In Silico Prediction of the Thermodynamic Equilibrium of Solute Partition in Multiphase Complex Fluids: A Case Study of Oil-Water Microemulsion.

Multiphase complex fluids such as micelles, microemulsions, and dispersions are ubiquitous in product formulations of foods, pharmaceuticals, cosmetics, and fine chemicals. Quantifying how active solutes partition in the microstructure of such multiphase fluids is necessary for designing formulations that can optimally deliver the benefits of functional actives. In this paper, we at first predict the structure of a heptane/butanol/sodium dodecyl sulfate droplet in water that self-assembled to form a microemulsion through the molecular dynamics (MD) simulation and subsequently investigate the thermodynamic equilibrium of solute partitioning using COSMOmic. To our knowledge, this is the first time that the MD/COSMOmic approach is used for predicting solute partitioning in a microemulsion. The predicted partition coefficients are compared to experimental values derived from retention measurements of the same microemulsion. We show that the experimental data of droplet-water partition coefficients (Kdroplet/w) can be reliably predicted by the method that combines MD simulations with COSMOmic.

Pyrolysis wastewater treatment by adsorption on biochars produced by poplar biomass.

Pyrolysis is a widely studied thermochemical process, however the disposal of the produced byproducts is an unexplored field. In particular, the acqueous phase, characterized by a high organic load (TOC), must be necessarily treated. Aims of this work is to study the potentiality of biochar as adsorbent material for the treatment of this wastewater. For this aim, pyrolysis wastewater and biochar produced in the same plant were used. Two biochars produced at different temperatures (550 and 750 °C) and an activated biochar produced by chemical activation with NaOH of the raw biomass were tested. The study shows that higher temperature in the biochar production leads to higher sorption capacity of the organic compounds due to an increase of the surface area. The activation process further increases the surface area of the biochar that becomes similar to that of a commercial activated carbon while the sorption capacity exceeds that of commercial activated carbon of 2.5 times.

Learning Adsorption Patterns on Amorphous Surfaces.

The physicochemical heterogeneity found on amorphous surfaces leads to a complex interaction of adsorbate molecules with topological and undercoordinated defects, which enhance the adsorption capacity and can participate in catalytic reactions. The identification and analysis of the adsorption structure observed on amorphous surfaces require novel tools that allow the segmentation of the surfaces into complex-shaped regions that contrast with the periodic patterns found on crystalline surfaces. We propose a Random Forest (RF) classifier that segments the surface into regions that can then be further analyzed and classified to reveal the dynamics of the interaction with the adsorbate. The RF segmentation is applied to the surface density map of the adsorbed molecules and employs multiple features (intensity, gradient, and the eigenvalues of the Hessian matrix) which are nonlocal and allow a better identification of the adsorption structures. The segmentation depends on a set of parameters that specify the training set and can be tailored to serve the specific purpose of the segmentation. Here, we consider an example in which we aim to separate highly heterogeneous regions from weakly heterogeneous regions. We demonstrate that the RF segmentation is able to separate the surface into a fully connected weakly heterogeneous region (whose behavior is somehow similar to crystalline surfaces and has an exponential distribution of the residence time) and a very heterogeneous region characterized by a complex residence-time distribution, which is generated by the undercoordinated defects and is responsible for the peculiar characteristics of the amorphous surface.

Predicting Partition Coefficients of Neutral and Charged Solutes in the Mixed SLES-Fatty Acid Micellar System.

Sodium laureth sulfate (SLES) and fatty acids are common ingredients in many cosmetic products. Understanding how neutral and charged fatty acid compounds partition between micellar and water phases is crucial to achieve the optimal design of the product formulation. In this paper, we first study the formation of mixed SLES and fatty acid micelles using molecular dynamics (MD) simulations. Micelle/water partition coefficients of neutral and charged fatty acids are then calculated using COSMOmic as well as a MD approach based on the potential of mean force (PMF) calculations performed using umbrella sampling (US). The combined US/PMF approach was performed with both the additive, non-polarizable CHARMM general force field (CGenFF) and the classical Drude polarizable force field. The partition coefficients for the neutral solutes are shown to be accurately calculated with the COSMOmic and additive CGenFF US/PMF approaches, while only the US/PMF approach with the Drude polarizable force field accurately calculated the experimental partition coefficient of the charged solute. These results indicate the utility of the Drude polarizable force field as a tool for the rational development of mixed micelles.