Biomedical Engineering Reference
In-Depth Information
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Cellulose film
Silica surface
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Time (min)
Figure 4.10 Changes in frequency with high-charge density polyampholyte adsorption,
beforeandafter rinsing, for silica substrateandcellulosefilmsurfaces. Conditions: pH4.3;
temperature25 C; and [NaCl] 1mM. The polyampholytewas injectedat time10min and
afteranincubationtimeofca.55minrinsingwithbackgroundelectrolytewasperformed.
measured QCM frequency was observed after replacing the polymer solution with the
buffer solution (rinsing). These observations imply that the interactions forces between
the polyampholyte and silica are stronger than for the cellulose film. These results can
be explained by considering electrostatic interactions as the main driving mechanism for
adsorption as both substrates exhibit significantly different surface charge densities. For
long equilibration times small changes in frequency are evident; this is hypothesized
to be the result of polymer reconformation and exchange at the interface, given the
polydisperse nature of this macromolecule.
The swelling and water-holding ability of adsorbed polyampholyte layers on cellulose
films as a function of ionic strength was evaluated by using D f plots. Figure 4.11
shows the relation between dissipation and frequency change for the same high charge
density polyampholyte adsorbed on cellulose at different ionic strengths.
Larger variations in energy dissipation imply more viscoelastic layers. Significant
changes in energy dissipation can be seen for intermediate values of salt concentration
(e.g., 10 and 100 mM). The viscoelastic character of the polyampholyte layers built up
at extreme salt conditions is interpreted as being the result of more rigid structures (e.g.,
at 0.1, 1, and 1000 mM). On the other hand, no major differences are observed on the
state of hydration and extension of the adsorbed layer.
4.10.3
Coupling QCM and SPR Data
While SPR and QCM are often used to monitor adsorption and adsorbed layer dynamics,
each technique has its own strengths and weaknesses. Also, as presented before, they
have assumptions inherent in data collection and analysis (Bailey, Kambhampati et al .
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