Chemistry Reference
In-Depth Information
Table 4 Pseudocomponents for poly(ethylene) considered in Fig.
14
M
k
k
={ 1, 0, 1, 2, 3, 4}
k = {0, 1, 2, 3}
j
M
2
p
,
j
(g/mol)
x
2
p
,
j
M
2
p
,
j
(g/mol)
x
2
p
,
j
10
4
10
3
1
2.8614
0.93970
2.7676
0.54529
2.6717
10
5
8.3769
10
4
2
0.06030
0.44588
4.6883
10
5
3
0.00883
M
k
moment of molecular weight distribution,
M
2
p,j
molecular weight of the pseudocomponent,
x
2
p,j
mole fraction of the pseudocomponent in the solvent free system
Fig. 16 Solubility of poly(E
96.2
co
AA
3.8
) in ethene. Polymer properties can be found in Table
5
.
Polymer concentration in the mixture is about 3 wt%.
Symbols
represent experimental data [
61
]
compared with results form PC SAFT calculation [
43
].
Dashed line
shows monodisperse calcula
tion using
M
n
;
solid line
shows monodisperse calculation using
M
w
; and
dotted line
shows
calculation using two pseudocomponents given in Table
6
Figure
14
contains the results obtained with PC-SAFT when using the set of two
pseudocomponents left-hand side from Table
4
, in comparison with the experimen-
tal data and with the monodisperse calculations. As can be seen, the results of the
calculations can be improved remarkably when accounting for the polydispersity by
using only two pseudocomponents.
As a second example, the phase equilibrium in the system poly(ethylene-
co
-
acrylic acid)/ethene is illustrated in Fig.
16
. The polymer has a polydispersity index
M
w
/
M
n
of about 3.3. The solubility of this copolymer was first modeled assuming
the polymer to be monodisperse. Neither modeling using
M
n
nor using
M
w
as the
molecular weight of the polymer could satisfactorily describe the experimental data
(Fig.
16
). In a second step, the polydispersity of the copolymer was accounted for
by using two pseudocomponents (see Table
6
). As also shown in Fig.
16
, without
changing or refitting any parameters, the modeling is now in almost perfect
agreement with the experimental data. This again demonstrates the importance of
accounting for polydispersity in the modeling as well as in the interpretation of the
experimental data [
43
].
