First-Principles Prediction of Liquid/Liquid Interfacial Tension

Synergistic Modeling of Liquid Properties: Integrating Neural Network-Derived Molecular Features with Modified Kernel Models

A significant challenge in applying machine learning to computational chemistry, particularly considering the growing complexity of contemporary machine learning models, is the scarcity of available experimental data. To address this issue, we introduce an approach that derives molecular features from an intricate neural network-based model and applies them to a simpler conventional machine learning model that is robust to overfitting. This method can be applied to predict various properties of a liquid system, including viscosity or surface tension, based on molecular features drawn from the ab initio calculated free energy of solvation. Furthermore, we propose a modified kernel model that includes Arrhenius temperature dependence to incorporate theoretical principles and diminish extreme nonlinearity in the model. The modified kernel model demonstrated significant improvements in certain scenarios and possible extensions to various theoretical concepts of molecular systems.

Multi-Stimuli-Responsive, Topology-Regulated, and Lignin-Based Nano/Microcapsules from Pickering Emulsion Templates for Bidirectional Delivery of Pesticides

The increasing demand for improving pesticide utilization efficiency has prompted the development of sustainable, targeted, and stimuli-responsive delivery systems. Herein, a multi-stimuli-responsive nano/microcapsule bidirectional delivery system loaded with pyraclostrobin (Pyr) is prepared through interfacial cross-linking from a lignin-based Pickering emulsion template. During this process, methacrylated alkali lignin nanoparticles (LNPs) are utilized as stabilizers for the tunable oil-water (O/W) Pickering emulsion. Subsequently, a thiol-ene radical reaction occurs with the acid-labile cross-linkers at the oil-water interface, leading to the formation of lignin nano/microcapsules (LNCs) with various topological shapes. Through the investigation of the polymerization process and the structure of LNC, it was found that the amphiphilicity-driven diffusion and distribution of cyclohexanone impact the topology of LNC. The obtained Pyr@LNC exhibits high encapsulation efficiency, tunable size, and excellent UV shielding to Pyr. Additionally, the flexible topology of the Pyr@LNC shell enhances the retention and adhesion of the foliar surface. Furthermore, Pyr@LNC exhibits pH/laccase-responsive targeting against Botrytis disease, enabling the intelligent release of Pyr. The in vivo fungicidal activity shows that efficacy of Pyr@LNC is 53% ± 2% at 14 days postspraying, whereas the effectiveness of Pyr suspension concentrate is only 29% ± 4%, and the acute toxicity of Pyr@LNC to zebrafish is reduced by more than 9-fold compared with that of Pyr technical. Moreover, confocal laser scanning microscopy shows that the LNCs can be bidirectionally translocated in plants. Therefore, the topology-regulated bidirectional delivery system LNC has great practical potential for sustainable agriculture.

Predicting absolute aqueous solubility by applying a machine learning model for an artificially liquid-state as proxy for the solid-state

In this study, we use machine learning algorithms with QM-derived COSMO-RS descriptors, along with Morgan fingerprints, to predict the absolute solubility of drug-like compounds. The QM-derived descriptors account for the molecular properties of the solute, i.e., the solute-solute interactions in an artificial-liquid-state (super-cooled liquid), and the solute-solvent interactions in solution. We employ two main approaches to predict solubility: (i) a hypothetical pathway that involves melting the solute at room temperature T = T¯ ([Formula: see text]) and mixing the artificially liquid solute into the solvent ([Formula: see text]). In this approach [Formula: see text] is predicted using machine learning models, and the [Formula: see text] is obtained from COSMO-RS calculations; (ii) direct solubility prediction using machine learning algorithms. The models were trained on a large number of Bayer in-house compounds for which water solubility data is available at physiological pH of 6.5 and ambient temperature. We also evaluated our models using external datasets from a solubility challenge. Our models present great improvements compared to the absolute solubility prediction with the QSAR model for the artificial liquid state as implemented in the COSMOtherm software, for both in-house and external datasets. We are furthermore able to demonstrate the superiority of QM-derived descriptors compared to cheminformatics descriptors. We finally present low-cost alternative models using fragment-based COSMOquick calculations with only marginal reduction in the quality of predicted solubility.

Effect of Oil-Soluble/Water-Soluble Surfactants on the Stability of Water-in-Oil Systems, an Atomic Force Microscopy Study

The stabilization mechanism of water-in-oil (W/O) emulsions has been studied by measuring the interactions between two water droplets in n-tetradecane using atomic force microscopy. The effects of water-soluble surfactants (SDS/CTAB/Tween 80), an oil-soluble surfactant (Span 20), and the coexistence of the water and oil-soluble surfactants on the stability of water droplets in oil were investigated separately. It is found that the addition of oil-soluble surfactants (Span 20) prevents the coalescence of water droplets in oil. To discuss the role of an oil-soluble surfactant, we analyzed the force curve by applying the theoretical model. The results demonstrate that the oil-soluble surfactant (Span 20) stabilizes dispersed droplets by adsorbing onto the interface and forming a relatively tighter layer with the increase in surfactant concentration, which hinders film rupture. This behavior of the surfactant could also be properly characterized by steric hindrance. A further step was taken by introducing another water-soluble surfactant. It is found that the addition of either SDS or CTAB into the water phase is futile in inducing droplet coalescence in the presence of Span 20. In contrast, Tween 80 was found to be effective in destabilizing water droplets, which could be due to the competitive adsorption between Tween 80 and Span 20 at the interface. By characterizing the interfacial adsorption of Tween 80 and Span 20 with a theoretical adsorption isotherm model, the result indicates that interface replacement would result in a loose adsorption layer that is insufficient to hinder droplet coalescence. Our study provides an intriguing understanding of the role of surfactants in the stabilization and destabilization of water-in-oil emulsions.

New Prediction Model of Surface and Interfacial Energies Based on COSMO-UCE

The nature and strength of intermolecular and surface forces are the key factors that influence the solvation, adhesion and wetting phenomena. The universal cohesive energy prediction equation based on conductor-like screening model (COSMO-UCE) was extended from like molecules (pure liquids) to unlike molecules (dissimilar liquids). A new molecular-thermodynamic model of interfacial tension (IFT) for liquid-liquid and solid-liquid systems was developed in this work, which can predict the surface free energy of solid materials and interfacial energy directly through cohesive energy calculations based on COSMO-UCE. The applications of this model in prediction of IFT for water-organic, solid (n-hexatriacontane, polytetrafluoroethylene(PTFE) and octadecyl-amine monolayer)-liquid systems have been verified extensively with successful results; which indicates that this is a straightforward and reliable model of surface and interfacial energies through predicting intermolecular interactions based on merely molecular structure (profiles of surface segment charge density), the dimensionless wetting coefficient R_A/C can characterize the wetting behavior (poor adhesive (non-wetting), wetting, spreading) of liquids on the surface of solid materials very well.

First-principles prediction of critical micellar concentrations for ionic and nonionic surfactants

The concentration of surfactant in solution for which micelles start to form, also known as critical micelle concentration is a key property in formulation design. The critical micelle concentration can be determined experimentally with a tensiometer by measuring the surface tension of a concentration series. In analogy with experiments, in-silico predictions can be achieved through interfacial tension calculations. We present a newly developed method, which employs first principles-based interfacial tension calculations rooted in COSMO-RS theory, for the prediction of the critical micelle concentration of a set of nonionic, cationic, anionic, and zwitterionic surfactants in water. Our approach consists of a combination of two prediction strategies for modelling two different phenomena involving the removal of the surfactant hydrophobic tail from contact with water. The two strategies are based on regular micelle formation and thermodynamic phase separation of the surfactant from water and both are required to take into account a wide range of polarity in the hydrophilic headgroup. Our method yields accurate predictions for the critical micellar concentration, within one log unit from experiments, for a wide range of surfactant types and introduces possibilities for first-principles based prediction of formulation properties for more complex compositions.

Molecular Transport across Oil-Brine Interfaces Impacts Interfacial Tension: Time-Effects in Buoyant and Pendant Drop Measurements

The buoyant drop method is a ubiquitous tool for addressing phenomena at the liquid-liquid interface via the determination of the interfacial tension (IFT) between two immiscible phases. Here, the focus is on how electrolytes (in an aqueous phase) and carboxylic acids (in a decane phase) impact the interfacial layer between the two phases. The IFT measurement provides a single number, which is not fulfilling when it comes to deducing information about a complex multiparameter system. Furthermore, the temporal evolution of IFT does not always reach a steady-state value on a time scale, which is realistic to use for comparative studies. We have investigated the temporal evolution of IFT in a series of experiments with varying compositions of the decane-carboxylic acid phase and the brine phase. The results show that there are at least two opposing effects in play. For water-soluble acids, the IFT initially increases with time until a turnover point is reached from where there is a gradual decay. The IFT at the turnover point is close to that of the pure water-decane system. For a poorly water-soluble acid, the IFT shows a much smaller increase and the turnover happens much faster. For a water-soluble acid, there is a high degree of sensitivity toward the electrolyte; it determines the position (in time) of the IFT peak and the steepness of the subsequent decay. Now, if the phases are reversed, that is, by placing a drop of brine in the decane-surfactant phase, the IFT decreases with time regardless of the acid and with little impact of the electrolyte and its concentration in the brine. We propose an explanation for the observed behavior (supported by COSMO-RS calculations), which is based on diffusion in and out of the two phases, solubility, and interfacial reactivity (i.e., aggregation between electrolytes and carboxylic acids).

First-Principles Prediction of Surface Wetting

We have developed a method for predicting the solvation contribution to solid-liquid interfacial tension (IFT) based on density functional theory and the implicit solvent model COSMO-RS. Our method can be used to predict wetting behavior for a solid surface in contact with two liquids. We benchmarked our method against measurements of contact angle from water-in-oil on silica wafers and a range of self-assembled monolayers (SAMs) with different compositions, ranging from oil-wet to water-wet. We also compared our predictions to literature data for wetting of a polydimethylsilane surface. By explicitly including deprotonation for silica surfaces and carboxylic acid SAMs, very good agreement was obtained with experimental data for nearly all surfaces. Poor agreement was found for amine-terminated SAMs, which could be the result of both method and model insufficiencies and impurities known to be present for such surfaces. Solid-liquid IFT cannot be measured directly, making predictions such as from our method all the more important.

Thermodynamic and Kinetic Parameters for Calcite Nucleation on Peptoid and Model Scaffolds: A Step toward Nacre Mimicry

The production of novel composite materials, assembled using biomimetic polymers known as peptoids (N-substituted glycines) to nucleate CaCO₃, can open new pathways for advanced material design. However, a better understanding of the heterogeneous CaCO₃ nucleation process is a necessary first step. We determined the thermodynamic and kinetic parameters for calcite nucleation on self-assembled monolayers (SAMs) of nanosheet-forming peptoid polymers and simpler, alkanethiol analogues. We used nucleation rate studies to determine the net interfacial free energy (γ _net) for the peptoid-calcite interface and for SAMs terminated with carboxyl headgroups, amine headgroups, or a mix of the two. We compared the results with γ _net determined from dynamic force spectroscopy (DFS) and from density functional theory (DFT), using COSMO-RS simulations. Calcite nucleation has a lower thermodynamic barrier on the peptoid surface than on carboxyl and amine SAMs. From the relationship between nucleation rate (J ₀) and saturation state, we found that under low-saturation conditions, i.e. <3.3 (pH 9.0), nucleation on the peptoid substrate was faster than that on all of the model surfaces, indicating a thermodynamic drive toward heterogeneous nucleation. When they are taken together, our results indicate that nanosheet-forming peptoid monolayers can serve as an organic template for CaCO₃ polymorph growth.

Thermal and chemical enhanced recovery of heavy chlorinated organic compounds in saturated porous media: 1D cell drainage-imbibition experiments

Chemical and thermal enhanced recovery of pure heavy chlorinated organic compounds (DNAPL; dense non-aqueous phase liquids) was investigated by using lab-scale 1D cells. Temperature was increased to reduce DNAPL viscosity (and hence increase its mobility), while surfactant was added to decrease capillary forces involved in the entrapment of DNAPL in porous media. Laboratory scale experiments, based on mass balance and indirect monitoring methods (i.e., permittivity, electrical resistivity and optical density), were conducted to quantify the effects of these enhancements. Heating the DNAPL up to 50 °C decreased its viscosity by a factor of two. The addition of a surfactant; i.e., Sodium Dodecyl Benzene Sulfonate (SDBS), at its Critical Micelle Concentration (to prevent DNAPL solubilization), decreased interfacial tensions by a factor of 12. Drainage-imbibition experiments performed in 1D cells provided retention curves (capillary pressure as a function of water saturation) of a two-phase (DNAPL-water) system in experimental glass bead porous media. The observed reduction of residual saturation (S_rn) obtained with SDBS was 28% for 0.5 mm-diameter glass beads (GB) and 46% for 0.1 mm GB. No significant decrease in S_m was observed with thermal enhancement. The van Genuchten - Mualem model was found to satisfactorily reproduce the measured retention curves. Indirect measurements of water saturations (S_w) showed that: i. measured permittivities were very close to values modeled with the Complex Refractive Index Model (CRIM); ii. Archie's Law was less successful in reproducing measured electrical resistivities; iii. optical densities provide accurate estimations of S_w. At field scale, the combined monitoring of electrical resistivity (which provides a global picture) and permittivity (which yields locally precise but spatially limited information) is expected to significantly improve the collection of information on residual saturations S_rn.

Unstable, Super Critical CO2-Water Displacement in Fine Grained Porous Media under Geologic Carbon Sequestration Conditions

In this study we investigated fluid displacement water with supercritical (sc) CO₂ in chalk under conditions close to those used for geologic CO₂ sequestration (GCS), to answer two main questions: How much volume is available for scCO₂ injection? And what is the main mechanism of displacement over a range of temperatures? Characterization of immiscible scCO₂ displacement, at the pore scale in the complex microstructure in chalk reservoirs, offers a pathway to better understand the macroscopic processes at the continuum scale. Fluid behavior was simulated by solving the Navier-Stokes equations, using finite-volume methods within a pore network. The pore network was extracted from a high resolution 3D image of chalk, obtained using X-ray nanotomography. Viscous fingering dominates scCO₂ infiltration and pores remain only partially saturated. The unstable front, developed with high capillary number, causes filling of pores aligned with the flow direction, reaching a maximum of 70% scCO₂ saturation. The saturation rate increases with temperature but the final saturation state is the same for all investigated temperatures. The higher the saturation rate, the higher the dynamic capillary pressure coefficient. A higher dynamic capillary pressure coefficient indicates that scCO₂ needs more time to reach capillary equilibrium in the porous medium.

COSMOplex: self-consistent simulation of self-organizing inhomogeneous systems based on COSMO-RS

During the past 20 years, the efficient combination of quantum chemical calculations with statistical thermodynamics by the COSMO-RS method has become an important alternative to force-field based simulations for the accurate prediction of free energies of molecules in liquid systems. While it was originally restricted to homogeneous liquids, it later has been extended to the prediction of the free energy of molecules in inhomogeneous systems such as micelles, biomembranes, or liquid interfaces, but these calculations were based on external input about the structure of the inhomogeneous system. Here we report the rigorous extension of COSMO-RS to a self-consistent prediction of the structure and the free energies of molecules in self-organizing inhomogeneous systems. This extends the application range to many new areas, such as the prediction of micellar structures and critical micelle concentrations, finite loading effects in micelles and biomembranes, the free energies and structure of liquid interfaces, microemulsions, and many more related topics, which often are of great practical importance.

Oil spill modeling in deep waters: Estimation of pseudo-component properties for cubic equations of state from distillation data

Deep-water oil spills represent a major, localized threat to marine ecosystems. Multi-purpose computer models have been developed to predict the fate of spilled oil. These models include databases of pseudo-components from distillation cut analysis for hundreds of oils, and have been used for guiding response action, damage assessment, and contingency planning for marine oil spills. However, these models are unable to simulate the details of deep-water, high-pressure chemistry. We present a new procedure to calculate the chemical properties necessary for such simulations that we validate with 614 oils from the ADIOS oil library. The calculated properties agree within 20.4% with average values obtained from data for measured compounds, for 90% of the chemical properties. This enables equation-of-state calculations of dead oil density, viscosity, and interfacial tension. This procedure enables development of comprehensive oil spill models to predict the behavior of petroleum fluids in the deep sea.

Simulations of Interfacial Tension of Liquid-Liquid Ternary Mixtures Using Optimized Parametrization for Coarse-Grained Models

In this work, liquid-liquid systems are studied by means of coarse-grained Monte Carlo simulations (CG-MC) and Dissipative Particle Dynamics (DPD). A methodology is proposed to reproduce liquid-liquid equilibrium (LLE) and to provide variation of interfacial tension (IFT), as a function of the solute concentration. A key step is the parametrization method based on the use of the Flory-Huggins parameter between DPD beads to calculate solute/solvent interactions. Parameters are determined using a set of experimental compositional data of LLE, following four different approaches. These approaches are evaluated, and the results obtained are compared to analyze advantages/disadvantages of each one. These methodologies have been compared through their application on six systems: water/benzene/1,4-dioxane,water/chloroform/acetone, water/benzene/acetic acid, water/benzene/2-propanol, water/hexane/acetone, and water/hexane/2-propanol. CG-MC simulations in the Gibbs (NVT) ensemble have been used to check the validity of parametrization approaches for LLE reproduction. Then, CG-MC simulations in the osmotic (μ_soluteN_solventP _zzT) ensemble were carried out considering the two liquid phases with an explicit interface. This step allows one to work at the same bulk concentrations as the experimental data by imposing the precise bulk phase compositions and predicting the interface composition. Finally, DPD simulations were used to predict IFT values for different solute concentrations. Our results on variation of IFT with solute concentration in bulk phases are in good agreement with experimental data, but some deviations can be observed for systems containing hexane molecules.

Structure of Nanoparticles Derived from Designer Surfactant TPGS-750-M in Water, As Used in Organic Synthesis

Using density functional theory and the COSMO-RS implicit solvent model, we predict the structure and physical chemical properties of nanomicelles derived from the designer surfactant TPGS-750-M used in organic synthesis. We predict that the influence of chain length of the PEG region is low, while the termination of the PEG chain (-OH vs.-OCH₃ ) plays a very large role. The interfacial tension is considerably lower between the micellar and water phases for the -OH than the -OCH₃ terminated surfactant, and our calculations reproduce the large difference observed in average particle size as a function of PEG chain termination. We propose a structure for the nanoparticles formed by TPGS-750-M in water that is consistent with a ≈50 nm average diameter, which is significantly larger than a single micelle. According to the calculations, each nanoparticle would consist of 30-40 aggregated TPGS-750-M micelles forming a compartmentalized nanoparticle, with considerable amounts of water in the PEG region. The whole particle is stabilized by vitamin E succinate at the nanoparticle-water interface. In the presence of Zn dust or powder, the surfactant collides with the Zn surface, and by interactions with the hydrophobic inner cores, form organozinc species that are protected from the surrounding water. This explains why highly moisture-sensitive Negishi-like couplings take place in surfactant-water systems.

Liquid–liquid extraction in flow of the radioisotope titanium-45 for positron emission tomography applications

The continuous liquid–liquid extraction of the PET radioisotope ⁴⁵Ti using a membrane-based separator allows for efficient ⁴⁵Ti recovery and radiolabeling.

Direct Prediction of Calcite Surface Wettability with First-Principles Quantum Simulation

Prediction of intrinsic surface wettability from first-principles offers great opportunities in probing new physics of natural phenomena and enhancing energy production or transport efficiency. We propose a general quantum mechanical approach to predict the macroscopic wettability of any solid crystal surfaces for different liquids directly through atomic-level density functional simulation. As a benchmark, the wetting characteristics of calcite crystal (10.4) under different types of fluids (water, hexane, and mercury), including either contact angle or spreading coefficient, are predicted and further validated with experimental measurements. A unique feature of our approach lies in its capability of capturing the interactions among various polar fluid molecules and solid surface ions, particularly their charge density difference distributions. Moreover, this approach provides insightful and quantitative predictions of complicated surface wettability alteration problems and wetting behaviors of liquid/liquid/solid triphase systems.

Modelling how incorporation of divalent cations affects calcite wettability-implications for biomineralisation and oil recovery

Using density functional theory and geochemical speciation modelling, we predicted how solid-fluid interfacial energy is changed, when divalent cations substitute into a calcite surface. The effect on wettability can be dramatic. Trace metal uptake can impact organic compound adsorption, with effects for example, on the ability of organisms to control crystal growth and our ability to predict the wettability of pore surfaces. Wettability influences how easily an organic phase can be removed from a surface, either organic compounds from contaminated soil or crude oil from a reservoir. In our simulations, transition metals substituted exothermically into calcite and more favourably into sites at the surface than in the bulk, meaning that surface properties are more strongly affected than results from bulk experiments imply. As a result of divalent cation substitution, calcite-fluid interfacial energy is significantly altered, enough to change macroscopic contact angle by tens of degrees. Substitution of Sr, Ba and Pb makes surfaces more hydrophobic. With substitution of Mg and the transition metals, calcite becomes more hydrophilic, weakening organic compound adsorption. For biomineralisation, this provides a switch for turning on and off the activity of organic crystal growth inhibitors, thereby controlling the shape of the associated mineral phase.

Multiscale Materials Modeling in an Industrial Environment

In this review, we sketch the materials modeling process in industry. We show that predictive and fast modeling is a prerequisite for successful participation in research and development processes in the chemical industry. Stable and highly automated workflows suitable for handling complex systems are a must. In particular, we review approaches to build and parameterize soft matter systems. By satisfying these prerequisites, efficiency for the development of new materials can be significantly improved, as exemplified here for formulation polymer development. This is in fact in line with recent Materials Genome Initiative efforts sponsored by the US government. Valuable contributions to product development are possible today by combining existing modeling techniques in an intelligent fashion, provided modeling and experiment work hand in hand.

HandaPhos: A General Ligand Enabling Sustainable ppm Levels of Palladium-Catalyzed Cross-Couplings in Water at Room Temperature

The new monophosphine ligand HandaPhos has been identified such that when complexed in a 1:1 ratio with Pd(OAc)2, enables Pd-catalyzed cross-couplings to be run using ≤1000 ppm of this pre-catalyst. Applications to Suzuki-Miyaura reactions involving highly funtionalized reaction partners are demonstrated, all run using environmentally benign nanoreactors in water at ambient temperatures. Comparisons with existing state-of-the-art ligands and catalysts are discussed herein.

Quantum chemical approach in the description of the amphiphile clusterization at the air/liquid and liquid/liquid interfaces with phase nature accounting. I. Aliphatic normal alcohols at the air/water interface

A new model based on the quantum chemical approach is proposed to describe structural and thermodynamic parameters of clusterization for substituted alkanes at the air/liquid and liquid/liquid interfaces. The new model by the authors, unlike the previous one, proposes an explicit account of the liquid phase (phases) influence on the parameters of monomers, clusters and monolayers of substituted alkanes at the regarded interface. The calculations were carried out in the frameworks of the quantum chemical semiempirical PM3 method (Mopac 2012), using the COSMO procedure. The new model was tested in the calculations of the clusterization parameters of fatty alcohols under the standard conditions at the air/water interface. The enthalpy, Gibbs' energy and absolute entropy of formation for alcohol monomers alongside with clusterization parameters for the cluster series including the monolayer at air/water interface were calculated. In our calculations the sinkage of monomers, molecules in clusters and monolayers was varied from 1 up to 5 methylene groups. Thermodynamic parameters calculated using the proposed model for the alcohol monolayers are in a good agreement with the corresponding experimental data. However, the proposed model cannot define the most energetically preferable immersion of the monolayer molecules in the water phase.

Calculation of solvation free energies with DCOSMO-RS

The concept of dielectric continuum models has turned out to be very fruitful for the qualitative description of solvation effects in quantum chemical calculations, although from a theoretical perspective its basis is questionable, at least if applied to polar solvents, because the electrostatic nearest neighbor interactions in polar solvents are much too strong to be described by macroscopic dielectric continuum theory. On the basis of this insight, the Conductorlike Screening Model for Realistic Solvation (COSMO-RS) had been developed, which gives a thermodynamically consistent, quantitative description of solvation effects in polar and nonpolar solvents, even in mixtures and at variable temperature, starting from quantum chemical calculations of solute and solvent molecules embedded in a virtual conductor (COSMO). Though COSMO-RS usually only requires quantum chemical calculations in the conductor and thus does not allow for studying of the concrete solvent influence on the solute electron density, the direct COSMO-RS (DCOSMO-RS) has been introduced, which uses the σ-potential, i.e., a solvent specific response function provided by COSMO-RS, as a replacement of the conductor or dielectric response employed in continuum solvation models. In this article we describe the current status of DCOSMO-RS and demonstrate the performance of the DCOSMO-RS approach for the prediction of free energies of solvation.