Phase Diagram Study of Sodium Dodecyl Sulfate Using Dissipative Particle Dynamics

A Versatile Approach to Stabilize Liquid-Liquid Interfaces using Surfactant Self-Assembly

Stabilizing liquid-liquid interfaces, whether between miscible or immiscible liquids, is crucial for a wide range of applications, including energy storage, microreactors, and biomimetic structures. In this study, a versatile approach for stabilizing the water-oil interface is presented using the morphological transitions that occur during the self-assembly of anionic, cationic, and nonionic surfactants mixed with fatty acid oils. The morphological transitions underlying this approach are characterized and extensively studied through small-angle X-ray scattering (SAXS), rheometry, and microscopy techniques. Dissipative particle dynamics (DPD) as a simulation tool is adopted to investigate these morphological transitions both in the equilibrium ternary system as well as in the dynamic condition of the water-oil interface. Such a versatile strategy holds promise for enhancing applications such as liquid-in-liquid 3D printing. Moreover, it has the potential to revolutionize a wide range of fields where stabilizing liquid-liquid interfaces not only offers unprecedented opportunities for fine-tuning nanostructural morphologies but also imparts interesting practical features to the resulting liquid shapes. These features include perfusion capabilities, self-healing, and porosity, which could have significant implications for various industries.

Agglomeration inhibition engineering of nickel-cobalt alloys by a sacrificial template for efficient urea electrolysis

Designing efficient non-precious metal-based catalysts for urea oxidation reaction (UOR) is essential for achieving energy-saving hydrogen production and the treatment of wastewater containing ammonia. In this study, sodium dodecyl sulfate (SDS) is employed as a sacrificial template to synthesize NiCo alloy nanowires (NiCo(SDS)/CC), and the instinct formation mechanism is investigated. It is found that SDS can inhibit the Ostwald ripening during hydrothermal and calcination processes, which could release abundant active cobalt, thereby modulating the electronic structure to promote the catalytic reaction. Moreover, SDS as a sacrificial template can induce the deposition of metal atoms and increase the specific surface area of the catalyst, providing abundant active sites to accelerate the reaction kinetics. As expected, the NiCo(SDS)/CC exhibits good activity for both UOR and hydrogen evolution reactions (HER) and it requires only 1.31 V and -86 mV to obtain a current density of ±10 mA cm-2, respectively. This work provides a new strategy for reducing the agglomeration of transition metals to design high-performance composite catalysts for urea oxidation.

Reducing the assemblies of amyloid-beta multimers by sodium dodecyl sulfate surfactant at concentrations lower than critical micelle concentration: molecular dynamics simulation exploration

Amyloid-β peptide, the predominant proteinaceous component of senile plaques, is responsible for the incidence of Alzheimer's disease (AD), an age-associated neurodegenerative disorder. Specifically, the amyloid-β(1-42) (Aβ1-42) isoform, known for its high toxicity, is the predominant biomarker for the preliminary diagnosis of AD. The aggregation of the Aβ1-42 peptides can be affected by the components of the cellular medium through changing their structures and molecular interactions. In this study, we investigated the effect of sodium dodecyl sulfate (SDS) at much lower concentrations than the critical micelle concentration (CMC) on Aβ1-42 aggregation. For this purpose, we studied mono-, di-, tri- and tetramers of Aβ1-42 peptide in two different concentrations of SDS molecules (10 and 40 molecules) using a 300 ns molecular dynamics simulation for each system. The distance between the center of mass (COM) of Aβ1-42 peptides confirms that an increase in the number of SDS molecules decreases their aggregation probability due to greater interaction with SDS molecules. Besides, the less compactness parameter reveals the reduced aggregation probability of Aβ1-42 peptides. Based on the energetic FEL landscapes, SDS molecules with the concentration closer to the CMC are an effective inhibitory agent to prevent the formation of Aβ1-42 fibrils. Also, the aggregation direction of the peptide pairs can be predicted by determining the direction of the accumulation-deterrent forces.Communicated by Ramaswamy H. Sarma.

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.

Investigating anionic surfactant phase diagrams using dissipative particle dynamics: development of a transferable model

Dissipative particle dynamics (DPD) provides a powerful coarse-grained simulation technique for the study of a wide range of soft matter systems. Here, we investigate the transferability of DPD models to the prediction of anionic surfactant phase diagrams, taking advantage of fast parameter sweeps to optimise the choice of DPD parameters for these systems. Parameters are developed which provide a good representation of the phase diagrams of SDS (sodium dodecyl sulfate) and three different isomeric forms of LAS (linear alkylbenzene sulfonates) across an extensive concentration range. A high degree of transferability is seen, with parameters readily transferable to other systems, such as AES (alkyl ether sulfates). Excellent agreement is obtained with experimentally measured quantities, such as the lamellar layer spacing. Isosurfaces are produced from the surfactant head group, from which the second moment M of the isosurface normal distribution is calculated for different phase structures. Lyotropic liquid crystalline phases are characterised by a combination of the eigenvalues of M, radial distribution functions, and visual inspections.

Studying the Structure of Sodium Lauryl Ether Sulfate Solutions Using Dissipative Particle Dynamics

Sodium lauryl ether sulfate (SLES) is a common anionic surfactant used in a large number of personal care products. Commercial products typically contain a distribution in the number of ethoxy groups; despite this, there is limited existing work studying the effect of the ethoxy groups on the phase formation and structure. This is particularly important for the effect the structure has on the viscosity, an important consideration for commercial products. Dissipative particle dynamics is used to simulate the full phase diagram of SLES in water, including both micellar and lyotropic liquid crystal phases. Phase transitions occur at locations which are in good agreement with experimental data, and we find that these boundaries can shift as a result of varying the number of ethoxy groups. Varying the ethoxy groups has a significant effect on the micellar shape and crystalline spacing, with a reduction leading to more nonspherical micelles and decreased periodic spacing of the hexagonal and lamellar phases. Finally, while typical commercial products contain a distribution of ethoxy groups, computational work tends to focus on simulations containing a single chain length. We show that it is valid to use monodisperse simulations to infer behavior about solutions with a polydisperse chain length, based on its mean molecular length.

Phase Diagram Study of Catanionic Surfactants Using Dissipative Particle Dynamics

Dissipative particle dynamics (DPD) simulations has been performed to study the phase transition of a mixture of cationic and anionic surfactants in an aqueous solution as a function of the total concentration in water and the relative ratio of surfactants. The impact of the relative difference between the tail lengths of the cationic and anionic surfactants on the phase diagram has been simulated by tuning the number of DPD beads in the simulation model. This research also discusses the impact of the frequently used values of the parameters associated with the harmonic bonds among the bonded DPD beads on the obtained self-assemblies. We find remarkable differences in the resultant self-assemblies based on different choices of harmonic bond parameters. The performed simulations show an enhanced spectrum of self-assemblies with augmented tail lengths and disparate harmonic bond parameters. The obtained self-assemblies are quite unique and can potentially be used in the future for various applications. We also compare the simulation results of the vesicle structures obtained by modeling the electrostatic interaction in the simulation among the charged beads by explicitly introducing charges with a long-range interaction with those obtained by tuning the implicit electrostatic interaction without the long-range interaction. The effects of the chain length of the model and the harmonic bond parameters on the internal density of DPD beads and stress profiles within the vesicles are examined closely. These results are a significant contribution to understanding the stability of the phases and tailoring of the desired vesicles.

A generic force field for simulating native protein structures using dissipative particle dynamics

A coarse-grained force field for molecular dynamics simulations of the native structures of proteins in a dissipative particle dynamics (DPD) framework is developed. The parameters for bonded interactions are derived by mapping the bonds and angles for 20 amino acids onto target distributions obtained from fully atomistic simulations in explicit solvent. A dual-basin potential is introduced for stabilizing backbone angles, to cover a wide spectrum of protein secondary structures. The backbone dihedral potential enables folding of the protein from an unfolded initial state to the folded native structure. The proposed force field is validated by evaluating the structural properties of several model peptides and proteins including the SARS-CoV-2 fusion peptide, consisting of α-helices, β-sheets, loops and turns. Detailed comparisons with fully atomistic simulations are carried out to assess the ability of the proposed force field to stabilize the different secondary structures present in proteins. The compact conformations of the native states were evident from the radius of gyration and the high intensity peaks of the root mean square deviation histograms, which were found to be within 0.4 nm. The Ramachandran-like energy landscape on the phase space of backbone angles (θ) and dihedrals (ϕ) effectively captured the conformational phase space of α-helices at ∼(ϕ = 50°,θ = 90°) and β-strands at ∼(ϕ = ±180°,θ = 90-120°). Furthermore, the residue-residue native contacts were also well reproduced by the proposed DPD model. The applicability of the model to multidomain complexes was assessed using lysozyme and a large α-helical bacterial pore-forming toxin, cytolysin A. Our study illustrates that the proposed force field is generic, and can potentially be extended for efficient in silico investigations of membrane bound polypeptides and proteins using DPD simulations.

Nanobioremediation: A sustainable approach towards the degradation of sodium dodecyl sulfate in the environment and simulated conditions

Nanotechnology has gained huge importance in the field of environmental clean-up today. Due to their remarkable and unique properties, it has shown potential application for the remediation of several pesticides and textile dyes. Recently it has shown positive results for the remediation of sodium dodecyl sulfate (SDS). One of the highly exploited surfactants in detergent preparation is anionic surfactants. The SDS selected for the present study is an example of anionic linear alkyl sulfate. It is utilized extensively in industrial washing, which results in the high effluent level of this contaminant and ubiquitously toxic to the environment. The present review is based on the research depicting the adverse effects of SDS in general and possible strategies to minimizing its effects by bacterial degradation which are capable of exploiting the SDS as an only source of carbon. Moreover, it has also highlighted that how nanotechnology can play a role in the remediation of such recalcitrant pesticides.

Chemical computational approaches for optimization of effective surfactants in enhanced oil recovery

The surfactant flooding becomes an attractive method among several Enhanced Oil Recovery (EOR) processes to improve the recovery of residual oil left behind in the reservoir after secondary oil recovery process. The designing of a new effective surfactant is a comparatively complex and often time consuming process as well as cost-effective due to its dependency on the crude oil and reservoir properties. An alternative chemical computational approach is focused in this article to optimize the performance of effective surfactant system for EOR. The molecular dynamics (MD), dissipative particle dynamics (DPD) and density functional theory (DFT) simulations are mostly used chemical computational approaches to study the behaviour in multiple phase systems like surfactant/oil/brine. This article highlighted a review on the impact of surfactant head group structure on oil/water interfacial property like interfacial tensions, interface formation energy, interfacial thickness by MD simulation. The effect of entropy in micelle formation has also discussed through MD simulation. The polarity, dipole moment, charge distribution and molecular structure optimization have been illustrated by DFT. A relatively new coarse-grained method, DPD is also emphasized the phase behaviour of surfactant/oil/brine as well as polymer-surfactant complex system.