Transcript Computational investigation of new separation schemes for

Computational investigation of new separation schemes
for branched polymers
Yongmei Wang, Department of Chemistry, University of Memphis
Separation and characterization of branched polymers according to its architecture is a real need and a real
challenge. The simplest and first-implemented chromatographic techniques separate polymers according to
size, which is the basis of size exclusion chromatography (i.e. SEC). The desire to separate polymers
according to properties other than size has led to the advent of novel chromatographic methods such as liquid
chromatography at the critical condition (LCCC) and liquid adsorption chromatography (LAC). However, the
partitioning rules of star-shaped polymers in these chromatography conditions are not well understood. We
perform Monte Carol simulations to investigate the partitioning rules of star polymers at all three
chromatographic conditions and we contrast behavior between random walk (RW) model versus self-avoiding
walks (SAW) model of polymer chains. The former is widely used to interpret experimental results, but the
latter is a more accurate model of real star polymers encountered in experiments.
Random walk stars in LAC mode
f=2; D=14
f=2; D=29
f=3; D=14
f=3; D=29
f=4; D=14
f=4; D=29
f=6; D=14
f=6; D=29
f=8; D=14
f=8; D=29
50
ln(K)
40
30
20
10
0
100
200
300
Ntot
400
500
30
25
ln(K)
60
SAW stars in LAC mode
20
15
10
5
f=2; D=14
f=2; D=29
f=3; D=14
f=3; D=29
f=4; D=14
f=4; D=29
f=6; D=14
f=6; D=29
f=8; D=14
f=8; D=29
-100
0
100
Ntot
200
300
Two graphs on the left
illustrate how the two
models lead to different
predictions. RW model
predicts that in LAC model,
partitioning coefficient K is
independent of number of
arms, only on total
molecular weight Ntot;
SAW model shows there
are dependence on
parameters other than Ntot.