Energy Renormalization Method for the Coarse-Graining of Polymer Viscoelasticity.

Developing temperature transferable coarse-grained (CG) models is essential for the computational prediction of polymeric glass-forming (GF) material behavior, but their dynamics are often greatly altered from those of all-atom (AA) models mainly because of the reduced fluid configurational entropy under coarse-graining. To address this issue, we have recently introduced an energy renormalization (ER) strategy that corrects the activation free energy of the CG polymer model by renormalizing the cohesive interaction strength ε as a function of temperature T, i.e., ε(T), thus semiempirically preserving the T-dependent dynamics of the AA model. Here we apply our ER method to consider-in addition to T-dependency-the frequency f-dependent polymer viscoelasticity. Through smallamplitude oscillatory shear molecular dynamics simulations, we show that changing the imposed oscillation f on the CG systems requires changes in ε values (i.e., ε(T, f)) to reproduce the AA viscoelasticity. By accounting for the dynamic fragility of polymers as a material parameter, we are able to predict ε(T, f) under coarse-graining in order to capture the AA viscoelasticity, and consequently the activation energy, across a wide range of T and f in the GF regime. Specifically, we showcase our achievements on two representative polymers of distinct fragilities, polybutadiene (PB) and polystyrene (PS), and show that our CG models are able to sample viscoelasticity up to the megahertz regime, which approaches state-of-the-art experimental resolutions, and capture results sampled via AA simulations and prior experiments.

Side-group size effects on interfaces and glass formation in supported polymer thin films.

Recent studies on glass-forming polymers near interfaces have emphasized the importance of molecular features such as chain stiffness, side-groups, molecular packing, and associated changes in fragility as key factors that govern the magnitude of Tg changes with respect to the bulk in polymer thin films. However, how such molecular features are coupled with substrate and free surface effects on Tg in thin films remains to be fully understood. Here, we employ a chemically specific coarse-grained polymer model for methacrylates to investigate the role of side-group volume on glass formation in bulk polymers and supported thin films. Our results show that bulkier side-groups lead to higher bulk Tg and fragility and are associated with a pronounced free surface effect on overall Tg depression. By probing local Tg within the films, however, we find that the polymers with bulkier side-groups experience a reduced confinement-induced increase in local Tg near a strongly interacting substrate. Further analyses indicate that this is due to the packing frustration of chains near the substrate interface, which lowers the attractive interactions with the substrate and thus lessens the surface-induced reduction in segmental mobility. Our results reveal that the size of the polymer side-group may be a design element that controls the confinement effects induced by the free surface and substrates in supported polymer thin films. Our analyses provide new insights into the factors governing polymer dynamics in bulk and confined environments.

Energy-Renormalization for Achieving Temperature Transferable Coarse-Graining of Polymer Dynamics.

The bottom-up prediction of the properties of polymeric materials based on molecular dynamics simulation is a major challenge in soft matter physics. Coarse-grained (CG) models are often employed to access greater spatiotemporal scales required for many applications, but these models normally experience significantly altered thermodynamics and highly accelerated dynamics due to the reduced number of degrees of freedom upon coarse-graining. While CG models can be calibrated to meet certain properties at particular state points, there is unfortunately no temperature transferable and chemically specific coarse-graining method that allows for modeling of polymer dynamics over a wide temperature range. Here, we pragmatically address this problem by "correcting" for deviations in activation free energies that occur upon coarse-graining the dynamics of a model polymeric material (polystyrene). In particular, we propose a new strategy based on concepts drawn from the Adam-Gibbs (AG) theory of glass formation. Namely we renormalize the cohesive interaction strength and effective interaction length-scale parameters to modify the activation free energy. We show that this energy-renormalization method for CG modeling allows accurate prediction of atomistic dynamics over the Arrhenius regime, the non-Arrhenius regime of glass formation, and even the non-equilibrium glassy regime, thus allowing for the predictive modeling of dynamic properties of polymer over the entire range of glass formation. Our work provides a practical scheme for establishing temperature transferable coarse-grained models for predicting and designing the properties of polymeric materials.

Glass-Transition and Side-Chain Dynamics in Thin Films: Explaining Dissimilar Free Surface Effects for Polystyrene vs Poly(methyl methacrylate).

Despite having very similar bulk properties such as glass-transition temperature (Tg), density, and fragility, polystyrene (PS) and poly(methyl methacrylate) (PMMA) exhibit characteristically different Tg depression in free-standing ultrathin films due to free surface effects. Here we explain this difference using our recently established chemistry-specific coarse-grained (CG) models for these two polymers. Models capture the dissimilar scaling of Tg with free-standing film thickness as seen in experiments and enable us to quantify the size of the regions near free surfaces over which chain relaxation exhibits differences from bulk. Most interestingly, vibrational density of states (VDOS) analysis uncovers a relationship between the amplitude of side-chain fluctuations, associated with side-chain flexibility and Tg-nanoconfinement. We discover that increasing backbone to side-chain mass ratio in CG models increases the amplitude of side-chain fluctuations and suppresses the free-surface effect on Tg. We show that mass distribution and side-chain flexibility are central to explain dissimilar free surface effects on PS and PMMA. Our model predictions are further corroborated by experimental evidence showing the role of mass distribution in styrene thin films. Our study ascertains the significance of molecular characteristics on nanoconfinement and highlights the ability for chemistry-specific CG models to explore the thermomechanical properties of polymer thin films.

Molecular Weight Effects on the Glass Transition and Confinement Behavior of Polymer Thin Films.

Nanoscale polymer thin films exhibit strong confinement effects on Tg arising from free surfaces. However, the coupled influence of molecular weight (MW) and surface effects on Tg is not well understood for low MW film systems below the entanglement length. Utilizing atomistically informed coarse-grained molecular dynamics simulations for poly(methyl methacrylate) (PMMA), it is demonstrated that the decrease in free-standing film Tg with respect to bulk is more significant for low MW compared to high MW systems. Investigation of the local interfacial properties reveals that the increase in the local free volume near the free surface is greater for low MW, explaining the MW dependence of Tg -confinement behaviors. These findings corroborate recent experiments on low MW films, and highlight the relationship between nanoconfinement phenomena and local free volume effects arising from free surfaces.

Systematic Method for Thermomechanically Consistent Coarse-Graining: A Universal Model for Methacrylate-Based Polymers.

We present a versatile systematic two-bead-per-monomer coarse-grain modeling strategy for simulating the thermomechanical behavior of methacrylate polymers at length and time scales far exceeding atomistic simulations. We establish generic bonded interaction parameters via Boltzmann inversion of probability distributions obtained from the common coarse-grain bead center locations of five different methacrylate polymers. Distinguishing features of each monomer side-chain group are captured using Lennard-Jones nonbonded potentials with parameters specified to match the density and glass-transition temperature values obtained from all-atomistic simulations. The developed force field is validated using Flory-Fox scaling relationships, self-diffusion coefficients of monomers, and modulus of elasticity for p(MMA). Our approach establishes a transferable, efficient, and accurate scale-bridging strategy for investigating the thermomechanics of copolymers, polymer blends, and nanocomposites.

Life cycle environmental impacts of selected U.S. ethanol production and use pathways in 2022.

Projected life cycle greenhouse gas (GHG) emissions and net energy value (NEV) of high-ethanol blend fuel (E85) used to propel a passenger car in the United States are evaluated using attributional life cycle assessment. Input data represent national-average conditions projected to 2022 for ethanol produced from corn grain, corn stover, wheat straw, switchgrass, and forest residues. Three conversion technologies are assessed: advanced dry mill (corn grain), biochemical (switchgrass, corn stover, wheat straw), and thermochemical (forest residues). A reference case is compared against results from Monte Carlo uncertainty analysis. For this case, one kilometer traveled on E85 from the feedstock-to-ethanol pathways evaluated has 43%-57% lower GHG emissions than a car operated on conventional U.S. gasoline (base year 2005). Differences in NEV cluster by conversion technology rather than by feedstock. The reference case estimates of GHG and NEV skew to the tails of the estimated frequency distributions. Though not as optimistic as the reference case, the projected median GHG and NEV for all feedstock-to-E85 pathways evaluated offer significant improvement over conventional U.S. gasoline. Sensitivity analysis suggests that inputs to the feedstock production phase are the most influential parameters for GHG and NEV. Results from this study can be used to help focus research and development efforts.