
1.13526
1.39631
2.48312
0.52104
0.30160
1.90992
0.26297
0.02263
1.70445
0.47147
0.39
1.04169
1.21841
2.50152
0.03040
0.15510
2.46059
0.43055
0.02480
1.82909
0.29061
0.22
S12
Reference:
[1]
T. Tozawa, J. T. A. Jones, S. I. Swamy, S. Jiang, D. J. Adams, S. Shakespeare, R.
Clowes, D. Bradshaw, T. Hasell, S. Y. Chong, C. Tang, S. Thompson, J. Parker, A. Trewin, J.
Bacsa, A. M. Z. Slawin, S. Alexander, A. I. Cooper, Nat. Mater. 2009, 8, 973-978.
[2]
J. J. Potoff, J. I. Siepmann, AIChE Journal 2001, 47, 1676-1682.
[3]
Accelrys Inc., San Diego, CA, 2005.
[4]
A. K. Rappié, C. J. Casewit, K. S. Colwell, W. A. Goddard III, W. M. Skid, J. Am.
Chem. Soc. 1992, 114, 10024-10035.
S13