The Effects of Chloride Binding on the Behavior of Cellulose-Derived Solutes in the Ionic Liquid 1‑Butyl-3-methylimidazolium Chloride

The structure and diffusion of various linear and ringed solutes are examined in two different solvents, the ionic liquid 1-butyl-3-methylimidazolium chloride ([BMIM]­Cl) and SPC/E water, using molecular dynamics (MD) simulations. The formation of distinctly ordered local solvent environments around these solutes is observed. Specifically, spatial distribution functions reveal significant ordering of the solvents around the solutes with chloride–hydroxyl group interactions largely dictating these arrangements. Further, a breakdown of the hydrogen bonds that develop between the solute and solvent is provided, showing a relationship between the presence of additional functional groups and the distribution of hydrogen bonds. The diffusivities of the solutes were determined in water at 298 K, 1 bar and [BMIM]Cl at 400 K, 1 bar. The results show that the solutes were approximately 10–100 times more diffusive in water than in [BMIM]­Cl. Within [BMIM]­Cl, diffusivity appears to decrease with increasing strength of the hydroxyl groups present. Additionally, the free energies of solvation of the solutes are determined with COSMO-RS, providing information about their tendencies in forming aggregates. These results are then compared with MD results in which aggregation is quantified through the use of a dispersion measure. Though all solutes remained relatively dispersed in each of the solvents, those with hydroxyl groups were seen to be the most highly dispersed in the solvent [BMIM]­Cl. Further, the dynamic dispersal of a large solute aggregate into [BMIM]Cl was studied, finding that solutes with hydroxyl groups tend to form complexes with the chloride ions. If strong enough, these chlorides can actually bind multiple solutes together into long chains, inhibiting their dispersal in solvent. It is believed that the formation of these chloride–solute complexes is largely responsible for the decreased diffusivity and elevated dispersion seen in simulations with [BMIM]­Cl

Atomistic Potentials for Trisiloxane, Alkyl Ethoxylate, and Perfluoroalkane-Based Surfactants with TIP4P/2005 and Application to Simulations at the Air–Water Interface

The mechanism of superspreading, the greatly enhanced spreading of water droplets facilitated by trisiloxane surfactants, is still under debate, largely because the role and behavior of the surfactants cannot be sufficiently resolved by experiments or continuum simulations. Previous molecular dynamics studies have been performed with simple model molecules or inaccurate models, strongly limiting their explanatory power. Here we present a force field dedicated to superspreading, extending existing quantum-chemistry-based models for the surfactant and the TIP4P/2005 water model (Abascal et al. J. Chem. Phys., 2005, 123, 234505). We apply the model to superspreading trisiloxane surfactants and nonsuperspreading alkyl ethoxylate and perfluoroalkane surfactants at various concentrations at the air–water interface. We show that the developed model accurately predicts surface tensions, which are typically assumed important for superspreading. Significant differences between superspreading and traditional surfactants are presented and their possible relation to superspreading discussed. Although the force field has been developed for superspreading problems, it should also perform well for other simulations involving polymers or copolymers with water

Observed Mechanism for the Breakup of Small Bundles of Cellulose Iα and Iβ in Ionic Liquids from Molecular Dynamics Simulations

Explicit, all-atom molecular dynamics simulations are used to study the breakup of small bundles of cellulose Iα and Iβ in the ionic liquids [BMIM]­Cl, [EMIM]­Ac, and [DMIM]­DMP. In all cases, significant breakup of the bundles is observed with the initial breakup following a common underlying mechanism. Anions bind strongly to the hydroxyl groups of the exterior strands of the bundle, forming negatively charged complexes. Binding also weakens the intrastrand hydrogen bonds present in the cellulose strands, providing greater strand flexibility. Cations then intercalate between the individual strands, likely due to charge imbalances, providing the bulk to push the individual moieties apart and initiating the separation. The peeling of an individual strand from the main bundle is observed in [EMIM]Ac with an analysis of its hydrogen bonds with other strands showing that the chain detaches glucan by glucan from the main bundle in discrete, rapid events. Further analysis shows that the intrastrand hydrogen bonds of each glucan tend to break for a sustained period of time before the interstrand hydrogen bonds break and strand detachment occurs. Examination of similar nonpeeling strands shows that, without this intrastrand hydrogen bond breakage, the structural rigidity of the individual unit can hinder its peeling despite interstrand hydrogen bond breakage

Definition and Computation of Intermolecular Contact in Liquids Using Additively Weighted Voronoi Tessellation

We present a definition of intermolecular surface contact by applying weighted Voronoi tessellations to configurations of various organic liquids and water obtained from molecular dynamics simulations. This definition of surface contact is used to link the COSMO-RS model and molecular dynamics simulations. We demonstrate that additively weighted tessellation is the superior tessellation type to define intermolecular surface contact. Furthermore, we fit a set of weights for the elements C, H, O, N, F, and S for this tessellation type to obtain optimal agreement between the models. We use these radii to successfully predict contact statistics for compounds that were excluded from the fit and mixtures. The observed agreement between contact statistics from COSMO-RS and molecular dynamics simulations confirms the capability of the presented method to describe intermolecular contact. Furthermore, we observe that increasing polarity of the surfaces of the examined molecules leads to weaker agreement in the contact statistics. This is especially pronounced for pure water

Effects of Water Concentration on the Structural and Diffusion Properties of Imidazolium-Based Ionic Liquid–Water Mixtures

We have used molecular dynamics simulations to study the properties of three ionic liquid (IL)–water systems: 1-butyl-3-methylimidazolium chloride ([bmim]­Cl), 1-ethyl-3-methylimidazolium acetate ([emim]­[Ac]), and 1,3-dimethylimidazolium dimethylphosphate ([dmim]­[DMP]). We observe the transition of those mixtures from pure IL to aqueous solution by analyzing the changes in important bulk properties (density) and structural and bonding properties (radial distribution functions, water clustering, hydrogen bonding, and cationic stacking) as well as dynamical properties (diffusion coefficients) at 12 different concentration samplings of each mixture, ranging from 0.0 to 99.95 mol % water. Our simulations revealed across all of the different structural, bonding, and dynamical properties major structural changes consistent with a transition from IL–water mixture to aqueous solution in all three ILs at water concentrations around 75 mol %. Among the structural changes observed were rapid increase in the frequency of hydrogen bonds, both water–water and water–anion. Similarly, at these critical concentrations, the water clusters formed begin to span the entire simulation box, rather than existing as isolated networks of molecules. At the same time, there is a sudden decrease in cationic stacking at the transition point, followed by a rapid increase near 90 mol % water. Finally, the diffusion coefficients of individual cations and anions show a rapid transition from rates consistent with diffusion in IL’s to rates consistent with diffusion in water beginning at 75 mol % water. The location of this transition is consistent, for [bmim]Cl and [dmim]­[DMP], with the water concentration limit above which the ILs are unable to dissolve cellulose

Reconsidering Dispersion Potentials: Reduced Cutoffs in Mesh-Based Ewald Solvers Can Be Faster Than Truncation

Long-range dispersion interactions have a critical influence on physical quantities in simulations of inhomogeneous systems. However, the perceived computational overhead of long-range solvers has until recently discouraged their implementation in molecular dynamics packages. Here, we demonstrate that reducing the cutoff radius for local interactions in the recently introduced particle–particle particle−mesh (PPPM) method for dispersion [Isele-Holder et al., <i>J. Chem. Phys.</i>, <b>2012</b>, <i>137</i>, 174107] can actually often be faster than truncating dispersion interactions. In addition, because all long-range dispersion interactions are incorporated, physical inaccuracies that arise from truncating the potential can be avoided. Simulations using PPPM or other mesh Ewald solvers for dispersion can provide results more accurately and more efficiently than simulations that truncate dispersion interactions. The use of mesh-based approaches for dispersion is now a viable alternative for all simulations containing dispersion interactions and not merely those where inhomogeneities were motivating factors for their use. We provide a set of parameters for the dispersion PPPM method using either <i>i</i><b>k</b> or analytic differentiation that we recommend for future use and demonstrate increased simulation efficiency by using the long-range dispersion solver in a series of performance tests on massively parallel computers

Reconsidering Dispersion Potentials: Reduced Cutoffs in Mesh-Based Ewald Solvers Can Be Faster Than Truncation

Long-range dispersion interactions have a critical influence on physical quantities in simulations of inhomogeneous systems. However, the perceived computational overhead of long-range solvers has until recently discouraged their implementation in molecular dynamics packages. Here, we demonstrate that reducing the cutoff radius for local interactions in the recently introduced particle–particle particle−mesh (PPPM) method for dispersion [Isele-Holder et al., <i>J. Chem. Phys.</i>, <b>2012</b>, <i>137</i>, 174107] can actually often be faster than truncating dispersion interactions. In addition, because all long-range dispersion interactions are incorporated, physical inaccuracies that arise from truncating the potential can be avoided. Simulations using PPPM or other mesh Ewald solvers for dispersion can provide results more accurately and more efficiently than simulations that truncate dispersion interactions. The use of mesh-based approaches for dispersion is now a viable alternative for all simulations containing dispersion interactions and not merely those where inhomogeneities were motivating factors for their use. We provide a set of parameters for the dispersion PPPM method using either <i>i</i><b>k</b> or analytic differentiation that we recommend for future use and demonstrate increased simulation efficiency by using the long-range dispersion solver in a series of performance tests on massively parallel computers

Reconsidering Dispersion Potentials: Reduced Cutoffs in Mesh-Based Ewald Solvers Can Be Faster Than Truncation

Long-range dispersion interactions have a critical influence on physical quantities in simulations of inhomogeneous systems. However, the perceived computational overhead of long-range solvers has until recently discouraged their implementation in molecular dynamics packages. Here, we demonstrate that reducing the cutoff radius for local interactions in the recently introduced particle–particle particle−mesh (PPPM) method for dispersion [Isele-Holder et al., <i>J. Chem. Phys.</i>, <b>2012</b>, <i>137</i>, 174107] can actually often be faster than truncating dispersion interactions. In addition, because all long-range dispersion interactions are incorporated, physical inaccuracies that arise from truncating the potential can be avoided. Simulations using PPPM or other mesh Ewald solvers for dispersion can provide results more accurately and more efficiently than simulations that truncate dispersion interactions. The use of mesh-based approaches for dispersion is now a viable alternative for all simulations containing dispersion interactions and not merely those where inhomogeneities were motivating factors for their use. We provide a set of parameters for the dispersion PPPM method using either <i>i</i><b>k</b> or analytic differentiation that we recommend for future use and demonstrate increased simulation efficiency by using the long-range dispersion solver in a series of performance tests on massively parallel computers

Translational Entropy and Dispersion Energy Jointly Drive the Adsorption of Urea to Cellulose

The adsorption of urea on cellulose at room temperature has been studied using adsorption isotherm experiments and molecular dynamics (MD) simulations. The immersion of cotton cellulose into bulk urea solutions with concentrations between 0.01 and 0.30 g/mL led to a decrease in urea concentration in all solutions, allowing the adsorption of urea on the cellulose surface to be measured quantitatively. MD simulations suggest that urea molecules form sorption layers on both hydrophobic and hydrophilic surfaces. Although electrostatic interactions accounted for the majority of the calculated interaction energy between urea and cellulose, dispersion interactions were revealed to be the key driving force for the accumulation of urea around cellulose. The preferred orientation of urea and water molecules in the first solvation shell varied depending on the nature of the cellulose surface, but urea molecules were systematically oriented parallel to the hydrophobic plane of cellulose. The translational entropies of urea and water molecules, calculated from the velocity spectrum of the trajectory, are lower near the cellulose surface than in bulk. As urea molecules adsorb on cellulose and expel surface water into the bulk, the increase in the translational entropy of the water compensated for the decrease in the entropy of urea, resulting in a total entropy gain of the solvent system. Therefore, the cellulose–urea dispersion energy and the translational entropy gain of water are the main factors that drive the adsorption of urea on cellulose