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Semicrystalline polymers (SCP) represent important class of materials used in many applications from packaging to transportation to electronics to pharmaceuticals. Understanding the structure and dynamics of the crystalline and amorphous fractions within SCP is an important challenge for both experimentalists and theoreticians. Recently, Cheng et al. (S. Cheng et al., J. Chem. Phys. 160, 114904 (2024)) utilized Broadband Dielectric Spectroscopy (BDS) to explore the relaxation time profiles within the amorphous region of a semi-crystalline poly(L-lactic acid) (PLLA) with ordered alternative stacking of crystalline/amorphous phases. Here, we build on those initial results and model the relaxation time distribution using the combination of the Doolittle free volume theory (FVT) and the compressible Self-Consistent Field Theory (cSCFT). We show that the new modeling framework successfully captures the temperature and position dependence of the local relaxation time of the semicrystalline PLLA above the glass transition temperature of the amorphous region. Finally, we derive a new empirical equation for the relaxation time profiles in amorphous regions of SCPs.

Polyurea (PUa) elastomers are extensively used in a wide range of applications spanning from biomedical to defense fields due to their enabling mechanical properties. These materials can be further reinforced through the incorporation of nanoparticles to form nanocomposites. This study focuses on an IPDI-based PUa matrix with exfoliated graphene nanoplatelet (xGnP) fillers. We propose a generalized constitutive model by integrating one Fractional Maxwell Model (FMM) and one Fractional Maxwell Gel (FMG) branch in a parallel configuration via introducing a new dimensionless number to bridge between these branches physically and mathematically. Through systematic local-to-global sensitivity analyses, we investigate the behavior of these nanocomposites to facilitate simulation, design, and performance prediction. Consistently, the constructed models share the same most/least influential model parameters. $\alpha_1$ and $E_{c_1}$, the power exponent and the characteristic modulus of the first branch, are found to be the most influential model parameters, while $\tau_{c_2}$ and $\tau_{c_1}$, the characteristic time-scales of each branch, are recognized as the least influential model parameters. The proposed PU nanocomposite constitutive laws can now make an impact to the design and optimization of coating and shock-absorbing coatings in a range of applications.

We develop a simple yet comprehensive nonlinear model to describe relaxation phenomena in amorphous glass-formers near the glass transition temperature. The model is based on the two-state, two-(time)scale (TS2) framework, and describes the isothermal relaxation of specific volume, enthalpy, or shear stress via a simple first-order nonlinear differential equation (the Trachenko-Zaccone [TZ] equation) for local cooperative events. These nonlinear dynamics of cooperatively rearranging regions (CRR) naturally arise from the TS2 framework. We demonstrate that the solutions of the TZ equation comprehensively encompass the Debye exponential relaxation, the Kohlrausch-Williams-Watts (KWW) stretched and compressed relaxations, and the Guiu-Pratt logarithmic relaxation. Furthermore, for the case of stress relaxation modeling, our model recovers, as one of its limits, the Eyring law for plastic flow, where the Eyring activation volume is related to thermodynamic parameters of the material. Using the example of polystyrene (PS), we demonstrate how our model successfully describes the Kovacs "asymmetry of approach" specific volume and enthalpy experiments, as well as the stress relaxation. Other potential applications of the model, including the dielectric relaxation, are also discussed. The presented approach disentangles the physical origins of different relaxation laws within a single general framework based on the underlying physics., Comment: 34 pages, 5 figures; submitted to Macromolecules

Polyurethane and polyurea-based adhesives are widely used in various applications, from automotive to electronics to medical. The adhesive performance depends strongly on its composition, and developing the formulation-structure-property relationship is crucial to making better products. Here, we investigate the dependence of the linear viscoelastic properties of polyurea nanocomposites, with IPDI-based polyurea (PUa) matrix and exfoliated graphene nanoplatelet (xGnP) fillers, on the hard segment weight fraction (HSWF) and the xGnP loading. We characterize the material using scanning electron microscopy (SEM) and dynamical mechanical analysis (DMA). It is found that changing HSWF leads to a significant variation in the stiffness of the material, from about 10 MPa for the 20% HSWF to about 100 MPa for the 30% HSWF to about 250 MPa for the 40% HSWF polymer (as measured by the tensile storage modulus at room temperature). The effect of the xGNP loading is significantly more limited and is generally within experimental error, except for the 20% HSWF material where the xGNP addition leads to about 80% increase in stiffness. To correctly interpret the DMA results, we developed a new physics-based rheological model for the description of the storage and loss moduli. The model is based on the fractional calculus approach and successfully describes the material rheology in a broad range of temperatures (-70{\deg}C to +70{\deg}C) and frequencies (0.1 to 100 s-1), using only six physically meaningful fitting parameters for each material. The results provide guidance for the development of nanocomposite PUa-based materials., Comment: Accepted to MDPI Polymers

We apply our recently-developed mean-field 'SL-TS2' (two-state Sanchez-Lacombe) model to simultaneously describe dielectric alpha-relaxation time and pressure-volume-temperature (PVT) data in four polymers (polystyrene, poly(methylmethacrylate), poly(vinyl acetate) and poly(cyclohexane methyl acrylate)) and four organic molecular glass formers (ortho-terphenyl, glycerol, PCB-62, and PDE). Previously, it has been shown that for all eight materials, the Casalini-Roland thermodynamical scaling, /tau_{/alpha} = f(TV_{sp}^{/gamma}) (where T is temperature and V_{sp} is specific volume), (Casalini, R.; Roland, C. M. Phys. Rev. Lett. 2014, 113 (8), 85701), is satisfied. It has also been previously shown that the same scaling emerges naturally (for sufficiently low pressures) within the 'SL-TS2' framework (Ginzburg, V. V. Soft Matter 2021, 17, 9094). Here, we fit the ambient pressure curves for the relaxation time and the specific volume as functions of temperature for the eight materials and observe a good agreement between theory and experiment. We then use the Casalini-Roland scaling to convert those results into 'master curves', thus enabling predictions of relaxation times and specific volumes at elevated pressures. The proposed approach can be used to describe other glass-forming materials, both low-molecular-weight and polymeric., Comment: 33 pages, 7 figures; submitted to Soft Matter

The COVID-19 pandemic has been a great catastrophe that upended human lives and caused millions of deaths all over the world. The rapid spread of the virus, with its early-stage exponential growth and subsequent 'waves', caught many medical professionals and decision-makers unprepared. Even though epidemiological models have been known for almost a century (since the 'Spanish Influenza' pandemic of 1918-20), the real-life spread of the SARS-CoV-2 virus often confounded the modelers. While the general framework of epidemiological models like SEIR (susceptible-exposed-infected-recovered) or SIR (susceptible-exposed-infected) was not in question, the behavior of model parameters turned out to be unpredictable and complicated. In particular, while the 'basic' reproduction number, R0, can be considered a constant (for the original SARS-CoV-2 virus, prior to the emergence of variants, R0 is between 2.5 and 3.0), the 'effective' reproduction number, R(t), was a complex function of time, influenced by human behavior in response to the pandemic (e.g., masking, lockdowns, transition to remote work, etc.) To better understand these phenomena, we model the first year of the pandemic (between February 2020 and February 2021) for a number of localities (fifty US states, as well as several countries) using a simple SIR model. We show that the evolution of the pandemic can be described quite successfully by assuming that R(t) behaves in a 'viscoelastic' manner, as a sum of two or three 'damped oscillators' with different natural frequencies and damping coefficients. These oscillators likely correspond to different sub-populations having different reactions to proposed mitigation measures. The proposed approach can offer future data modelers new ways to fit the reproduction number evolution with time (as compared to the purely data-driven approaches most prevalent today).

We simulate the motion of spherical particles in a phase-separating binary mixture. By combining cell dynamical equations with Langevin dynamics for particles, we show that the addition of hard particles significantly changes both the speed and the morphology of the phase separation. At the late stage of the spinodal decomposition process, particles significantly slow down the domain growth, in qualitative agreement with earlier experimental data., Comment: RevTex, 5 pages, 4 figures

We propose the general scaling model for the diffusio n-annihilation reaction $A_{+} + A_{-} \longrightarrow \emptyset$ with long-range power-law i nteractions. The presented scaling arguments lead to the finding of three different regimes, dep ending on the space dimensionality d and the long-range force power e xponent n. The obtained kinetic phase diagram agrees well with existing simulation data and approximate theoretical results., Comment: RevTEX, 7 pages, no figures, accepted to Physical Review E

We propose an exactly solvable self-consistent kinetic model of polymerization-induced phase separation (PIPS) via spinodal decomposition. Using modified Cahn-Hilliard and Glotzer-Coniglio theories for early and late stages of spinodal decomposition, we find scaling regimes and compare the obtained results with existing experimental and theoretical information on PIPS kinetics, finding a good qualitative agreement., Comment: RevTEX, 15 pages, 3 figures - GIF files, available upon request from ginzburg@colorado.edu

We introduce coarse-grained hydrodynamic equations of motion for diffusion-annihilation system with a power-law long-range interaction. By taking into account fluctuations of the conserved order parameter - charge density - we derive an analytically solvable approximation for the nonconserved order parameter - total particle density. Asymptotic solutions are obtained for the case of random Gaussian initial conditions and for system dimensionality $d \geq 2$. Large-t, intermediate-t and small-t asymptotics were calculated and compared with existing scaling theories, exact results and simulation data., Comment: 22 pages, RevTEX, 1 PostScript figure