60
A. Jayaraman et al.
presented above due to the higher CLP concentrations needed for these assembly
studies. Nonetheless, these CG simulations are feasible unlike atomistic simulations
and would be worthwhile as the formation of large-scale fibrils and fibers govern
the mechanical properties of CLP which is an important design parameter for its
application as a biomaterial for drug delivery and tissue engineering applications.
4 Polymer Nanocomposites (PNCs)
4.1 Background
Macroscopic properties of polymeric materials can be enhanced by mixing or
blending two polymers [109, 110] or by adding nanoparticles to a polymer forming
a polymer nanocomposite (PNC) [111–116]. The improved properties of the blend
or PNC compared to its pure components arise from the spatial arrangement of
the various components in the blend/nanocomposite. The spatial arrangement or
morphology of the polymer blends/PNCs at equilibrium is governed by thermodynamic driving forces. The key thermodynamic driving forces are the gain in entropy
upon mixing of these components, loss in polymer conformational entropy that could
occur upon mixing/demixing and favorable/unfavorable energetic interactions upon
mixing of the components of the blends/PNCs. These driving forces can be tuned
independently or in a coupled manner by varying the chemistry [117, 118], molecular weight [119, 120] and architecture of the polymer(s) [120–122], and in the
case of PNCs, also varying the chemistry [123–126], size [127–129], shape [130]
and surface functionalization [131–133] of the particles. In both blends and PNCs,
some polymer chemistries could enable directional and specific favorable interactions via h-bonding [2, 134, 135], π-π stacking [136, 137], etc. Apart from bringing
about an obvious gain in enthalpy through these interactions between polymers or
between polymer and the nanoparticle, specific and directional interactions can also
bring about a non-negligible change in entropy due to rotational constraints imposed
on interacting atoms in the presence of these directional interactions [138–140].
Thus, a mean-field representation of such directional interactions does not suffice
to describe the free energy of mixing in polymer blends and/or PNCs with specific
and directional interactions [138–142]. This motivates our work described in this
section aimed at developing polymer CG models that capture such directional and
specific interactions in order to guide synthesis of new synthetic polymer materials
or help understand past experimental results obtained for systems with such polymer
chemistries.
Past experimental studies have focused on understanding how h-bonding influences the phase behavior in polymer blends and PNCs. For example, in polymer
blends, past studies have looked at the effects of competition between intra- and
inter-chain h-bonding, accessibility of functional groups, steric crowding, spacing
between functional groups, etc., on the extent of h-bonding in the blend [138–140,
A. Jayaraman et al.
presented above due to the higher CLP concentrations needed for these assembly
studies. Nonetheless, these CG simulations are feasible unlike atomistic simulations
and would be worthwhile as the formation of large-scale fibrils and fibers govern
the mechanical properties of CLP which is an important design parameter for its
application as a biomaterial for drug delivery and tissue engineering applications.
4 Polymer Nanocomposites (PNCs)
4.1 Background
Macroscopic properties of polymeric materials can be enhanced by mixing or
blending two polymers [109, 110] or by adding nanoparticles to a polymer forming
a polymer nanocomposite (PNC) [111–116]. The improved properties of the blend
or PNC compared to its pure components arise from the spatial arrangement of
the various components in the blend/nanocomposite. The spatial arrangement or
morphology of the polymer blends/PNCs at equilibrium is governed by thermodynamic driving forces. The key thermodynamic driving forces are the gain in entropy
upon mixing of these components, loss in polymer conformational entropy that could
occur upon mixing/demixing and favorable/unfavorable energetic interactions upon
mixing of the components of the blends/PNCs. These driving forces can be tuned
independently or in a coupled manner by varying the chemistry [117, 118], molecular weight [119, 120] and architecture of the polymer(s) [120–122], and in the
case of PNCs, also varying the chemistry [123–126], size [127–129], shape [130]
and surface functionalization [131–133] of the particles. In both blends and PNCs,
some polymer chemistries could enable directional and specific favorable interactions via h-bonding [2, 134, 135], π-π stacking [136, 137], etc. Apart from bringing
about an obvious gain in enthalpy through these interactions between polymers or
between polymer and the nanoparticle, specific and directional interactions can also
bring about a non-negligible change in entropy due to rotational constraints imposed
on interacting atoms in the presence of these directional interactions [138–140].
Thus, a mean-field representation of such directional interactions does not suffice
to describe the free energy of mixing in polymer blends and/or PNCs with specific
and directional interactions [138–142]. This motivates our work described in this
section aimed at developing polymer CG models that capture such directional and
specific interactions in order to guide synthesis of new synthetic polymer materials
or help understand past experimental results obtained for systems with such polymer
chemistries.
Past experimental studies have focused on understanding how h-bonding influences the phase behavior in polymer blends and PNCs. For example, in polymer
blends, past studies have looked at the effects of competition between intra- and
inter-chain h-bonding, accessibility of functional groups, steric crowding, spacing
between functional groups, etc., on the extent of h-bonding in the blend [138–140,