Disentangling Component Dynamics in an All-Polymer Nanocomposite Based on Single-Chain Nanoparticles by Quasielastic Neutron Scattering

Nonmonotonic Composition Dependence of Viscosity upon Adding Single-Chain Nanoparticles to Entangled Polymers

Well-characterized single-chain nanoparticles (SCNPs), synthesized from a linear polystyrene precursor through an intramolecular [4 + 4] thermal cycloaddition cross-linking reaction in dilute conditions, were added to entangled polystyrene melts at different concentrations. Starting from the pure linear melt, which is much more viscous than the melt of SCNPs, the zero-shear viscosity increased upon the addition of nanoparticles and reached a maximum before eventually dropping to the value of the SCNP melt. Molecular simulations reveal the origin of this unexpected behavior, which is the interplay of the very different compositional dependences of the dynamics of the two components. The SCNPs become much slower than the linear chains as their concentration decreases because they are threaded by the linear chains, reaching a maximum viscosity which is higher than that of the linear chains at a fraction of about 20%. This behavior is akin to that of single-loop ring polymers when added to linear matrices. This finding provides insights into the design and use of SCNPs as effective entropic viscosity modifiers of polymers and contributes to the discussion of the physics of loopy structures.

When does a macromolecule transition from a polymer chain to a nanoparticle?

Frequently, the defining characteristic of a nanoparticle is simply its size, where objects that are 1-100 nm are characterized as nanoparticles. However, synthetic and biological macromolecules, in particular high molecular weight chains, can satisfy this size requirement without providing the same phenomena as one would expect from a nanoparticle. At the same time, soft polymer nanoparticles are important in a broad range of fields, including understanding protein folding, drug delivery, vitrimers, catalysis and nanomedicine. Moreover, the recent flourish of all polymer nanocomposites has led to the synthesis of soft all-polymer nanoparticles, which emerge from internal crosslinking of a macromolecule. Thus, there exists a transition of an internally crosslinked macromolecule from a polymer chain to a nanoparticle as the amount of internal crosslinks increases, where the polymer chain exhibits different behavior than the nanoparticle. Yet, this transition is not well understood. In this work, we seek to address this knowledge gap and determine the transition of a macromolecule from a polymer chain to a nanoparticle as internal crosslinking increases. In this work, small angle neutron scattering (SANS) offers insight into the structure of polystyrene and poly(ethyl hexyl methacrylate) nanostructures in dilute solutions, with crosslinking densities that vary from 0.1 to 10.7%. Analyses of the SANS data provides structural characteristics to classify a nanostructure as chain-like or particle-like and identify a crosslinking dependent transition between the two morphologies. It was found that for both types of polymeric nanostructures, a crosslinking density of 0.81% (∼ a crosslink for every 1 in 125 monomers) or higher exhibit clear particle-like behavior. Lower crosslinking density nanostructures showed amounts of collapse similar to that of a star polymer (0.1% XL) or a random walk polymer chain (0.4% XL). Thus, the transition of an internally crosslinked macromolecule from a polymer chain to a nanoparticle is not an abrupt transition but occurs via the gradual contraction of the chain with incorporated crosslinks.

Impact of composition on the crystal texture and on the dynamics of P(THF-co-ECH) copolymers

We present a combined study by quasielastic neutron scattering (QENS), differential scanning calorimetry (DSC) and wide angle X-ray scattering (WAXS) on poly(tetrahydrofuran-co-epichlorohydrin) copolymers, to see how their composition can be used to tune their crystallizability and to elucidate the impact of this factor on the dynamical properties. QENS reveals a strong effect on the local dynamics upon cooling down, where the local motions of a sample that remains in the supercooled state at lower temperatures are less Gaussian and slower than those in a sample that crystallizes a few degrees below. This can be attributed to the enhancement of local heterogeneities in the former, which could be a determining factor preventing crystallization.