Water/oil interfacial tension reduction - an interfacial entropy driven process

Enhanced oil recovery promoted by aqueous deep eutectic solvents on silica and calcite surfaces: a molecular dynamics study

Enhanced oil recovery (EOR) plays a critical role in optimizing oil extraction from existing fields to satisfy global energy demands while mitigating environmental impact. One promising EOR technique involves injecting water with reduced surface tension utilizing deep eutectic solvents (DESs). Despite early experimental support, the efficacy of aqueous-DES EOR varies and depends on factors such as connate water saturation, water salinity, and reservoir wettability. The recovery mechanisms for aqueous DESs are poorly understood due to the intricate nature of oil components and reservoir formation. In this paper, we investigate the role of DESs in the EOR process through molecular dynamics (MD) simulations. Three different types of DES molecules, such as choline chloride : urea (ChCl : U), choline chloride : ethylene glycol (ChCl : EG), and menthol : salicylic acid (M : SA) are used, for the recovery of dodecane (C12H26) oil from silica and calcite confined surfaces. We have demonstrated the structural characteristics of these systems by examining various physical properties, including interaction energies, density profiles, hydrogen bonds, and interfacial tension (IFT). Different concentrations (10 and 25 wt%) of DESs have been considered to unravel the effect of concentration on oil removal. The wettability of the substrate and the IFT between oil and aqueous DESs are critical physical properties that play a crucial role in influencing EOR phenomena. The IFT between water and oil decreases with the addition of DESs for all DES molecules, leading to a shift in surface behavior from oleophilic to oleophobic and ultimately facilitating the removal of oil from the substrate. Additionally, hydrogen bond formation between DESs and water has been calculated to elucidate its influence on the water/oil interface and substrate wettability. The study provides insights into the fundamental aspects of EOR processes for more effective and sustainable oil extraction.

Utilizing deterministic smart tools to predict recovery factor performance of smart water injection in carbonate reservoirs

Smart water injection (SWI) is a practical enhanced oil recovery (EOR) technique that improves displacement efficiency on micro and macro scales by different physiochemical mechanisms. However, the development of a reliable smart tool to predict oil recovery factors is necessary to reduce the challenges related to experimental procedures. These challenges include the cost and complexity of experimental equipment and time-consuming experimental methods for obtaining the recovery factor (RF). In this paper, three predictive algorithms including adaptive neuro-fuzzy inference system (ANFIS), artificial neural network (ANN), and multigene genetic programming (MGGP) are developed to predict the RF of smart water flooding in carbonate reservoirs. Accordingly, 205 data points from coreflooding tests and 122 from Amott-cell tests were collected from previous studies. Porosity, permeability, oil viscosity, and oil density at reservoir temperature, injection rate, total dissolved solids (TDS), temperature, injection time, and initial water saturation (Swi) were selected as the input parameters. Results show the great performance of ANN, compared to other employed algorithms. Coefficients of determination (R2) of ANN obtained from Amott-cell data for training, testing, validation, and overall data are 0.9748, 0.9021, 0.9765, and 0.9646, respectively. The corresponding values from coreflooding data are 0.9502, 0.9582, 0.9837, and 0.9523, respectively. Moreover, parametric sensitivity analysis was performed for the input parameters. Based on this analysis, time and injection rate have the most positive impact on the Amott-cell and coreflooding, respectively. Sensitivity analysis from Amott-cell data introduces TDS and oil viscosity have the most negative effects on RF performance. Furthermore, the most negative effects belong to porosity and permeability for coreflooding experiments.

Experimental and simulation-based characterization of surfactant adsorption layers at fluid interfaces

Adsorption of surfactants to fluid interfaces occurs in numerous technological and daily-life contexts. The coverage at the interface and other properties of the formed adsorption layers determine the performance of a surfactant with regard to the desired application. Given the importance of these applications, there is a great demand for the comprehensive characterization and understanding of surfactant adsorption layers. In this review, we provide an overview of suitable experimental and simulation-based techniques and review the literature in which they were used for the investigation of surfactant adsorption layers. We come to the conclusion that, while these techniques have been successfully applied to investigate Langmuir monolayers of water-insoluble surfactants, their application to the study of Gibbs adsorption layers of water-soluble surfactants has not been fully exploited. Finally, we emphasize the great potential of these methods in providing a deeper understanding of the behavior of soluble surfactants at interfaces, which is crucial for optimizing their performance in various applications.

Molecular Interactions of Perfluorinated and Branched Fluorine-Free Surfactants at Interfaces: Insights from a New Reliable Force Field

Per- and polyfluoroalkyl substances (PFAS) constitute a class of synthetic compounds with exceptional interfacial properties. Their widespread use in many industrial applications and consumer products, combined with their remarkable chemical and thermal stability, has led to their ubiquitous presence in environmental matrices, including surface water and groundwater. To replace PFAS with fluorine-free surfactants, it is necessary first to develop a deep molecular-level understanding of the mechanisms responsible for the exceptional properties of PFAS. For instance, it has been shown that fluorine-free surfactants with highly branched or methylated chains can achieve low surface tensions at air-water interfaces and can provide highly hydrophobic surface coatings. Although molecular simulations combined with experiments are promising for uncovering these mechanisms, the reliability of simulation results depends strongly on the accuracy of the force fields implemented. At the moment, atomistic force fields are not available to describe PFAS in a variety of environments. Ab initio methods could help fill this knowledge gap, but they are computationally demanding. As an alternative, ab initio calculations could be used to develop accurate force fields for atomistic simulations. In this work, a new algorithm is proposed, which, built from accurate ab initio calculations, yields force fields for perfluorinated sulfonic and perfluoroalkyl acids. The accuracy of the new force field was benchmarked against solvation free energy and interfacial tension data. The new force fields were then used to probe the interfacial behavior of the PFAS surfactants. The interfacial properties observed in our simulations were compared with those manifested by two branched fluorine-free surfactants. The good agreement achieved with experiments and ab initio calculations suggests that the proposed protocol could be implemented to study other perfluorinated substances and help in the design of fluorine-free surfactants for targeted applications.

Molecular Density Fluctuations Control Solubility and Diffusion for Confined Aqueous Hydrogen

Hydrogen's contribution to a sustainable energy transformation requires intermittent storage technologies, e.g., underground hydrogen storage (UHS). Toward designing UHS sites, atomistic molecular dynamics (MD) simulations are used here to quantify thermodynamic and transport properties for confined aqueous H2. Slit-shaped pores of width 10 and 20 Å are carved out of kaolinite. Within these pores, water yields pronounced hydration layers. Molecular H2 distributes along these hydration layers, yielding solubilities up to ∼25 times those in the bulk. Hydrogen accumulates near the siloxane surface, where water density fluctuates significantly. On the contrary, a dense hydration layer forms on the gibbsite surface, which is, for the most part, depleted of H2. Although confinement reduces water mobility, the diffusion of aqueous H2 increases as the kaolinite pore width decreases, also a consequence of water density fluctuations. These results relate to H2 permeability in underground hydrogen storage sites.

Assessment of spilled oil dispersion affected by dispersant: Characteristic, stability, and related mechanism

Oil dispersion, a crucial process in oil transport, involves the detachment of oil droplets from slicks and their introduction into the water column, influencing subsequent oil migration and transformation. This study examines oil dispersion, considering characteristics, stability, and mechanisms, while evaluating the impact of dispersants and salinity. Results show the significant role of surfactant type in dispersants on oil dispersion characteristics, with anionic surfactants exhibiting higher sensitivity to salinity changes compared to nonionic surfactants. The dispersion efficiency varies with salinity, with anionic surfactants performing better in low salinity (<20‰) and nonionic surfactants showing superior performance at 30-35‰ salinities. Rheological analysis illustrates the breakup and coalescence of oil droplets within the shear rates of breaking waves. An increase in interfacial film rigidity impedes the coalescence of oil droplets, contributing to the dynamic stability of the oil-water hybrid system. The use of GM-2, a nonionic dispersant, results in the formation of a solid-like interface, characterized by increased elastic modulus, notably at 20‰ salinity. However, stable droplet size distribution (DSD) at 35‰ salinity for 60 h suggests droplets can remain dispersed in seawater. The enhancement of stability of oil dispersion is interpreted as the result of two mechanisms: stabilizing DSD and developing the strength of viscoelastic interfacial film. These findings offer insights into oil dispersion dynamics, highlighting the importance of surfactant selection and salinity in governing dispersion behavior, and elucidating mechanisms underlying dispersion stability.

Mechanism of nearshore sediment-facilitated oil transport: New insights from causal inference analysis

A quantitative understanding of spilled oil transport in a nearshore environment is challenging due to the complex physicochemical processes in aqueous conditions. The physicochemical processes involved in oil sinking mainly include oil dispersion, sediment settling, and oil-sediment interaction. For the first time, this work attempts to address the sinking mechanism in petroleum contaminant transport using structural causal models based on observed data. The effects of nearshore salinity distribution from the estuary to the ocean on those three processes are examined. The causal inference reveals sediment settling is the crucial process for oil sinking. Salinity indirectly affects oil sinking by promoting sediment settling rather than directly affecting oil-sediment interaction. The increase of salinity from 0‰ to 35‰ provides a natural enhancement for sediment settling. Notably, unbiased causal effect estimates demonstrate the strongest positive causal effect on the settling efficiency of sediments is posed by increasing oil dispersion effectiveness, with a normalized value of 1.023. The highest strength of the causal relationship between oil dispersion and sediment settling highlights the importance of the dispersing characteristics of spilled oil to sediment-facilitated oil transport. The employed logic, a data-driven method, will shed light on adopting advanced causal inference tools to unravel the complicated contaminants' transport.

Machine learning approaches for estimating interfacial tension between oil/gas and oil/water systems: a performance analysis

Interfacial tension (IFT) is a key physical property that affects various processes in the oil and gas industry, such as enhanced oil recovery, multiphase flow, and emulsion stability. Accurate prediction of IFT is essential for optimizing these processes and increasing their efficiency. This article compares the performance of six machine learning models, namely Support Vector Regression (SVR), Random Forests (RF), Decision Tree (DT), Gradient Boosting (GB), Catboosting (CB), and XGBoosting (XGB), in predicting IFT between oil/gas and oil/water systems. The models are trained and tested on a dataset that contains various input parameters that influence IFT, such as gas-oil ratio, gas formation volume factor, oil density, etc. The results show that SVR and Catboost models achieve the highest accuracy for oil/gas IFT prediction, with an R-squared value of 0.99, while SVR outperforms Catboost for Oil/Water IFT prediction, with an R-squared value of 0.99. The study demonstrates the potential of machine learning models as a reliable and resilient tool for predicting IFT in the oil and gas industry. The findings of this study can help improve the understanding and optimization of IFT forecasting and facilitate the development of more efficient reservoir management strategies.

Synthesis and Application of a Novel Multi-Branched Block Polyether Low-Temperature Demulsifier

In this paper, a low-temperature thick oil demulsifier with high polarity was prepared by introducing ethylene oxide, propylene oxide block, and butylene oxide using m-diphenol as a starting agent. The main reasons for the difficulty involved in the low-temperature emulsification of extractive fluids were explained by analyzing the synthetic influencing factors and infrared spectra of the star comb polymer (PR-D2) and by analyzing the four fractions, interfacial energies, and zeta potentials of crude oils from the Chun and Gao fields. The effects of PR-D2 surfactant on the emulsification performance of crude oil recovery fluids were investigated via indoor and field experiments. The experimental results indicate that the optimal synthesis conditions for this emulsion breaker are as follows: a quality ratio of ionic reaction intermediates and meso-diphenol of R = 10:1; 1 g of the initiator; a polymerization temperature of 80 °C; and a reaction time of 8 h. Colloidal asphaltenes in the crude oil were the main factor hindering the low-temperature demulsification of the Gao oilfield's extractive fluids, and the reason for the demulsification difficulty of the extractive fluids in the Chun oilfield is that the temperature of demulsification is lower than the wax precipitation point. The demulsification rate of the Chun oilfield's extractive fluids reached more than 98% when the PR-D2 concentration reached 150 mg/L at 43 °C. The demulsification rate of the Gao oilfield's extractive fluids reached more than 98% at a PR-D2 concentration of 150 mg/L at 65 °C. The field experiments show that the Chun oilfield's extractive fluids can still demulsify after the temperature is reduced to 43 °C in winter. The emulsification temperature of the Gao oilfield's extractive fluids was reduced from 73 °C to 68 °C, with an excellent demulsification effect.

Emulsifier adsorption kinetics influences drop deformation and breakup in turbulent emulsification

Turbulent drop breakup is of large importance for applications such as food and pharmaceutical processing, as well as of substantial fundamental scientific interest. Emulsification typically takes place in the presence of surface-active emulsifiers (natural occurring and/or added). Under equilibrium conditions, these lower the interfacial tension, enabling deformation and breakup. However, turbulent deformation is fast in relation to emulsifier kinetics. Little is known about the details of how the emulsifier influences drop deformation under turbulent conditions. During the last years, significant insight in the mechanism of turbulent drop breakup has been reached using numerical experiments. However, these studies typically use a highly simplistic description of how the interface responds to turbulent stress. This study investigates how the limited exchange rate of emulsifier between the bulk and the interface influences the deformation process in turbulent drop breakup for application-relevant emulsifiers and concentrations, in the context of state-of-the-art single drop breakup simulations. In conclusion, if the Weber number is high or the emulsifier is supplied at a concentration giving an adsorption time less than 1/10th of the drop breakup time, deformation proceeds as if the emulsifier adsorbed infinitely fast. Otherwise, the limited emulsifier kinetics delays breakup and can alter the breakup mechanism.

Gatifloxacin Loaded Nano Lipid Carriers for the Management of Bacterial Conjunctivitis

Bacterial conjunctivitis (BC) entails inflammation of the ocular mucous membrane. Early effective treatment of BC can prevent the spread of the infection to the intraocular tissues, which could lead to bacterial endophthalmitis or serious visual disability. In 2003, gatifloxacin (GTX) eyedrops were introduced as a new broad-spectrum fluoroquinolone to treat BC. Subsequently, GTX use was extended to other ocular bacterial infections. However, due to precorneal loss and poor ocular bioavailability, frequent administration of the commercial eyedrops is necessary, leading to poor patient compliance. Thus, the goal of the current investigation was to formulate GTX in a lipid-based drug delivery system to overcome the challenges with the existing marketed eyedrops and, thus, improve the management of bacterial conjunctivitis. GTX-NLCs and SLNs were formulated with a hot homogenization-probe sonication method. The lead GTX-NLC formulation was characterized and assessed for in vitro drug release, antimicrobial efficacy (against methicillin-resistant Staphylococcus aureus and Pseudomonas aeruginosa), and ex vivo permeation. The lead formulation exhibited desired physicochemical characteristics, an extended release of GTX over a 12 h period, and was stable over three months at the three storage conditions (refrigerated, room temperature, and accelerated). The transcorneal flux and permeability of GTX from the GTX-NLC formulation were 5.5- and 6.0-fold higher in comparison to the commercial eyedrops and exhibited a similar in vitro antibacterial activity. Therefore, GTX-NLCs could serve as an alternative drug delivery platform to improve treatment outcomes in BC.

Microscopic insights on clathrate hydrate growth from non-equilibrium molecular dynamics simulations

Clathrate hydrates form and grow at interfaces. Understanding the relevant molecular processes is crucial for developing hydrate-based technologies. Many computational studies focus on hydrate growth within the aqueous phase using the 'direct coexistence method', which is limited in its ability to investigate hydrate film growth at hydrocarbon-water interfaces. To overcome this shortcoming, a new simulation setup is presented here, which allows us to study the growth of a methane hydrate nucleus in a system where oil-water, hydrate-water, and hydrate-oil interfaces are all simultaneously present, thereby mimicking experimental setups. Using this setup, hydrate growth is studied here under the influence of two additives, a polyvinylcaprolactam oligomer and sodium dodecyl sulfate, at varying concentrations. Our results confirm that hydrate films grow along the oil-water interface, in general agreement with visual experimental observations; growth, albeit slower, also occurs at the hydrate-water interface, the interface most often interrogated via simulations. The results obtained demonstrate that the additives present within curved interfaces control the solubility of methane in the aqueous phase, which correlates with hydrate growth rate. Building on our simulation insights, we suggest that by combining data for the potential of mean force profile for methane transport across the oil-water interface and for the average free energy required to perturb a flat interface, it is possible to predict the performance of additives used to control hydrate growth. These insights could be helpful to achieve optimal methane storage in hydrates, one of many applications which are attracting significant fundamental and applied interests.

Computational Strategies for Entropy Modeling in Chemical Processes

Computational simulations of entropy are important in understanding the thermodynamic forces that drive chemical reactions on a molecular scale. In recent years, various algorithms have been developed and applied in conjunction with molecular modeling techniques to evaluate the change of entropy in solvation, hydrophobic interactions, and chemical reactions. The aim of this review is to highlight four specific computational entropy calculation methods: normal mode analysis, free volume theory, two-phase thermodynamics, and configurational entropy modeling. The technical aspects, applications, and limitations of each method will be discussed in detail.

From Lactose to Alkyl Galactoside Fatty Acid Esters as Non-Ionic Biosurfactants: A Two-Step Enzymatic Approach to Cheese Whey Valorization

A library of alkyl galactosides was synthesized to provide the "polar head" of sugar fatty acid esters to be tested as non-ionic surfactants. The enzymatic transglycosylation of lactose resulted in alkyl β-D-galactopyranosides, whereas the Fischer glycosylation of galactose afforded isomeric mixtures of α- and β-galactopyranosides and α- and β-galactofuranosides. n-Butyl galactosides from either routes were enzymatically esterified with palmitic acid, used as the fatty acid "tail" of the surfactant, giving the corresponding n-butyl 6-O-palmitoyl-galactosides. Measurements of interfacial tension and emulsifying properties of n-butyl 6-O-palmitoyl-galactosides revealed that the esters of galactopyranosides are superior to those of galactofuranosides, and that the enantiopure n-butyl 6-O-palmitoyl-β-D-galactoside, prepared by the fully enzymatic route, leads to the most stable emulsion. These results pave the way to the use of lactose-rich cheese whey as raw material for the obtainment of bio-based surfactants.

Wetting Properties of Clathrate Hydrates in the Presence of Polycyclic Aromatic Compounds: Evidence of Ion-Specific Effects

Polycyclic aromatic hydrocarbons (PAHs) have attracted remarkable multidisciplinary attention due to their intriguing π-π stacking configurations, showing enormous opportunity for their use in a variety of advanced applications. To secure progress, detailed knowledge on PAHs' interfacial properties is required. Employing molecular dynamics, we probe the wetting properties of brine droplets (KCl, NaCl, and CaCl₂) on sII methane-ethane hydrate surfaces immersed in various oil solvents. Our simulations show synergistic effects due to the presence of PAHs compounded by ion-specific effects. Our analysis reveals phenomenological correlations between the wetting properties and a combination of the binding free-energy difference and entropy changes upon oil solvation for PAHs at oil/brine and oil/hydrate interfaces. The detailed thermodynamic analysis conducted upon the interactions between PAHs and various interfaces identifies molecular-level mechanisms responsible for wettability alterations, which could be applicable for advancing applications in optics, microfluidics, biotechnology, medicine, as well as hydrate management.