Impact of Chain Conformation on Structural Heterogeneity in Polymer Network

Abstract

Polymer networks generally consist of an ensemble of single chains. However, understanding how chain conformation affects the structure and properties of polymer networks remains a challenge for optimizing their functionality. Here, we present the fabrication and comparative study of a polymer network composed of collapsed self-entangled chains (intrachain entangled network) and a standard polymer network in which random-coil chains are entangled with each other (interchain entangled network). For poly­(methyl methacrylate) thin films composed of these networks, we coupled solvent vapor swelling and single-molecule tracking techniques to examine the anomalies in the dynamics of a small-molecular probe included in the system. We demonstrate that when compared to the interchain entangled network the intrachain one exhibits a more substantial structural heterogeneity, particularly under highly crowded conditions. This network also exhibits physical compactness, which keeps the heterogeneous network structure frozen over time and impedes network plasticization through solvent uptake by the film.

Single-Particle Tracking in Poly(Ethylene Glycol) Diacrylate: Probe Size Effect on the Diffusion Behaviors of Nanoparticles in Unentangled Polymer Solutions

“…Regardless of the diameter, both displacement distributions possess a tail at larger normalΔ x τ , especially at smaller τ, which reveal the presence of anomalous and non-Gaussian diffusion behaviors of the nanoparticles in the unentangled PEGDA solutions, studied in this work. In fact, a careful analysis of the tails in the G s curves using a previously reported approach further indicate that the probability of a large tracer displacement is lower for the 200 nm particle and therefore more Gaussian . These results can be associated with several possible physical reasons and interactions: the strong steric interactions existing between the bulky probe particle and the dense, crowded polymer solution; the spatial heterogeneity of the microscale PEGDA structure, probed by the nanoparticles across multiple length and time scales; , and the effect of the probe confinement within a crowded microstructure.…”

“…71,86 As previously reported, Fickian diffusion exhibiting non-Gaussian displacement characteristics has been observed in many complex materials, ranging from hydrogel structures 50,58 to solventswollen polymer films and networks. 87,99 In this work, we initially characterized the nanoparticles' transport mode by using the power-law scaling approach. It involves a least-square fitting of the single-particle tMSD curves using a wellestablished power law function, yielding the subdiffusion parameter, β.…”

“…In fact, a careful analysis of the tails in the G s curves using a previously reported approach 72 further indicate that the probability of a large tracer displacement is lower for the 200 nm particle and therefore more Gaussian. 87 These results can be associated with several possible physical reasons and interactions: the strong steric interactions existing between the bulky probe particle and the dense, crowded polymer solution; 72 the spatial heterogeneity of the microscale PEGDA structure, probed by the nanoparticles across multiple length and time scales; 66,87 and the effect of the probe confinement within a crowded microstructure. As predicted, the hindered diffusion of particles is complex and may be originated from multiple factors at the same time.…”

“…For each relevant particle size, the van Hove distribution was obtained for three different τ values (1, 5, and 10 frames) and was fitted to a Gaussian function to obtain the standard deviation, σ, in each distribution. For the sake of simplicity, the positive half of G s (Δ x , τ) was plotted versus Δ x /σ, consistent to previous publications . The deviation of the van Hove distributions from the expected Gaussian behavior was also quantified via the non-Gaussian parameter, α 2 (eq ): α 2 = false⟨ normalΔ x 4 ( τ ) false⟩ 3 false⟨ normalΔ x 2 ( τ ) false⟩ 2 − 1 where Δ x 4 (τ) and Δ x 2 (τ) describe the fourth and second moment of the probability distribution function of two-dimensional particle displacements, respectively.…”

“…For the sake of simplicity, the positive half of G s (Δx, τ) was plotted versus Δx/σ, consistent to previous publications. 87 The deviation of the van Hove distributions from the expected Gaussian behavior was also quantified via the non-Gaussian parameter, α 2 (eq 5): 18…”