Challenge to Reconcile Experimental Micellar Properties of the CnEm Nonionic Surfactant Family

Computational predictions of interfacial tension, surface tension, and surfactant adsorption isotherms

All-atom (AA) molecular dynamics (MD) simulations are employed to predict interfacial tensions (IFT) and surface tensions (ST) of both ionic and non-ionic surfactants. The general AMBER force field (GAFF) and variants are examined in terms of their performance in predicting accurate IFT/ST, γ, values for chosen water models, together with the hydration free energy, ΔGhyd, and density, ρ, predictions for organic bulk phases. A strong correlation is observed between the quality of ρ and γ predictions. Based on the results, the GAFF-LIPID force field, which provides improved ρ predictions is selected for simulating surfactant tail groups. Good γ predictions are obtained with GAFF/GAFF-LIPID parameters and the TIP3P water model for IFT simulations at a water-triolein interface, and for GAFF/GAFF-LIPID parameters together with the OPC4 water model for ST simulations at a water-vacuum interface. Using a combined molecular dynamics-molecular thermodynamics theory (MD-MTT) framework, a mole fraction of C12E6 molecule of 1.477 × 10-6 (from the experimental critical micelle concentration, CMC) gives a simulated surface excess concentration, ΓMAX, of 76 C12E6 molecules at a 36 nm2 water-vacuum surface (3.5 × 10-10 mol cm-2), which corresponds to a simulated ST of 35 mN m-1. The results compare favourably with an experimental ΓMAX of C12E6 of 3.7 × 10-10 mol cm-2 (80 surfactants for a 36 nm2 surface) and experimental ST of C12E6 of 32 mN m-1 at the CMC.

Predicting surfactant phase behavior with a molecularly informed field theory

HYPOTHESIS

The computational study of surfactants and self-assembly is challenging because 1) models need to reflect chemistry-specific interactions, and 2) self-assembled structures are difficult to equilibrate with conventional molecular dynamics. We propose to overcome these challenges with a multiscale simulation approach where relative entropy minimization transfers chemically-detailed information from all-atom (AA) simulations to coarse-grained (CG) models that can be simulated using field-theoretic methods. Field-theoretic simulations are not limited by intrinsic physical time scales like diffusion and allow for rigorous equilibration via free energy minimization. This approach should enable the study of properties that are difficult to obtain by particle-based simulations.

SIMULATION WORK

We apply this workflow to sodium dodecylsulfate. To ensure chemical fidelity we present an AA force field calibrated against interfacial tension experiments. We generate CG models from AA simulation trajectories and show that particle-based and field-theoretic simulations of the CG model reproduce AA simulations and experimental measurements.

FINDINGS

The workflow captures the complex balance of interactions in a multicomponent system ultimately described by an atomistic model. The resulting CG models can study complex 3D phases like double or alternating gyroids, and reproduce salt effects on properties like aggregation number and shape transitions.

A many-body dissipative particle dynamics parametrisation scheme to study behaviour at air-water interfaces

In this article, we present a general parametrisation scheme for many-body dissipative particle dynamics (MDPD). The scheme is based on matching model components to experimental surface tensions and chemical potentials. This allows us to obtain the correct surface and mixing behaviours of complex, multicomponent systems. The methodology is tested by modelling the behaviour of nonionic polyoxyethylene alkyl ether surfactants at an air/water interface. In particular, the influence of the number of ethylene oxide units in the surfactant head group is investigated. We find good agreement with many experimentally obtained parameters, such as minimum surface area per molecule; and a decrease in the surface tension with increasing surfactant surface density. Moreover, we observe an orientational transition, from surfactants lying directly on the water surface at low surface coverage, to surfactants lying parallel or tilted with respect to the surface normal at high surface coverage. The parametrisation scheme is also extended to cover the zwitterionic surfactant lauryldimethylamine oxide (LDAO), where we provide good predictions for the surface tension at maximum surface coverage. Here, if we exceed this coverage, we are able to demonstrate the spontaneous production of micelles from the surface surfactant layer.

Phase Behavior of Alkyl Ethoxylate Surfactants in a Dissipative Particle Dynamics Model

We present a dissipative particle dynamics (DPD) model capable of capturing the liquid state phase behavior of nonionic surfactants from the alkyl ethoxylate (C_nE_m) family. The model is based upon our recent work [Anderson et al. J. Chem. Phys. 2017, 147, 094503] but adopts tighter control of the molecular structure by setting the bond angles with guidance from molecular dynamics simulations. Changes to the geometry of the surfactants were shown to have little effect on the predicted micelle properties of sampled surfactants, or the water-octanol partition coefficients of small molecules, when compared to the original work. With these modifications the model is capable of reproducing the binary water-surfactant phase behavior of nine surfactants (C₈E₄, C₈E₅, C₈E₆, C₁₀E₄, C₁₀E₆, C₁₀E₈, C₁₂E₆, C₁₂E₈, and C₁₂E₁₂) with a good degree of accuracy.

Inverse ISAsomes in Bio-Compatible Oils—Exploring Formulations in Squalane, Triolein and Olive Oil

In contrast to their more common counterparts in aqueous solutions, inverse ISAsomes (internally self-assembled somes/particles) are formulated as kinetically stabilised dispersions of hydrophilic, lyotropic liquid-crystalline (LC) phases in non-polar oils. This contribution reports on their formation in bio-compatible oils. We found that it is possible to create inverse hexosomes, inverse micellar cubosomes (Fd3m) and an inverse emulsified microemulsion (EME) in excess squalane with a polyethylene glycol alkyl ether as the primary surfactant forming the LC phase and to stabilise them with hydrophobised silica nanoparticles. Furthermore, an emulsified -phase and inverse hexosomes were formed in excess triolein with the triblock-copolymer Pluronic® P94 as the primary surfactant. Stabilisation was achieved with a molecular stabiliser of type polyethylene glycol (PEG)-dipolyhydroxystearate. For the inverse hexosomes in triolein, the possibility of a formulation without any additional stabiliser was explored. It was found that a sufficiently strong stabilisation effect was created by the primary surfactant alone. Finally, triolein was replaced with olive oil which also led to the successful formation of inverse hexosomes. As far as we know, there exists no previous contribution about inverse ISAsomes in complex oils such as triolein or plant oils, and the existence of stabiliser-free (i.e., self-stabilising) inverse hexosomes has also not been reported until now.

Influence of Temperature and Concentration on the Self-Assembly of Nonionic CiEj Surfactants: A Light Scattering Study

Nonionic poly(ethylene oxide) alkyl ether (C_iE_j) surfactants self-assemble into aggregates of various sizes and shapes above their critical micelle concentration (CMC). Knowledge on solution attributes such as CMC as well as aggregate characteristics is crucial to choose the appropriate surfactant for a given application, e.g., as a micellar solvent system. In this work, we used static and dynamic light scattering to measure the CMC, aggregation number (N _agg), and hydrodynamic radius (R _h) of four different C_iE_j surfactants (C₈E₅, C₈E₆, C₁₀E₆, and C₁₀E₈). We examined the influence of temperature, concentration, and molecular structure on the self-assembly in the vicinity of the CMC. A minimum in the CMC vs temperature curve was identified for all surfactants investigated. Further, extending the hydrophilic and hydrophobic chain lengths leads to an increase and decrease of the CMC, respectively. The size of the aggregates strongly depends on temperature. N _agg and R _h increase with increasing temperature for all surfactants investigated. Additionally, N _agg and R _h both increase with increasing surfactant concentration. The data obtained in this work further improve the understanding of the influence of temperature and molecular structure on the self-assembly of C_iE_j surfactants and will further foster their use in micellar solvent systems.

Micellization of Rhamnolipid Biosurfactants and Their Applications in Oil Recovery: Insights from Mesoscale Simulations

The dissipative particle dynamics (DPD) mesoscopic method is used to investigate the self-assembly of rhamnolipid congeners and their aggregation behaviors with paraffins including nonane and pentadecane. The coarse-grained force field is parameterized by combining molecular dynamics (MD) simulations, COSMOtherm calculations, and available experimental data. This model reproduces the vesicular formation of α-l-rhamnopyranosyl-β-hydroxydecanoyl-β-hydroxydecanoate (Rha-C10-C10) reported by all-atom MD simulations. The vesicle composed of Rha-C10-C10 is found to be most stable at a surfactant concentration of 100-146 mM based on asphericity analysis. The architecture of rhamnolipid congeners affects the morphology of their aggregates. Di-rhamno-di-lipidic dRha-C16-C16 forms vesicles with a thicker unilamellar layer of 3.2 nm. Rha-C16-C16 forms vesicles at a lower concentration of 70 mM, but the enclosed water space collapses when the surfactant concentration increases. dRha-C10-C10 forms wormlike micelles, which agglomerate into a torus and interconnected network at higher concentrations. In the presence of alkane molecules, dRha-C10-C10 maintains its wormlike micellar morphology with alkane molecules wrapped inside the aggregates. For Rha-C10-C10, Rha-C16-C16, and dRha-C16-C16, nonane molecules are distributed in the hydrophobic subdomain formed by rhamnolipid molecules. Spherical vesicles are formed at a surfactant concentration of 50 mM and then develop into ellipsoidal vesicles when the concentration increases to 125 mM. When mixed with pentadecane, the alkane molecules are aggregated and surrounded by surfactants forming a core-shell structure at a low surfactant concentration of 20 mM. At higher alkane and surfactant concentrations, the morphologies develop into disk micelles, wormlike micelles, and vesicles, with pentadecane molecules being distributed and packed with rhamnolipids. The obtained simulation results suggest that these biosurfactants have potential as environmental remediation agents.

Model for the Simulation of the CnEm Nonionic Surfactant Family Derived from Recent Experimental Results

Using a comprehensive set of recently published experimental results for training and validation, we have developed computational models appropriate for simulations of aqueous solutions of poly(ethylene oxide) alkyl ethers, an important class of micelle-forming nonionic surfactants, usually denoted C_nE_m. These models are suitable for use in simulations that employ a moderate amount of coarse graining and especially for dissipative particle dynamics (DPD), which we adopt in this work. The experimental data used for training and validation were reported earlier and produced in our laboratory using dynamic light scattering (DLS) measurements performed on 12 members of the C_nE_m compound family yielding micelle size distribution functions and mass-weighted mean aggregation numbers at each of several surfactant concentrations. The range of compounds and quality of the experimental results were designed to support the development of computational models. An essential feature of this work is that all simulation results were analyzed in a way that is consistent with the experimental data. Proper account is taken of the fact that a broad distribution of micelle sizes exists, so mass-weighted averages (rather than number-weighted averages) over this distribution are required for the proper comparison of simulation and experimental results. The resulting DPD force field reproduces several important trends seen in the experimental critical micelle concentrations and mass-averaged mean aggregation numbers with respect to surfactant characteristics and concentration. We feel it can be used to investigate a number of open questions regarding micelle sizes and shapes and their dependence on surfactant concentration for this important class of nonionic surfactants.

A Surface Site Interaction Point Method for Dissipative Particle Dynamics Parametrization: Application to Alkyl Ethoxylate Surfactant Self-Assembly

Dissipative particle dynamics (DPD) is a coarse-grained approach to the simulation of large supramolecular systems, but one limitation has been that the parameters required to describe the noncovalent interactions between beads are not readily accessible. A first-principles computational method has been developed so that bead interaction parameters can be calculated directly from ab initio gas-phase molecular electrostatic potential surfaces of the molecular fragments that represent the beads. A footprinting algorithm converts the molecular electrostatic potential surfaces into a discrete set of surface site interaction points (SSIPs), and these SSIPs are used in the SSIMPLE (surface site interaction model for the properties of liquids at equilibrium) algorithm to calculate the free energies of transfer of one bead into a solution of any other bead. The bead transfer free energies are then converted into the required DPD interaction parameters for all pairwise combinations of different beads. The reliability of the parameters was demonstrated using DPD simulations of a range of alkyl ethoxylate surfactants. The simulations reproduce the experimentally determined values of the critical micelle concentration and mean aggregation number well for all 22 surfactants studied.

Utilizing Machine Learning for Efficient Parameterization of Coarse Grained Molecular Force Fields

We present a machine learning approach to automated force field development in dissipative particle dynamics (DPD). The approach employs Bayesian optimization to parametrize a DPD force field against experimentally determined partition coefficients. The optimization process covers a discrete space of over 40 000 000 points, where each point represents the set of potentials that jointly forms a force field. We find that Bayesian optimization is capable of reaching a force field of comparable performance to the current state-of-the-art within 40 iterations. The best iteration during the optimization achieves an R² of 0.78 and an RMSE of 0.63 log units on the training set of data, these metrics are maintained when a validation set is included, giving R² of 0.8 and an RMSE of 0.65 log units. This work hence provides a proof-of-concept, expounding the utility of coupling automated and efficient global optimization with a top down data driven approach to force field parametrization. Compared to commonly employed alternative methods, Bayesian optimization offers global parameter searching and a low time to solution.

Water Solubility and Surface Property of Alkyl Di-/Tri-/Tetraoxyethyl β-d-Xylopyranosides

Alkyl di-/tri-/tetraoxyethyl β-d-xylopyranosides as derivatives of alkyl xylosides are a class of non-ionic sugar-based surfactants. They were stereoselectively synthesized by the Helferich method. Their properties including hydrophilic-lipophilic balance number, water solubility, surface property, foam property, emulsifying property, and thermotropic liquid crystal property were mainly investigated. The results showed that their water solubility decreased with increasing the alkyl chain length and increasing the number of the oligooxyethyl fragment. The critical micelle concentration had a monotonous decreasing trend with increasing the alkyl chain length. Nonyl di-/tri-/tetraoxyethyl β-d-xylopyranosides [-(OCH₂CH₂)_m-, where m = 2, 3, and 4] exhibited the most excellent foaming ability and foam stability. In the n-octane/water system, dodecyl tetraoxyethyl β-d-xylopyranosides and tetradecyl tetraoxyethyl β-d-xylopyranosides had the strongest emulsion ability. In addition, some alkyl di-/tri-/tetraoxyethyl β-d-xylopyranosides had thermotropic liquid crystal properties. Such sugar-based surfactants, alkyl di-/tri-/tetraoxyethyl β-d-xylopyranosides, will be expected to develop for a variety of practical application.