The seemingly simple notion of the hydrophobic effect can be viewed
from multiple angles involving theory, simulation, and experiments.
This viewpoint examines five attributes of predictive models to enhance
synthetic efforts as well as experimental methods to quantify hydrophobicity.
In addition, we compare existing predictive models against experimental
data for polymer surface tension, lower critical solution temperature,
solution self-assembly morphology, and degradation behavior. Key conclusions
suggest that both the Hildebrand solubility parameters (HSPs) and
surface area-normalized Log
P
(Log
P
SA
–1
) values provide unique and complementary
insights into polymer phenomena. In particular, HSPs appear to better
describe bulk polymer phenomena for thermoplastics such as surface
tension, while Log
P
SA
–1
values
are well-suited for describing and predicting the behavior of polymers
in solution.
Thermoresponsive
copolymers that exhibit a lower critical solution temperature (LCST)
have been exploited to prepare stimuli-responsive materials for a
broad range of applications. It is well understood that the LCST of
such copolymers can be controlled by tuning molecular weight or through
copolymerization of two known thermoresponsive monomers. However,
no general methodology has been established to relate polymer properties
to their temperature response in solution. Herein, we sought to develop
a predictive relationship between polymer hydrophobicity and cloud
point temperature (
T
CP
). A series of statistical
copolymers were synthesized based on hydrophilic oligoethylene glycol
monomethyl ether methacrylate (OEGMA) and hydrophobic alkyl methacrylate
monomers and their hydrophobicity was compared using surface area-normalized
partition coefficients (log
P
oct
/SA).
However, while some insight was gained by comparing
T
CP
and hydrophobicity values, further statistical analysis
on both experimental and literature data showed that the molar percentage
of comonomer (i.e., grafting density) was the strongest influencer
of
T
CP
, regardless of the comonomer used.
The lack of dependence of
T
CP
on comonomer
chemistry implies that a broad range of functional, thermoresponsive
materials can be prepared based on OEGMA by simply tuning grafting
density.
Polymers that exhibit
a lower critical solution temperature (LCST)
have been of great interest for various biological applications such
as drug or gene delivery, controlled release systems, and biosensing.
Tuning the LCST behavior through control over polymer composition
(e.g., upon copolymerization of monomers with different hydrophobicity)
is a widely used method, as the phase transition is greatly affected
by the hydrophilic/hydrophobic balance of the copolymers. However,
the lack of a general method that relates copolymer hydrophobicity
to their temperature response leads to exhaustive experiments when
seeking to obtain polymers with desired properties. This is particularly
challenging when the target copolymers are comprised of monomers that
individually form nonresponsive homopolymers, that is, only when copolymerized
do they display thermoresponsive behavior. In this study, we sought
to develop a predictive relationship between polymer hydrophobicity
and cloud point temperature (
T
CP
). A series
of statistical copolymers were synthesized based on hydrophilic
N
,
N
-dimethyl acrylamide (DMA) and hydrophobic
alkyl acrylate monomers, and their hydrophobicity was compared using
surface area-normalized octanol/water partition coefficients (Log
P
oct
/SA). Interestingly, a correlation between
the Log
P
oct
/SA of the copolymers and
their
T
CP
s was observed for the P(DMA-
co
-RA) copolymers, which allowed
T
CP
prediction of a demonstrative copolymer P(DMA-
co
-MMA). These results highlight the strong potential of this computational
tool to improve the rational design of copolymers with desired temperature
responses prior to synthesis.
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