Equilibration of linear polyethylene melts with pre-defined molecular weight distributions employing united atom Monte Carlo simulations.

Possessing control over the molecular size (molecular weight/chain length/degree of polymerization) distribution of a polymeric material is extremely important in applications. This is manifested de facto by the extensive contemporary scientific literature on processes for controlling this distribution experimentally. Yet, the literature on computational techniques for achieving prescribed molecular size distributions in simulations and exploring their impact on properties is much less abundant than its experimental/technical counterpart. Here, we develop-on the basis of united atom melt simulations employing connectivity-altering Monte Carlo moves-a new Metropolis selection criterion that drives the multichain system to a prescribed but otherwise arbitrary distribution of molecular sizes. The new formulation is a generalization of that originally proposed [P. V. K. Pant and D. N. Theodorou, Macromolecules 28, 7224 (1995)], but simpler and more computationally efficient. It requires knowledge solely of the target distribution, which need not be normalized. We have implemented the new formulation on long-chain linear polyethylene melts, obtaining excellent results. The target molecular size distribution can be provided in tabulated form, allowing absolute freedom as to the types of chain size profiles that can be simulated. Distributions for which equilibration has been achieved here for linear polyethylene include a truncated most probable, a truncated Schulz-Zimm, an arbitrary one defined in tabulated form, a broad truncated Gaussian, and a bimodal Gaussian. The last two are comparable to those encountered in industrial applications. The impact of the molecular size distribution on the properties of the simulated melts, such as density, chain dimensions, and mixing thermodynamics, is explored.

Development of a Meshless Kernel-Based Scheme for Particle-Field Brownian Dynamics Simulations.

We develop a meshless discretization scheme for particle-field Brownian dynamics simulations. The density is assigned on the particle level using a weighting kernel with finite support. The system's free energy density is derived from an equation of state (EoS) and includes a square gradient term. The numerical stability of the scheme is evaluated in terms of reproducing the thermodynamics (equilibrium density and compressibility) and dynamics (diffusion coefficient) of homogeneous samples. Using a reduced description to simplify our analysis, we find that numerical stability depends strictly on reduced reference compressibility, kernel range, time step in relation to the friction factor, and reduced external pressure, the latter being relevant under isobaric conditions. Appropriate parametrization yields precise thermodynamics, further improved through a simple renormalization protocol. The dynamics can be restored exactly through a trivial manipulation of the time step and friction coefficient. A semiempirical formula for the upper bound on the time step is derived, which takes into account variations in compressibility, friction factor, and kernel range. We test the scheme on realistic mesoscopic models of fluids, involving both simple (Helfand) and more sophisticated (Sanchez-Lacombe) equations of state.

Interactions of a Novel Anthracycline with Oligonucleotide DNA and Cyclodextrins in an Aqueous Environment.

Berubicin, a chemotherapy medication belonging to the class of anthracyclines, is simulated in double-stranded DNA sequences and cyclodextrins in an aqueous environment via full-atom molecular dynamics simulations on the time scale of microseconds. The drug is studied in both the neutral and protonated states so as to better comprehend the role of its charge in the formed complexes. The noncovalent berubicin-DNA and berubicin-cyclodextrin complexes are investigated in detail, paying special attention to their thermodynamic description by employing the double decoupling method, the solvent balance method, the weighted solvent accessible surface model, and the linear interaction energy method. A novel approach for extracting the desolvation thermodynamics of the binding process is also presented. Both the binding and desolvation Gibbs energies are decomposed into entropic and enthalpic contributions so as to elucidate the nature of complexation and its driving forces. Selected structural and geometrical properties of all the complexes, which are all stable, are analyzed. Both cyclodextrins under consideration are widely utilized for drug delivery purposes, and a comparative investigation between their bound states with berubicin is carried out.

Buckling kinetics of graphene membranes under uniaxial compression.

Despite past investigations of the buckling instability, the kinetics of the buckling process is not well understood. We develop a generic framework for determining the buckling kinetics of membranes under compressive stress (σ_{b}) via molecular dynamics simulations. The buckling time (t_{b}) is modeled by an extended Boltzmann-Arrhenius-Zhurkov equation accounting for temperature (T) and scale-dependent bending rigidity. We discern three regimes: (I) t_{b} decreases with T; (II) t_{b} increases with T; (III) t_{b} is T independent. Regime II coheres with the predictions of the theory of fluctuating sheets (TFS). Regime I is seen at small scales due to fluctuations about equilibrium and is not predicted by the TFS.

Solvation Free Energy of Dilute Grafted (Nano)Particles in Polymer Melts via the Self-Consistent Field Theory.

Predicting the distribution of a chemical species across multiple phases is of critical importance to environmental protection, pharmaceuticals, and high added-value chemicals. Computationally, this problem is addressed by determining the free energy of solvation of the species in the different phases using a well-established thermodynamic formulation. Following recent developments in sterically stabilized colloids and nanocomposite materials, the solvation of polymer-grafted nanoparticles in different solvents or polymer melts has become relevant. We develop a Self-Consistent Field theoretical framework to determine the solvation free energy of grafted particles inside a molten polymer matrix phase at low concentrations. The solvation free energy is calculated based on the notion of a pseudochemical potential introduced by Ben-Naim. Grafted and matrix chains are taken to be of the same chemical constitution, but their lengths are varied systematically, as are the particle radius and the areal density of grafted chains. In addition, different affinities between the nanoparticle core and the polymer (contact angles) are considered. At very low or very high amounts of grafted material, solvation depends on the adhesion tension between the bare particle and the matrix or on the surface tension of the grafted polymer, respectively. The dependence of the solvation free energy on molecular characteristics is more complicated at intermediate grafting densities and high curvatures, where the contribution of the entropy of grafted chains becomes significant. In general, solvation is less favored in cases where the matrix chains are much shorter than the grafted ones. The former tend to penetrate and swell the brush, thus generating conformational and translational entropy penalties. This effect becomes more pronounced when considering large particles since the grafted chains have less available space and extend more. For extremely low amounts of grafted material, we observe the opposite trend, albeit weak. Based on our calculations, we propose a generic model for estimating the solvation free energies of grafted nanoparticles in polymer melts from their molecular characteristics. The model and associated SCF formulation, illustrated here for chemically identical grafted and matrix chains, can be extended to obtain partition coefficients of grafted nanoparticles between different polymer melts.

Molecular simulations of fluoxetine in hydrated lipid bilayers, as well as in aqueous solutions containing ß-cyclodextrin.

Fluoxetine, which is a well-known antidepressant drug, is studied in hydrated cholesterol-free and cholesterol-containing lipid bilayers through unbiased and biased atomistic molecular dynamics simulations. The latter are conducted for the calculation of the potential of mean force (PMF) of fluoxetine along an axis perpendicular to the two leaflets of the bilayer. The PMF indicates that the drug prefers to reside inside the lipid phase and allows us to calculate important thermodynamic properties, such as the Gibbs energy difference of partitioning from the water to the lipid phase and the Gibbs energy barrier for hopping events between the two leaflets of the bilayer. The results from the biased simulations are in accord with the mass density profiles calculated from the unbiased simulations. Moreover, we estimate the effect of fluoxetine mole fraction on the order parameters of the lipid alkyl chains and on the area per lipid. It is also found that fluoxetine forms a hydrogen bond network with lipids and water molecules penetrating into the lipid phase. In addition, fluoxoetine is studied in detail in aqueous solutions containing ß-cyclodextrin. It is observed from unbiased molecular dynamics simulations that the two aforementioned molecules form a noncovalent complex spontaneously and the calculated binding free energy is in agreement with the literature.

A coarse-grained model for capturing the helical behavior of isotactic polypropylene.

Understanding the process-property relations of helical polymers using molecular simulations has been an attractive research field over the years. Specifically, isotactic polypropylene still remains a challenge for current computational experimentation, as it exhibits phenomena such as crystallization that emerge on large spatial and temporal scales. Coarse-graining is an efficient technique for approaching such phenomena, although previous coarse-grained models lack in preserving important atomistic and structural details. In this paper we develop a new coarse-grained model, based on the popular MARTINI force field, that is able to reproduce the helical behavior of isotactic polypropylene. To test the model, the predicted statistical and structural properties (characteristic ratio, density, entanglement molecular weight, solubility parameter in the melt) are compared with previous simulation results and available experimental data. For the development of the new coarse-grained force field, a single unperturbed chain Monte Carlo algorithm has been implemented: an efficient algorithm which samples conformations representative of a melt by simulating just a single chain.

Multiscale simulations of polyzwitterions in aqueous bulk solutions and brush array configurations.

Zwitterionic polymers are very promising candidates for antifouling materials that exhibit high chemical stability as compared to polyethylene glycol-based systems. A number of simulation and experimental studies have emerged over recent years for the investigation of sulfobetaine-based zwitterionic polymers. Investigating the structural and thermodynamic properties of such polymers requires access to broad time and length regimes, thus necessitating the development of multiscale simulation strategies. The present article advocates a mesoscopic dissipative particle dynamics (DPD) model capable of addressing a wide range of time and length scales. The mesoscopic force field was developed hand-in-hand with atomistic simulations based on the OPLS force field through a bottom-up parameterization procedure that matches the atomistically calculated strand-length, strand-angle and pair distribution functions. The DPD model is validated against atomistic simulations conducted in this work, and against relevant atomistic simulation studies, theoretical predictions and experimental correlations from the literature. Properties examined include the conformations of SPE polymers in dilute bulk aqueous solution, the density profile and thickness of brush arrays as functions of the grafting density and chain length. In addition, we compute the potential of mean force of an approaching hydrophilic or hydrophobic foulant via umbrella sampling as a function of its position relative to the poly-zwitterion-covered surface. The aforementioned observables lead to important insights regarding the conformational tendencies of grafted polyzwitterions and their antifouling properties.

In silico study of levodopa in hydrated lipid bilayers at the atomistic level.

This article presents atomistic molecular dynamics and umbrella sampling simulations of levodopa at various concentrations in hydrated cholesterol-free 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC) and cholesterol-containing 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) bilayers. Levodopa is the standard medication for Parkinson's disease and is marketed under various trade names; in the context of this article, the levodopa molecule is mostly studied in its zwitterionic form but some results concerning the neutral levodopa are presented as well for comparison purposes. The motivation is to study in detail how levodopa behaves in different hydrated lipid membranes, primarily from the thermodynamic point of view, and reveal aspects of mechanism of its permeation through them. Dependencies of properties on the levodopa concentration are also investigated. Special attention is paid to the calculation of mass density profiles, order parameters and self-diffusion coefficients. Levodopa zwitterions, which form a hydrogen bond network with water and phospholipid molecules, are found to be preferentially located at the water/lipid interface, as well as in the aqueous phase surrounding the cholesterol-free and cholesterol-containing bilayers. This is concluded from the potentials of mean force calculated by umbrella sampling simulations as levodopa is transferred from the lipid to the aqueous phase along an axis perpendicular to the two leaflets of the membranes.

Potential of Mean Force between Bare or Grafted Silica/Polystyrene Surfaces from Self-Consistent Field Theory.

We investigate single and opposing silica plates, either bare of grafted, in contact with vacuum or melt phases, using self-consistent field theory. Solid-polymer and solid-solid nonbonded interactions are described by means of a Hamaker potential, in conjunction with a ramp potential. The cohesive nonbonded interactions are described by the Sanchez-Lacombe or the Helfand free energy densities. We first build our thermodynamic reference by examining single surfaces, either bare or grafted, under various wetting conditions in terms of the corresponding contact angles, the macroscopic wetting functions (i.e., the work of cohesion, adhesion, spreading and immersion), the interfacial free energies and brush thickness. Subsequently, we derive the potential of mean force (PMF) of two approaching bare plates with melt between them, each time varying the wetting conditions. We then determine the PMF between two grafted silica plates separated by a molten polystyrene film. Allowing the grafting density and the molecular weight of grafted chains to vary between the two plates, we test how asymmetries existing in a real system could affect steric stabilization induced by the grafted chains. Additionally, we derive the PMF between two grafted surfaces in vacuum and determine how the equilibrium distance between the two grafted plates is influenced by their grafting density and the molecular weight of grafted chains. Finally, we provide design rules for the steric stabilization of opposing grafted surfaces (or fine nanoparticles) by taking account of the grafting density, the chain length of the grafted and matrix chains, and the asymmetry among the opposing surfaces.

Structure and thermodynamics of grafted silica/polystyrene dilute nanocomposites investigated through self-consistent field theory.

Polymer/matrix nanocomposites (PNCs) are materials with exceptional properties. They offer a plethora of promising applications in key industrial sectors. In most cases, it is preferable to disperse the nanoparticles (NPs) homogeneously across the matrix phase. However, under certain conditions NPs might lump together and lead to a composite material with undesirable properties. A common strategy to stabilize the NPs is to graft on their surface polymer chains of the same chemical constitution as the matrix chains. There are several unresolved issues concerning the optimal molar mass and areal density of grafted chains that would ensure best dispersion, given the nanoparticles and the polymer matrix. We propose a model for the prediction of key structural and thermodynamic properties of PNC and apply it to a single spherical silica (SiO2) nanoparticle or planar surface grafted with polystyrene chains embedded at low concentration in a matrix phase of the same chemical constitution. Our model is based on self-consistent field theory, formulated in terms of the Edwards diffusion equation. The properties of the PNC are explored across a broad parameter space, spanning the mushroom regime (low grafting densities, small NPs and chain lengths), the dense brush regime, and the crowding regime (large grafting densities, NP diameters, and chain lengths). We extract several key quantities regarding the distributions and the configurations of the polymer chains, such as the radial density profiles and their decomposition into contributions of adsorbed and free chains, the chains/area profiles, and the tendency of end segments to segregate at the interfaces. Based on our predictions concerning the brush thickness, we revisit the scaling behaviors proposed in the literature and we compare our findings with experiment, relevant simulations, and analytic models, such as Alexander's model for incompressible brushes.

Kinetic concepts and local failure in the interfacial shear strength of epoxy-graphene nanocomposites.

Interfacial shear strength (IFSS) is a key property in the design of composites and nanocomposites. Many simulation studies quantify the interfacial characteristics of sandwichlike specimens in terms of the IFSS and pullout force; a common feature of these studies is that they employ finite model systems and are therefore subject to strong finite size effects. We propose an alternative approach which is applicable to both aperiodic and periodic computational specimens. The interfaces are subjected to multiple shear deformation simulations over a wide range of temperatures (T) and shear stresses (σ_{zx}). From these simulations we collect the failure times (t_{f}); by analyzing them in the framework of an extended Boltzmann-Arrhenius-Zhurkov kinetic equation we derive the IFSS, the limiting stress for barrierless transitions, the activation energy, the activation volume for failure, the sliding velocities, and a local elastic shear modulus for the interface. We test our methodology on epoxy diglycidyl ether bisphenol F-diethyl toluene diamine interfaces in contact with (i) pristine graphene, (ii) graphene with single-atom vacancies, and (iii) graphene with hydroxyl-ΟΗ groups. Differences in the mechanism of interfacial failure among these three systems are discussed.

Promising Route for the Development of a Computational Framework for Self-Assembly and Phase Behavior Prediction of Ionic Surfactants Using MARTINI.

Surfactants are amphiphilic molecules with multiple uses and industrial applications as detergents, wetting agents, emulsifiers, and so forth. They can be divided into three main categories: nonionic, ionic, and zwitterionic. The development of a universal computational framework able to predict key properties such as their critical micelle concentration (cmc) and the size of the micelles they form and to ultimately extract phase diagrams for their aqueous solutions, possibly in the presence of salts and oils, using their chemical constitution as input, would provide valuable information for the design and the production of these materials. In this work, we focus on ionic surfactants and investigate a possible route toward the development of such a framework based on coarse-grained simulations using the MARTINI forcefield in two versions: its implicit solvent version, called Dry MARTINI, and its explicit solvent version, called Wet MARTINI. The surfactants considered in our efforts are the anionic sodium dodecyl sulfate (SDS) and the three cationic cetyl, dodecyl, and octyl trimethyl ammonium bromide (CTAB, DTAB, and OTAB, respectively). First, we choose their mapping onto coarse-grained MARTINI beads. Next, we estimate their cmc's, their peak aggregation numbers, Nagg, and in the case of SDS, its small angle neutron scattering pattern at low concentrations, applying the Dry MARTINI forcefield. With a single modification to the Lennard-Jones energy parameter between hydrophobic beads and invoking Ewald summation with a physically meaningful dielectric constant for electrostatic interactions, our estimates are in very good agreement with experimental results. Furthermore, we predict the phase behavior of SDS/water and CTAB/water binary solutions using Wet MARTINI and find semiquantitative agreement with experimental phase diagrams. We conclude that the MARTINI forcefield, with careful treatment of electrostatic interactions and appropriate modification of parameters for some key functional groups, can be a powerful ally in the quest for a universal computational framework for the design of new surfactants with improved properties.

Molecular Simulations and Mechanistic Analysis of the Effect of CO2 Sorption on Thermodynamics, Structure, and Local Dynamics of Molten Atactic Polystyrene.

A simulation strategy encompassing different scales was applied to the systematic study of the effects of CO2 uptake on the properties of atactic polystyrene (aPS) melts. The analysis accounted for the influence of temperature between 450 and 550 K, polymer molecular weights (M w) between 2100 and 31000 g/mol, and CO2 pressures up to 20 MPa on the volumetric, swelling, structural, and dynamic properties of the polymer as well as on the CO2 solubility and diffusivity by performing molecular dynamics (MD) simulations of the system in a fully atomistic representation. A hierarchical scheme was used for the generation of the higher M w polymer systems, which consisted of equilibration at a coarse-grained level of representation through efficient connectivity-altering Monte Carlo simulations, and reverse-mapping back to the atomistic representation, obtaining the configurations used for subsequent MD simulations. Sorption isotherms and associated swelling effects were determined by using an iterative procedure that incorporated a series of MD simulations in the NPT ensemble and the Widom test particle insertion method, while CO2 diffusion coefficients were extracted from long MD runs in the NVE ensemble. Solubility and diffusivity compared favorably with experimental results and with predictions of the Sanchez-Lacombe equation of state, which was reparametrized to capture the M w dependence of polymer properties with greater accuracy. Structural features of the polymer matrix were correctly reproduced by the simulations, and the effects of gas concentration and M w on structure and local dynamics were thoroughly investigated. In the presence of CO2, a significant acceleration of the segmental dynamics of the polymer occurred, more pronouncedly at low M w. The speed-up effect caused by the swelling agent was not limited to the chain ends but affected the whole chain in a similar fashion.

Molecular Modeling Investigations of Sorption and Diffusion of Small Molecules in Glassy Polymers.

With a wide range of applications, from energy and environmental engineering, such as in gas separations and water purification, to biomedical engineering and packaging, glassy polymeric materials remain in the core of novel membrane and state-of the art barrier technologies. This review focuses on molecular simulation methodologies implemented for the study of sorption and diffusion of small molecules in dense glassy polymeric systems. Basic concepts are introduced and systematic methods for the generation of realistic polymer configurations are briefly presented. Challenges related to the long length and time scale phenomena that govern the permeation process in the glassy polymer matrix are described and molecular simulation approaches developed to address the multiscale problem at hand are discussed.

Molecular dynamics simulations of EPON-862/DETDA epoxy networks: structure, topology, elastic constants, and local dynamics.

Structural, topological, mechanical and dynamical properties of EPON-862/DETDA epoxy networks are investigated with Molecular Dynamics (MD) simulations. The epoxy networks are composed of the resin Diglycidyl Ether Bisphenol F (DGEBF), also known as EPON-862, and the hardener Diethyl Toluene Diamine (DETDA). Systems with four different crosslinking degrees are examined; the effect of the degree of crosslinking on studied properties is thus determined. The computed quantities are retrieved by employing several simulation strategies and numerical methods of statistical mechanics in order to gain a rigorous and solid understanding of the aforementioned properties as well as to assess the accuracy and applicability of the methods employed. We quantify and analyze the local structure of the EPON-862/DETDA epoxy networks through the partial pair distribution functions, the Faber-Ziman partial structure factors and through simulated X-ray diffraction patterns, demonstrating good agreement with an experimental spectrum from a similar epoxy resin. The topology of the networks is examined with the aim of assessing percolation of connectivity, the properties of network fragments (subnetworks), and the distribution of functionalities of the crosslinks. The elastic constants of the systems are retrieved by employing two equilibrium (analysis of volume fluctuations, Parrinello-Rahman strain fluctuation relation) and one nonequilibrium (uniaxial tension/compression deformations at prescribed rate) method. Finally, the glass temperatures of the systems are estimated by calculating the density as a function of temperature and by analyzing the reorientational dynamics of bond vectors which describe relaxation processes at the segment level.

SimNano: A Trust Region Strategy for Large-Scale Molecular Systems Energy Minimization Based on Exact Second-Order Derivative Information.

In this work, a new energy minimization strategy is presented that achieves better convergence properties than the standard algorithms employed in the field (fewer steps and usually a lower minimum) and is also computationally efficient; therefore, it becomes suitable for dealing with large-scale molecular systems. The proposed strategy is integrated into the SimNano energy minimization platform that is also described herein. SimNano relies on the analytical calculation of the molecular systems' gradient vectors and Hessian matrices using the computational modeling framework proposed by the authors ( Chatzieleftheriou , S. ; Adendorff , M. R. ; Lagaros , N. D. Generalized Potential Energy Finite Elements for Modeling Molecular Nanostructures . J. Chem. Inf. Model. 2016 , 56 ( 10 ), 1963 - 1978 ). The basis of the proposed minimization strategy is a trust region algorithm based on exact second-order derivative information. Taking advantage of the Hessian matrices' sparsity, a specialized treatment of the data structure is implemented. The latter is beneficial and often rather necessary, especially in the case of large-scale molecular systems, improving the speed and reducing the memory requirements. In order to demonstrate the efficiency of the proposed energy minimization strategy, several test examples are examined, and the results achieved are compared with those obtained by one of the most popular molecular simulation software packages, i.e., the Large-Scale Atomic/Molecular Massively Parallel Simulator (LAMMPS). The results indicate that the proposed minimization strategy exhibits superior convergence properties compared with the typical algorithms (i.e., nonlinear conjugate gradient algorithm, limited-memory Broyden-Fletcher-Goldfarb-Shanno (LBFGS) algorithm, etc.). The SimNano energy minimization platform can be downloaded from the site http://users.ntua.gr/nlagaros/simnano.html , enabling researchers in the field to build molecular systems and perform energy minimization runs using input files in LAMMPS format.

Thermodynamic Analysis of n-Hexane-Ethanol Binary Mixtures Using the Kirkwood-Buff Theory.

A complete thermodynamic analysis of mixtures consisting of molecules with complex chemical constitution can be rather demanding. The Kirkwood-Buff theory of solutions allows the estimation of thermodynamic properties, which cannot be directly extracted from atomistic simulations, such as the Gibbs energy of mixing (Δmix G). In this work, we perform molecular dynamics simulations of n-hexane-ethanol binary mixtures in the liquid state under two temperature-pressure conditions and at various mole fractions. On the basis of the recently published methodology of Galata [ Fluid Phase Equilib. 2018 , 470 , 25 - 37 ] , we first calculate the Kirkwood-Buff integrals in the isothermal-isobaric ( NpT) ensemble, identifying how system size affects their estimation. We then extract the activity coefficients, excess Gibbs energy, excess enthalpy, and excess entropy for the n-hexane-ethanol binary mixtures we simulate. We employ two approaches for quantifying composition fluctuations: one based on counting molecular centers of mass and a second one based on counting molecular segments. Results from the two approaches are practically indistinguishable. We compare our results against predictions of vapor-liquid equilibria obtained in a previous simulation work using the same force field, as well as with experimental data, and find very good agreement. In addition, we develop a simple methodology to identify the hydrogen bonds between ethanol molecules and analyze their effects on mixing properties.

Multiscale Molecular Simulations of Polymer-Matrix Nanocomposites: or What Molecular Simulations Have Taught us About the Fascinating Nanoworld.

Following the substantial progress in molecular simulations of polymer-matrix nanocomposites, now is the time to reconsider this topic from a critical point of view. A comprehensive survey is reported herein providing an overview of classical molecular simulations, reviewing their major achievements in modeling polymer matrix nanocomposites, and identifying several open challenges. Molecular simulations at multiple length and time scales, working hand-in-hand with sensitive experiments, have enhanced our understanding of how nanofillers alter the structure, dynamics, thermodynamics, rheology and mechanical properties of the surrounding polymer matrices.