Hydrophilic-lipophilic Difference Research Articles

Comparison of Machine Learning Approaches for Prediction of the Equivalent Alkane Carbon Number for Microemulsions Based on Molecular Properties.

The chemical properties of oils are vital in the design of microemulsion systems. The hydrophilic-lipophilic difference equation used to predict microemulsions' phase behavior expresses the oils' physiochemical properties as the equivalent alkane carbon number (EACN). The experimental determination of EACN requires knowledge of the temperature dependence of the microemulsion system and the effects of different surfactant concentrations. Thus, the experimental determination is time-intensive and tedious, requiring days to months for proper separations. Furthermore, the experiments require high purity of chemicals because microemulsions are sensitive to impurities. Our work focuses on the quick and reliable predictions of the EACN with machine learning (ML) models. Due to the immaturity of ML chemical predictions, we compare three graph neural networks (GNNs) and a gradient-boosted tree algorithm, known as XGBoost. The GNNs use the molecular structures represented as simplified molecular-input line-entry system (SMILES) codes for the initial input, which allows us to assess whether geometry optimization is necessary for reliable results. The XGBoost model also begins with the SMILES representations of the molecules but uses molecular descriptors instead of geometry optimizations. The best model tested (crystal graph convolutional neural network with Merck molecular force field-94) has an error of 1.15 EACN units of the true EACN for unknown data with the errors skewed toward zero and an R2 score of 0.9.

The Characteristic Curvature (Cc) of Ionic Surfactants Assessed via Small-Angle X-ray Scattering.

The characteristic curvature (Cc), within the hydrophilic-lipophilic difference + net (Hn) - average (Ha) curvature (HLD-NAC) framework, is the dimensionless net curvature, -Hn·L (L is the surfactant's tail length parameter), that a surfactant acquires at the characteristic condition (T = 25 °C, no added cosurfactants, oil with an equivalent alkane carbon number (EACN) of zero and for ionic surfactants, a total salinity (S) of 1 g NaCl/100 mL). A recent article demonstrated the validity of the Cc concept, where Hn was assessed via oil and water solubilization radii. Here, we assess Hn from the characteristic length (ξ) obtained from the analysis of SAXS profiles of microemulsions produced at semicharacteristic conditions (characteristic condition but varying S). The predicted relationship, -L·Hn,semicharacteristic = Ccbi + bi·ln(S), was confirmed with the five ionic surfactants explored. The SAXS-assessed Cc (Cc = Ccbi/bi) values are consistent with those obtained from solubilization studies and phase inversion scans. The Cc-SAXS method provides a way to assess the hydrophobicity of ionic surfactants directly, avoiding the bias that could be introduced by cosurfactants in phase inversion studies and minimizing the impact of potential uncertainties in the surfactant volume to area ratio (vs/as) required to calculate the solubilization radii in the solubilization method.

Fragranced consumer products: Formulation practices, related models, and recommendations to enable wider hydrophilic–lipophilic difference (HLD) application

AbstractFragrances in consumer products are essential for appeal and market success. However, creating optimal stable formulas are especially challenging due to the polar nature of many fragrance ingredients. This perspective discusses how fragrances are currently dealt with within the industry, current surfactant and solvent models, and the barriers that today's industrial practice that prevent advancement to modeling and simulation. Recommendations for chemical suppliers, fragrance houses, and formulators are made regarding the implementation of the Hydrophilic‐Lipophilic Difference with Net Average Curvature (HLD‐NAC) model, which is the most comprehensive model for fragranced aqueous consumer products.

Hydrophilic lipophilic difference theory for fenofibrate formulation as a self-emulsifying drug delivery system

Hydrophilic lipophilic difference theory for fenofibrate formulation as a self-emulsifying drug delivery system

Application of Hydrophilic Lipophilic Difference Theory for Fenofibrate Formulation as a Self-Emulsifying Drug Delivery System

Application of Hydrophilic Lipophilic Difference Theory for Fenofibrate Formulation as a Self-Emulsifying Drug Delivery System

A methodology for measuring the characteristic curvature of technical-grade ethoxylated nonionic surfactants: the effects of concentration and dilution

Abstract Characterization of the behaviour of commercially available non-ionic surfactants has received considerable attention due to their efficacy in a variety of applications. The main challenge in the application of these types of surfactants is that the hydrophilicity of the surfactant varies with concentration and dilution due to the polydispersity of the ethylene oxide groups. The hydrophilicity of a surfactant can be quantified by the characteristic curvature (Cc) parameter of the hydrophilic–lipophilic difference (HLD) framework. In this work, a model based on natural logarithmic regression was developed to calculate the Cc value of commercial surfactants as a function of surfactant concentration by a fast and simple phase scan. The slope of the Cc curve and the measured Cc at a reference concentration were used to develop the model. The Cc values determined with the model agreed with the measured values from the phase scans. Furthermore, the linear mixing rule proved to be reliable for mixtures of polydisperse ethoxylated surfactants. Finally, the impact of the water-to-oil ratio on the Cc was evaluated and the implications were discussed.

Fourier transform infrared spectroscopy in surfactant science: A personal view

AbstractThe overall goal of this review paper on Fourier transform infrared spectroscopy (FT‐IR) is to provide non‐specialists and spectroscopists alike a motivational introduction to how this technique may be used to obtain unique structural information on a wide range of surfactant‐based systems. Two main topics are addressed—The structures of surfactant aggregates in solution and the interactions of surfactants in solution with solid surfaces. Infrared spectra can yield insights into the interactions of surfactants in mixed micelles as well as in microemulsions. The structures of adsorbed surfactant layers and their kinetics of formation may be elucidated from FT‐IR spectra obtained using attenuated total reflectance sampling techniques. Insights into the detergency process of solid oily soils may also be obtained from the spectra of phases formed at the soil‐surfactant solution interface. Future work in applying FT‐IR to the development of the hydrophilic–lipophilic difference + net average curvature (HLD‐NAC) framework is proposed. Spectral interpretation principles examined in many examples, particularly regarding surfactant hydration and the loci of oil solubilization, could be used in the further development of HLD‐NAC through application to some microemulsion systems that have recently been reported.

Modelling the partitioning equilibria of nonionic surfactant mixtures within the HLD framework

Commercial non-ionic surfactants are usually blends of species differing in the degree of ethoxylation, characterised by a distribution of surfactants with different affinity for the oil and the aqueous phases. This leads to an unexpected concentration dependence of the phase behaviour and the rationalization of such deviations is necessary for their exploitation in surfactant-based formulations. In this work, the phase behaviour of commercial Novel® nonionic surfactants in presence of brine and oil was studied fixing equal volumes of organic and aqueous phases and changing the amount of surfactant and brine salinity (fish cut). The conditions for the balanced state (microemulsion solubilizing equals amount of water and oil) have been determined for different alkanes. The phase behaviour of the surfactant mixture was described, without a priori information about its actual chemical composition, in terms of two pseudo-components: one hydrophilic, entirely at the interface, and the other lipophilic, able to partition itself between the interface and the oil bulk according to a partition constant P. The pseudo-components effect on the interface is quantified through surfactant characteristic parameters (SCPs), according to the Hydrophilic-Lipophilic-Difference (HLD) model. SCPs and P can be experimentally determined by fitting the dependence of the balanced state on the surfactant concentration. The model is successfully applied to the tested surfactants and can quantitively predict the behaviour of their mixtures.

Characterizing the Behavior of Bitumen–Water Systems with the Hydrophilic–Lipophilic Difference Framework

Characterizing the Behavior of Bitumen–Water Systems with the Hydrophilic–Lipophilic Difference Framework

Pulse-shape discrimination in water-based scintillators

This work describes a class of liquid scintillators that contain mostly water (>50 wt% of the entire composition) and can discriminate between interactions induced by neutrons and gamma rays. By balancing the interface interactions between the components of the formulation, these scintillators form emulsions that can be thermodynamically stable. This approach, which considers a quantity known as the hydrophilic–lipophilic difference, requires consideration of the salinity and temperature as well as characterization of the surfactants and oil phase. Emulsions comprised of water and various oils were characterized first. Then, the effect of scintillating dyes in the oil phase was considered, followed by the construction of partial phase diagrams of the emulsions. For transparent oil-in-water emulsions with a single phase, the scintillation light yield and metrics related to pulse-shape discrimination were measured. The best performing scintillators contained 33 wt% of a scintillating oil phase and exhibited a light yield that was as high as 18% of the light yield of a commercially available liquid scintillator that does not contain water (EJ-309). These water-based liquid scintillators exhibited a figure of merit of neutron/gamma ray discrimination as high as 1.79 at about 1500 keVee.

Spontaneous Emulsions: Adjusting Spontaneity and Phase Behavior by Hydrophilic-Lipophilic Difference-Guided Surfactant, Salt, and Oil Selection.

Spontaneous emulsion behavior has been difficult to predict and could be influenced by many variables including salinity, temperature, and chemical composition of the oil and surfactant. In this work, the hydrophilic-lipophilic difference (HLD) framework was used to predict the formation of spontaneous emulsions using a mixture of Span-80 and SLES surfactants. The spontaneity and emulsion behavior of different systems were modeled by estimating the HLDmix. The influence of surfactant ratio, salinity, and oil type was investigated. Spontaneous emulsification could only be observed when the HLDmix was between -0.96 and 1.04. Within this range, a negative HLDmix resulted in a greater spontaneity to form o/w emulsion, and a w/o emulsion was more likely to form when the HLDmix was positive. When the HLDmix was close to 0 (between -0.22 and 0.56 in our systems), emulsions were formed in both the oil and aqueous phases with high spontaneity. A combined effect of ultralow interfacial tension, Span-80 micelle swelling, and interfacial turbulence due to Marangoni effects is likely the main mechanism of the spontaneous emulsification observed in this study. A synergistic reduction in interfacial tension was observed between Span-80 and SLES (<1 mN/m). When the HLD of the system was close to 0, a bicontinuous emulsion phase was formed at the oil-water interface. The bicontinuous emulsion broke-up over time due to the ultralow interfacial tension and interfacial turbulence, forming dispersed oil and water droplets. Results from this work provide a practical method to suggest what surfactant composition, salinity, and oil type could promote (or eliminate) the conditions favorable for spontaneous emulsification.

An HLD framework for cationic ammonium surfactants

The Hydrophilic-Lipophilic Difference (HLD) model can be described by additive contributions accounting for the effect of the oil and surfactant nature, temperature, ionic strength, and so on. The first step to build an HLD framework for a surfactant class is to have Winsor III phase equilibria in a restricted range of formulation variables. In this respect, anionic and nonionic surfactants are well suited for an HLD study. On the contrary, it is difficult achieve for pure cationic surfactant Winsor III phase equilibria without the addition of alcohols and this has precluded the extension of the HLD to cationic surfactants. In the present contribution, we first propose a system based on a blend of single-tailed and double-tailed cationic surfactant to study the oil contribution, and then we afforded the determination of the surfactant contribution trough an experimental approach (the “HLD-titration”) that is especially tailored for systems displaying a wide range of existence of Winsor III phase equilibria. HLD-titration results confirmed the ionic strength contribution to HLD as a logarithmic function of salinity for cationic-based microemulsions similarly to anionic ones. However, the oil carbon number contribution is almost four-fold larger ( k ​= ​0.7 ​± ​0.1) with respect to anionic surfactants. A clearing point was observed in correspondence of the Winsor III phase equilibria under stirring. This approach allows us the determination of the so-called characteristic curvature ( Cc ), i.e. the term describing the surfactant nature contribution to the film curvature, of the cationic surfactant. Finally, the method was adopted to determine Cc values of 7 quaternary ammonium surfactants differing in the polar heads nature and further three amine oxide surfactant at pH ​= ​1 where they are protonated.

HLD-NAC design and evaluation of a fully dilutable lecithin-linker SMEDDS for ibuprofen

Lecithin-linker microemulsions have been previously proposed as a platform for designing a fully dilutable self-microemulsifying drug delivery system (SMEDDS). This SMEDDS formulation, composed of ethyl caprate (oil), lecithin (Le), glycerol monooleate (lipophilic linker, LL) and polyglycerol caprylate (hydrophilic linker, HL), produced a ternary phase diagram (TPD) that had a fully dilutable path suitable for oral drug delivery. However, introducing ibuprofen as an active pharmaceutical ingredient (API) resulted in TPD phase boundaries that eliminated the fully dilutable path. The purpose of this work was to understand the origin of the changes in the TPD, use that understanding to restore the fully dilutable path with an ibuprofen-loaded SMEDDS, and finally to evaluate the absorption of ibuprofen in vivo. The effect of ibuprofen on the HLD (hydrophilic-lipophilic difference, interpreted as normalized net interfacial curvature) of the system was evaluated via a polar oil model, showing that ibuprofen played a surfactant-like role, having a characteristic curvature (Cc) value of +5 (highly hydrophobic). The net-average curvature (NAC) framework used the HLD calculated with Le, LL, HL and ibuprofen Cc to generate TPDs in ibuprofen lecithin-linker systems. The HLD-NAC simulations show that restoring full dilutability required a highly hydrophilic linker (HL−) with a Cc of −5 or more negative. The fully dilutable path was restored after introducing a hexaglycerol caprylate as HL- (Cc = −6). Plasma concentration profiles obtained with this ibuprofen-loaded SMEDDS showed a more than three-fold increase in the area under the curve (AUC) of rat plasma concentration profiles compared to the same 25 mg/kg ibuprofen dose in suspension.

Effect of surfactant concentration on the hydrophobicity of polydisperse alkyl ethoxylates

AbstractThe effect of ethylene oxide number (EON) polydispersity on the phase behavior of alkyl ethoxylates has been well documented in the surfactant literature. These previous studies show that polydisperse alkyl ethoxylates appear more hydrophilic as the surfactant concentration decreases or as the oil‐to‐water ratio increases. This becomes a troubling issue considering that most surfactant formulations undergo dilution during use, and they experience a wide range of water‐to‐oil volume ratios. Within the hydrophilic–lipophilic difference framework, the surfactant hydrophobicity is assessed via the sigma (σ) term (also known as the characteristic curvature or Cc). In this work, the effect of surfactant concentration on the apparent value of sigma (σapp) is evaluated as a function of surfactant concentration. The experimental observations are then explained using a bifunctional model for alkyl ethoxylates that consider the dual nature of polar oils (free alcohol and low EON ethoxymers) as surfactants and as oil components. A segregation‐based model and a partition‐based model are implemented to account for the distribution of the ethoxymers in the surfactant pseudophase and the oil phase. Combining these distribution models with the bifunctional model and a group contribution model for sigma, one can predict the σ term versus surfactant concentration for a given water/oil ratio, starting from the EON distribution of the surfactant. The practical applications of the model are discussed.

Predicting Spontaneous Emulsification in Saltwater Environments Using the HLD Model.

Spontaneous emulsification of toluene with nonylphenol polyethoxylate (NPE) and sodium dodecylbenzenesulfonate (SDBS) surfactants in saltwater environments was studied. NaCl promoted the spontaneous emulsification of an otherwise non-spontaneous SDBS-toluene system. Dynamic light scattering and turbidity indicated that spontaneity increased with NaCl concentration. The mechanism of spontaneous emulsification was dependent on surfactant type; NPE emulsified via micelle swelling, and SDBS emulsified via nucleation and growth. Hydrophilic lipophilic difference (HLD) calculations were used to model spontaneous emulsification and spontaneity. As HLD approached zero, conditions became more favorable for spontaneous emulsification. Between HLD values of -2.4 and -2.05, samples transitioned from non-spontaneous to spontaneous. This study aids in predicting spontaneous emulsion formation in saltwater environments for applications in nanoemulsion formation and wastewater remediation.

Physical features’ characterization of the water-in-mineral oil macro emulsion stabilized by a nonionic surfactant

Water-in-oil (w/o) emulsions are widely used in the food and pharmaceutical industries, among others. Moreover, the most common type of emulsion produced and handled in the oil industry processes is the w/o emulsion. This study investigates the features of a water-in-mineral oil macro-emulsion formulated with mineral oil as the continuous phase and Span 83 as the nonionic surfactant. Emulsions are prepared at room temperature according to the hydrophilic–lipophilic difference (HLD) theory and were tested for the mean droplet size and droplet size distribution, viscosity, and kinetic stability. An empirical correlation was introduced that estimates the viscosity of the water-in-mineral oil macro-emulsions and captures the non-Newtonian behavior at larger water fractions. The effect of electrolyte and internal phase concentration was specifically assessed on the emulsion flocculation and the stability of the system. Stability tests show a threshold electrolyte concentration exists after which droplets coalesce upon collision and flocculation. Salting out is most likely the responsible mechanism of phase separation in the emulsions with higher electrolyte concentrations. The results imply that sedimentation is accountable for the formation of different layers in emulsion with time. The sedimentation rate was intensified for emulsion with smaller water content (64% variation in 3 days between 10% emulsion and 40% emulsion) and concentrated emulsions were found to be more stable. Also, the size of the droplets was influenced by the NaCl concentration, surfactant concentration, and phase ratio.

Formulating and Retaining the Structure of Polymerized Surfactant Phases Using a Microemulsion Curvature Framework.

Nanostructured polymers contain features smaller than 100 nm that are useful in a wide range of areas, including photonics, biomedical materials, and environmental applications. Out of the myriad of nanostructured polymers, surfactant-templated polymers are versatile because of their ability to have tunable domain sizes, structure, and composition. This work addresses the gap between the formulation with industrial-grade polymerizable surfactants and the final structure of the polymer, using the hydrophilic-lipophilic difference (HLD) and net-average curvature (NAC) frameworks. HLD indicates the proximity of the formulation (surfactant and oil monomer selection, temperature, electrolyte concentration) to the phase inversion point, where HLD = 0. NAC uses the HLD to determine the curvature of the surfactant-oil-water interface, leading not only to the size and shape of micelles and bicontinuous isotropic (L3) systems but also to defining the most likely regions for lyotropic liquid crystal (LLC) existence and phase separation in ternary phase diagrams. Polymerizing LLC fluids produced nanostructured polymers with similar LLC structures that were highly swellable, but with low compressive strength. Polymerizing L3 fluids produced strong, but less water-swellable nanostructured polymers with a similar characteristic length to the parent L3 microemulsion. The relatively small scale of the parent LLC (∼6-8 nm) or L3 (∼3-4 nm) systems is consistent with the translucent nature of the polymers produced and the HLD-NAC predicted sizes.

Characterizing the Oil-like and Surfactant-like Behavior of Polar Oils

In this work, a bifunctional model was developed to fit and predict the phase inversion point (PIP) of microemulsions containing polar oils. This model incorporated the hydrophilic-lipophilic difference (HLD) equations, where HLD = 0 at the PIP. The model uses a Langmuir isotherm to account for the interfacial segregation of polar oils as a function of their concentration in the bulk oil phase. The segregated polar oil was treated as being surfactant-like, having a characteristic curvature (Cc). The polar oil in the bulk oil phase was characterized via an equivalent alkane carbon number (EACN). The Cc value was obtained considering deviations in the PIP at low polar oil concentrations. The EACN was determined considering PIP deviations at high polar oil concentrations. Naphthenic acid and dodecanol were used as model polar oils mixed with ionic and nonionic surfactants and nonpolar oils. The EACN of the polar oil was shown to be independent of the EACN of the nonpolar oil and likely independent of the surfactant. The Cc for dodecanol was likely independent of the surfactant used. For naphthenic acid, the Cc was independent of the nonpolar oil, and within a certain surfactant type (ionic, nonionic, or extended ionic), it was likely independent of the surfactant. For the naphthenic acid systems, the segregation predicted via the bifunctional model was consistent with experimental measurements of this segregation. Given that the bifunctional model only involves phase inversion experiments, it is a convenient method to determine the oil-like and surfactant-like nature of polar oils.

Hydrophilic-Lipophilic-Difference (HLD) Guided Formulation of Oil Spill Dispersants with Biobased Surfactants

Abstract The large-scale use of dispersants during the BP Horizon spill revealed various risks associated with these formulations, particularly the use of volatile organic compound (VOC) solvents linked to respiratory illnesses, and the poor biodegradability of surfactants. Previous attempts at solving these issues involved formulations of lecithin and polyethylene glycol ester of sorbitan monooleate (Tween® 80) that still required the use of a volatile solvent, ethanol. In this work, the Hydrophilic-Lipophilic Difference (HLD) framework was used to develop a lecithin formulation containing food-grade lipophilic (Glycerol MonoOleate – GMO- and sorbitan monooleate – Span® 80) and hydrophilic (polyglycerol caprylate) linkers in combination with a nonvolatile and mineral oil solvent with food additive status. The HLD parameters for lecithin, linkers, and oils were used to determine the lecithin-linker formulas that yielded HLD ∼0 (the surfactant phase inversion point), reaching interfacial tensions of 10−2 mN/m, and high emulsification effectiveness with diluted bitumen. This effectiveness was close to that obtained with a simulated dispersant, and superior to the lecithin-Tween® 80-ethanol formula. The lecithin-linker system produced 4–11 μm emulsified drops, sufficiently small to enhance the biodegradability of the dispersion.

A Continuous and Predictive Viscosity Model Coupled to a Microemulsion Equation of State

SummarySurfactant floods can attain high oil recovery if optimal conditions with ultralow interfacial tensions (IFT) are achieved in the reservoir. A recently developed equation-of-state (EoS) phase-behavior net-average-curvature (NAC) model based on the hydrophilic-lipophilic difference (HLD-NAC) has been shown to fit and predict phase-behavior data continuously throughout the Winsor I, II, III, and IV regions. The state-of-the-art for viscosity estimation, however, uses empirical nonpredictive based on of fits to salinity scans, even though other parameters change, such as the phase number and compositions. In this paper, we develop the first-of-its-kind microemulsion viscosity model that gives continuous viscosity estimates in composition space. This model is coupled to our existing HLD-NAC phase-behavior EoS.The results show that experimentally measured viscosities in all Winsor regions (two- and three-phase) are a function of phase composition, temperature, pressure, salinity, and the equivalent alkane carbon number (EACN). More specifically, microemulsion viscosities associated with the three-phase invariant point have an M shape as formulation variables change, such as from a salinity scan. The location and magnitude of viscosity peaks in the M are predicted from two percolation thresholds after tuning to viscosity data. These percolation thresholds as well as other model parameters change linearly with EACN and brine salinity. We also show that the minimum viscosity in the M shape correlates linearly with EACN or the viscosity ratio. Other key parameters in the model are also shown to linearly correlate with the EACN and brine salinity. On the basis of these correlations, two- and three-phase microemulsion viscosities are determined in five-component space (surfactant, two brine components, and two oil components) independent of flash calculations. Phase compositions from the EoS flash calculations are entered into the viscosity model. Fits to experimental data are excellent, as well as viscosity predictions for salinity scans not used in the fitting process.