Polymeric-based
microparticles and fibers are tailorable for a
wide range of common industrial and biomedical applications, while
multiwalled carbon nanotubes (MWCNTs) are among the most useful macromolecules
based on their outstanding electronic, mechanical, and optical properties
at the nanoscale. If one combines these nanostructures with various
polymeric precursors, their range of potential applications becomes
even greater. One of the simplest and most affordable methods for
fabricating micro- and nanostructures is electrospinning. Herein we
demonstrate how MWCNTs may be used to produce tailor-made organic–organic
poly(vinylpyrrolidone) (PVP) microparticles and fibers via electrospinning
by studying their structural, vibrational, rheological, and mechanical
properties’ dependence on their solvent (ethanol (EtOH) or
dimethylformamide (DMF)) and resulting morphology. Specifically,
we find clear differences in morphologies from perfectly spherical
and isolated microparticles to fibers mats, or a combination of fibers
with entangled beads, with solvent type and concentration. On the
basis of our findings, we propose that the mechanism governing the
shape and size of the particles is a competition between the solvent’s
surface tension, dielectric constant, and viscoelastic properties.
We show, based on both our experimental results and density functional
theory (DFT) calculations, that OH functionalization of the MWCNTs
is essential for achieving high PVP coverages and promoting the stability
of the resulting PVP/MWCNT nanocomposite. Finally, by fabricating
PVP/MWCNT fiber mats, we demonstrate that low concentrations (0.01–0.1
wt %) of MWCNTs led to a qualitative improvement (∼250%) in
the resulting mechanical properties, i.e., a reinforced composite.
These results show how by controlling the solvent’s dielectric
constant, surface tension, and polymer concentration, one may produce
tailor-made polymeric nanomaterials in combination with other organic/inorganic
nanoparticles, i.e., silver, gold, or carbon allotropes, for next-generation
applications.