Stephen A. Barr

Self-assembly of coarse-grained ionic surfactants accelerated by graphics processing units

Due to the relatively long time scales inherent to ionic surfactant self-assembly (>μs), an aggressive computational approach is needed to obtain converged data on micellar solutions. This work presents a study of micellization using a coarse-grained (CG) model of aqueous ionic surfactants in replicated molecular dynamics (MD) simulations run on graphics processing unit hardware. The performance of our implementation of the CG model with electrostatics into the HOOMD-Blue GPU-accelerated MD software package is comparable to that of a modest sized cluster running a highly optimized parallel CPU code. From 0.36 ms of cumulative trajectory data, we are able to predict equilibrium thermodynamic and morphological properties of ionic surfactant micellar solutions. Estimating the critical micelle concentrations (CMC) from the free monomer (ρ1) and premicellar concentrations obtained from simulations of sodium hexyl sulfate (S6S, CMC of 460 ± 6 mM) at high (1 M) concentration, a value in good agreement with experimental results is obtained; however, the same method applied to simulations of sodium nonyl sulfate (S9S, ρ1 of 2.4 ± 0.01 mM) and sodium dodecyl sulfate (SDS, ρ1 of 0.02 ± 0.01 mM) at the same total concentration systematically underestimates the CMCs. An alternative method for calculating the CMC is presented, where the free monomer concentration computed from high concentration CG-MD data is used as the input to a simple theoretical model which can be used to extrapolate to a more accurate prediction of the CMC. Better agreement between the empirical and predicted CMC is obtained from this theory for S9S (28.7 ± 0.3 mM) and SDS (3.32 ± 0.04 mM), though the CMC for S6S is slightly underestimated (304 ± 3 mM). We also present statistically converged morphological data, including aggregation number distributions and the principal components of the gyration tensor. This data suggest a transition from spherical micelles to rod-like at a specific aggregation number, which increases with increasing hydrocarbon length.

Simulations of Peptide-Graphene Interactions in Explicit Water

The interaction of graphene with biomolecules has a variety of useful applications. In particular, graphitic surfaces decorated with peptides are being considered for high performance biochemical sensors. The interaction of peptides with graphene can also provide insight into the binding behavior of larger biomolecules. In this investigation, we have computed the binding enthalpies of a series of GXG tripeptides with graphene using classical molecular dynamics. Explicit water molecules were included to capture the effect of solvent. Of the twenty amino acid residues examined (X in GXG), arginine, glutamine, and asparagine exhibit the strongest interactions with graphene. Analysis of the trajectories shows that the presence of graphene affects the peptide conformation relative to its conformation in solution. We also find that the peptides favor the graphene interface predominantly due to the influence of the solvent, with hydrophilic residues binding more strongly than hydrophobic residues. These results demonstrate the need to include explicit solvent atoms when modeling peptide-graphene systems to mimic experimental conditions. Furthermore, the scheme outlined herein may be widely applicable for the determination and validation of surface interaction parameters for a host of molecular fragments using a variety of techniques, ranging from coarse-grained models to quantum mechanical methods.

Computation of the binding free energy of peptides to graphene in explicit water

The characteristic properties of graphene make it useful in an assortment of applications. One particular application--the use of graphene in biosensors--requires a thorough understanding of graphene-peptide interactions. In this study, the binding of glycine (G) capped amino acid residues (termed GXG tripeptides) to trilayer graphene surfaces in aqueous solution was examined and compared to results previously obtained for peptide binding to single-layer free-standing graphene [A. N. Camden, S. A. Barr, and R. J. Berry, J. Phys. Chem. B 117, 10691-10697 (2013)]. In order to understand the interactions between the peptides and the surface, binding enthalpy and free energy values were calculated for each GXG system, where X cycled through the typical 20 amino acids. When the GXG tripeptides were bound to the surface, distinct conformations were observed, each with a different binding enthalpy. Analysis of the binding energy showed the binding of peptides to trilayer graphene was dominated by van der Waals interactions, unlike the free-standing graphene systems, where the binding was predominantly electrostatic in nature. These results demonstrate the utility of computational materials science in the mechanistic explanation of surface-biomolecule interactions which could be applied to a wide range of systems.

Interactions Between Charged Surfaces with Ionizable Sites

A key factor controlling the interactions between surfaces in aqueous solutions is the surface charge density. Surfaces typically become charged though a titration process where surface groups can become ionized based on their dissociation constant and the pH of the solution. In this work, we use a Monte Carlo method to treat this process in a system with two planar surfaces with explicitly described ionizable sites in a salt solution. We focus on a system with a surface density of ionizable sites set to 4.8 nm(-2), corresponding to silica. We find that the surface charge density changes as the surfaces come close to contact due to interactions between the ionizable groups on each surface. In addition, we observe an attraction between the surfaces above a threshold surface charge, in good agreement with previous theoretical predictions based on uniformly charged surfaces. However, close to contact we find the force is significantly different than for the uniformly charged case.

Bond breaking in stretched molecules: multi-reference methods versus density functional theory

Several quantum chemistry methods were compared for modeling the breaking of bonds in small molecules subjected to extreme strain. This provides a rigorous test of quantum mechanical methods because a high degree of dynamical and non-dynamical correlation is required to accurately model bond breaking in a strained molecule. The methods tested included multi-reference methods, unrestricted Kohn–Sham density functional theory (DFT) using several functionals, and unrestricted coupled-cluster singles and doubles. It is challenging to employ the multi-reference method in a balanced way for the molecules considered due to the computational cost. While the DFT methods are less costly and provide balanced correlation, they do not have enough static correlation to properly model the bond-breaking curve to dissociation. Despite this, for the N12 DFT method the artifacts due to spin contamination of the unrestricted Kohn–Sham method were the least severe and tolerable. Given this, and the low computational cost, the N12 method was chosen for subsequent dynamical simulations for modeling fracture inception in polymers under extreme strain. The physical characteristics of the bond-breaking process are discussed as well as the influence of secondary conjugation on the process.

Conformational transitions of weak polyacids grafted to nanoparticles

The charge distribution on polyelectrolytes is a key factor, which controls their conformation and interactions. In weak polyelectrolytes, this distribution is determined by a number of factors, including the solvent conditions and local environment. In this work, we investigate charge distributions of chains end-grafted on a spherical nanoparticle in a salt solution, using grand canonical titration Monte Carlo simulations of a coarse-grained polymer model. In this approach, the ionization state of each polymer bead fluctuates based on the dissociation constant, pH of the solution, and interactions with other particles in the system. We determine charge and polymer conformations as functions of the pH and solvent quality. We compare the results to a fixed charge model and also investigate the role of grafting density and the effect of curvature on the film morphologies.

Binding of solvated peptide (EPLQLKM) with a graphene sheet via simulated coarse-grained approach.

Binding of a solvated peptide A1 ((1)E (2)P (3)L (4)Q (5)L (6)K (7)M) with a graphene sheet is studied by a coarse-grained computer simulation involving input from three independent simulated interaction potentials in hierarchy. A number of local and global physical quantities such as energy, mobility, and binding profiles and radius of gyration of peptides are examined as a function of temperature (T). Quantitative differences (e.g., the extent of binding within a temperature range) and qualitative similarities are observed in results from three simulated potentials. Differences in variations of both local and global physical quantities suggest a need for such analysis with multiple inputs in assessing the reliability of both quantitative and qualitative observations. While all three potentials indicate binding at low T and unbinding at high T, the extent of binding of peptide with the temperature differs. Unlike un-solvated peptides (with little variation in binding among residues), solvation accentuates the differences in residue binding. As a result the binding of solvated peptide at low temperatures is found to be anchored by three residues, (1)E, (4)Q, and (6)K (different from that with the un-solvated peptide). Binding to unbinding transition can be described by the variation of the transverse (with respect to graphene sheet) component of the radius of gyration of the peptide (a potential order parameter) as a function of temperature.

Rejection-free Monte Carlo scheme for anisotropic particles

We extend the geometric cluster algorithm [J. Liu and E. Luijten, Phys. Rev. Lett. 92, 035504 (2004)], a highly efficient, rejection-free Monte Carlo scheme for fluids and colloidal suspensions, to the case of anisotropic particles. This is made possible by adopting hyperspherical boundary conditions. A detailed derivation of the algorithm is presented, along with extensive implementation details as well as benchmark results. We describe how the quaternion notation is particularly suitable for the four-dimensional geometric operations employed in the algorithm. We present results for asymmetric Lennard-Jones dimers and for the Yukawa one-component plasma in hyperspherical geometry. The efficiency gain that can be achieved compared to conventional, Metropolis-type Monte Carlo simulations is investigated for rod-sphere mixtures as a function of rod aspect ratio, rod-sphere diameter ratio, and rod concentration. The effect of curved geometry on physical properties is addressed.

Prediction of Incipient Nano-Scale Rupture for Thermosets in Plane Stress

There is limited experimental evidence that fracture nucleation in polymers includes a small number of covalent bond scissions followed by rapid void growth by chemo-mechanical processes. Generalized criteria for predicting such bond scission, then, would help anticipate fracture in polymer matrix composites. Strain states at incipient bond scission for thermoset resins in plane stress are here predicted by atomistic simulation. Several cured epoxy systems were examined, each having a different chain length. For biaxial extension and a portion of the shearing regime, scission occurs at a critical value of the larger principal strain. This value increases with increasing chain length. The corresponding dilatation is largest for biaxial extension and decreases to nearly zero for pure shear. Results are compared with strain invariants at fracture measured from experiments in which polymer matrix composites having various ply stacking sequences were loaded to rupture.

Bond breaking in epoxy systems: A combined QM/MM approach.

A novel method to combine quantum mechanics (QM) and molecular mechanics has been developed to accurately and efficiently account for covalent bond breaking in polymer systems under high strain without the use of predetermined break locations. Use of this method will provide a better fundamental understanding of the mechano-chemical origins of fracture in thermosets. Since classical force fields cannot accurately account for bond breaking, and QM is too demanding to simulate large systems, a hybrid approach is required. In the method presented here, strain is applied to the system using a classical force field, and all bond lengths are monitored. When a bond is stretched past a threshold value, a zone surrounding the bond is used in a QM energy minimization to determine which, if any, bonds break. The QM results are then used to reconstitute the system to continue the classical simulation at progressively larger strain until another QM calculation is triggered. In this way, a QM calculation is only computed when and where needed, allowing for efficient simulations. A robust QM method for energy minimization has been determined, as well as appropriate values for the QM zone size and the threshold bond length. Compute times do not differ dramatically from classical molecular mechanical simulations.