Comparison of Friction Parametrization from Dynamics and Material Properties for a Coarse-Grained Polymer Melt.

In this work, we extend an approach to coarse-grained (CG) modeling for polymer melts in which the conservative potential is parametrized using the iterative Boltzmann inversion (IBI) method and the accelerated dynamics inherent to IBI are corrected using the dissipative Langevin thermostat with a single tunable friction parameter ( 084114). Diffusive measures from picoseconds to nanoseconds are used to determine the Langevin friction factor to apply to the CG model to recover all-atom (AA) dynamics; the resulting friction factors are then compared for consistency. Here, we additionally parametrize the CG dynamics using a material property, the zero-shear viscosity, which we measure using the Green-Kubo (GK) method.

Dynamically consistent coarse-grain simulation model of chemically specific polymer melts via friction parameterization.

Coarse-grained (CG) models of polymers involve grouping many atoms in an all-atom (AA) representation into single sites to reduce computational effort yet retain the hierarchy of length and time scales inherent to macromolecules. Parameterization of such models is often via "bottom-up" methods, which preserve chemical specificity but suffer from artificially accelerated dynamics with respect to the AA model from which they were derived. Here, we study the combination of a bottom-up CG model with a dissipative potential as a means to obtain a chemically specific and dynamically correct model.

Solvation Free Energy of Self-Assembled Complexes: Using Molecular Dynamics to Understand the Separation of ssDNA-Wrapped Single-Walled Carbon Nanotubes.

Molecular dynamics simulations were used to characterize the self-assembly of single-stranded DNA (ssDNA) on a (6,5) single-walled carbon nanotube (SWCNT) in aqueous solution for the purpose of gaining an improved theoretical understanding of separation strategies for SWCNTs using ssDNA as a dispersant. Four separate ssDNA sequences, ((TAT), TTA(TAT)ATT, C, (GTC)GT), at various levels of loading, were chosen for study based on published experimental work showing selective extraction of particular SWCNT species based on the ssDNA dispersant sequence. We develop a unique workflow based on free energy perturbation (FEP) and use this to determine the relative solubility of these complexes due to the adsorption of the ssDNA on the SWCNT surface, and hence, rank the favorability of separations observed during experiments.

Energy renormalization for coarse-graining polymers having different segmental structures.

Multiscale coarse-grained (CG) modeling of soft materials, such as polymers, is currently an art form because CG models normally have significantly altered dynamics and thermodynamic properties compared to their atomistic counterparts. We address this problem by exploiting concepts derived from the generalized entropy theory (GET), emphasizing the central role of configurational entropy in the dynamics of complex fluids. Our energy renormalization (ER) method involves varying the cohesive interaction strength in the CG models in such a way that dynamic properties related to are preserved.

Solvation of Carbon Nanoparticles in Water/Alcohol Mixtures: Using Molecular Simulation To Probe Energetics, Structure, and Dynamics.

Molecular dynamics simulations were used to examine the solvation behavior of buckminsterfullerene and single-walled carbon nanotubes (SWCNT) in a range of water/alcohol solvent compositions at 1 atm and 300 K. Results indicate that the alcohols assume the role of pseudosurfactants by shielding the nanotube from the more unfavorable interactions with polar water molecules. This is evident in both the free energies of transfer (ΔΔ = -68.

Energy Renormalization for Coarse-Graining the Dynamics of a Model Glass-Forming Liquid.

Coarse-grained modeling achieves the enhanced computational efficiency required to model glass-forming materials by integrating out "unessential" molecular degrees of freedom, but no effective temperature transferable coarse-graining method currently exists to capture dynamics. We address this fundamental problem through an energy-renormalization scheme, in conjunction with the localization model of relaxation relating the Debye-Waller factor ⟨u⟩ to the structural relaxation time τ. Taking ortho-terphenyl as a model small-molecule glass-forming liquid, we show that preserving ⟨u⟩ (at picosecond time scale) under coarse-graining by renormalizing the cohesive interaction strength allows for quantitative prediction of both short- and long-time dynamics covering the entire temperature range of glass formation.

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 as a function of temperature T, i.e.

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 coarse-graining method that allows for modeling of polymer dynamics over a wide temperature range.

Bayesian calibration of coarse-grained forces: Efficiently addressing transferability.

Generating and calibrating forces that are transferable across a range of state-points remains a challenging task in coarse-grained (CG) molecular dynamics. In this work, we present a coarse-graining workflow, inspired by ideas from uncertainty quantification and numerical analysis, to address this problem. The key idea behind our approach is to introduce a Bayesian correction algorithm that uses functional derivatives of CG simulations to rapidly and inexpensively recalibrate initial estimates f0 of forces anchored by standard methods such as force-matching.

Shear and dilational interfacial rheology of surfactant-stabilized droplets.

A new measurement method is suggested that is capable of probing the shear and dilational interfacial rheological responses of small droplets, those of size comparable to real emulsion applications. Freely suspended aqueous droplets containing surfactant and non-surface-active tracer particles are transported through a rectangular microchannel by the plane Poiseuille flow of the continuous oil phase. Optical microscopy and high-speed imaging record the shape and internal circulation dynamics of the droplets.

Tailored distribution of single-wall carbon nanotubes from arc plasma synthesis using magnetic fields.

We report a method for tuning the distribution of single-wall carbon nanotubes (SWCNTs) produced by the anodic arc production method via the application of nonuniform magnetic fields to the gap region during synthesis. Raman, ultraviolet-visible-near-infrared absorbance and near-infrared fluorescence spectroscopies were used to characterize samples together with scanning electron microscopy. Application of the nonuniform magnetic field 0.