Complex Liquid Mixtures Research Articles

Controlled organic solvent transport in ultramicroporous carbon membranes

The drive to decarbonize chemical processes necessitates exploring low-energy solutions for separating complex liquid mixtures ubiquitous in food, pharmaceuticals, petrochemical, and synthetic fuel production industries. This report comprehensively investigates conceptualizing and implementing two novel organic solvent separation processes: Organic Solvent Forward Osmosis (OSFO) and Organic Solvent Pressure Assisted Osmosis (OSPAO). The intrinsic molecular specificity of ultramicroporous carbon molecular sieve (CMS) membranes allowed the unprecedented separation of a complex mixture of short-chain alcohols (e.g., methyl alcohol, ethyl alcohol, and isopropyl alcohol) at room temperature. A new hybridized membrane-based separation methodology, OSPAO, that combines the elements of organic solvent nanofiltration (OSN) and OSFO is introduced. CMS-based OSPAO demonstrated a marked enhancement in the flux of organic species permeate, considerably improving separation efficiencies. The separation modalities presented in this report underscore the essential role of osmosis in the differentiation of organic solvents, thereby contributing valuable insights to osmosis-based separation technologies.

Unexpected Molecular Sieving of Xylene Isomer Using Tethered Ligand in Polymer-Metal-Organic Frameworks (polyMOFs).

Promising advances in adsorption technology can lead to energy-efficient solutions in industrial sectors. This work presents precise molecular sieving of xylene isomers in the polymer-metal-oragnic framework (polyMOF), a hybrid porous material derived from the parent isoreticular MOF-1 (IRMOF-1). PolyMOFs are synthesized by polymeric ligands bridged by evenly spaced alkyl chains, showing reduced pore sizes and enhanced stabilities compared to its parent material due to tethered polymer bridge within the pores while maintaining the original rigid crystal lattice. However, the exact configuration of the ligands within the crystals remain unclear, posing hurdles to predicting the adsorption performances of the polyMOFs. This work reveals that the unique pore structure of polyIRMOF-1-7a can discriminate xylene isomers with sub-angstrom size differences, leading to highly selective adsorption of p-xylene over other isomers and alkylbenzenes in complex liquid mixtures (αpX/OM = 15 and αpX/OME = 9). The structural details of the polyIRMOF-1-7a are elucidated through computational studies, suggesting a plausible configuration of alkyl chains within the polyMOF crystal, which enable a record-high p-xylene selectivity and stability in liquid hydrocarbon. With this unprecedented molecular selectivity in MOFs, "polymer-MOF" hybridization is expected to meet rigorous requirements for high-standard molecular sieving through precisely tunable and highly stable pores.

Characterizing Microheterogeneity in Liquid Mixtures via Local Density Fluctuations.

We present a novel approach to characterize and quantify microheterogeneity and microphase separation in computer simulations of complex liquid mixtures. Our post-processing method is based on local density fluctuations of the different constituents in sampling spheres of varying size. It can be easily applied to both molecular dynamics (MD) and Monte Carlo (MC) simulations, including periodic boundary conditions. Multidimensional correlation of the density distributions yields a clear picture of the domain formation due to the subtle balance of different interactions. We apply our approach to the example of force field molecular dynamics simulations of imidazolium-based ionic liquids with different side chain lengths at different temperatures, namely 1-ethyl-3-methylimidazolium chloride, 1-hexyl-3-methylimidazolium chloride, and 1-decyl-3-methylimidazolium chloride, which are known to form distinct liquid domains. We put the results into the context of existing microheterogeneity analyses and demonstrate the advantages and sensitivity of our novel method. Furthermore, we show how to estimate the configuration entropy from our analysis, and we investigate voids in the system. The analysis has been implemented into our program package TRAVIS and is thus available as free software.

Determination of self-diffusion coefficients in mixtures with benchtop 13C NMR spectroscopy via polarization transfer.

Nuclear magnetic resonance (NMR) is an established method to determine self-diffusion coefficients in liquids with high precision. The development of benchtop NMR spectrometers makes the method accessible to a wider community. In most cases, 1H NMR spectroscopy is used to determine self-diffusion coefficients due to its high sensitivity. However, especially when using benchtop NMR spectrometers for the investigation of complex mixtures, the signals in 1H NMR spectra can overlap, hindering the precise determination of self-diffusion coefficients. In 13C NMR spectroscopy, the signals of different compounds are generally well resolved. However, the sensitivity of 13C NMR is significantly lower than that of 1H NMR spectroscopy leading to very long measurement times, which makes diffusion coefficient measurements based on 13C NMR practically infeasible with benchtop NMR spectrometers. To circumvent this problem, we have combined two known pulse sequences, one for polarization transfer from 1H to the 13C nuclei (PENDANT) and one for the measurement of diffusion coefficients (PFG). The new method (PENPFG) was used to measure the self-diffusion coefficients of three pure solvents (acetonitrile, ethanol and 1-propanol) as well as in all their binary mixtures and the ternary mixture at various compositions. For comparison, also measurements of the same systems were carried out with a standard PFG-NMR routine on a high-field NMR instrument. The results are in good agreement and show that PENPFG is a useful tool for the measurement of the absolute value of the self-diffusion coefficients in complex liquid mixtures with benchtop NMR spectrometers.

Data-driven predictions of complex organic mixture permeation in polymer membranes

Membrane-based organic solvent separations are rapidly emerging as a promising class of technologies for enhancing the energy efficiency of existing separation and purification systems. Polymeric membranes have shown promise in the fractionation or splitting of complex mixtures of organic molecules such as crude oil. Determining the separation performance of a polymer membrane when challenged with a complex mixture has thus far occurred in an ad hoc manner, and methods to predict the performance based on mixture composition and polymer chemistry are unavailable. Here, we combine physics-informed machine learning algorithms (ML) and mass transport simulations to create an integrated predictive model for the separation of complex mixtures containing up to 400 components via any arbitrary linear polymer membrane. We experimentally demonstrate the effectiveness of the model by predicting the separation of two crude oils within 6-7% of the measurements. Integration of ML predictors of diffusion and sorption properties of molecules with transport simulators enables for the rapid screening of polymer membranes prior to physical experimentation for the separation of complex liquid mixtures.

The Autonomous Formulation Laboratory: An Open Liquid Handling Platform for Formulation Discovery Using X-ray and Neutron Scattering

The application of machine learning techniques to X-ray scattering experiments has been of significant recent interest, offering advances in areas such as the study of complex oxides. Despite these success stories, few applications of these techniques into soft materials have been reported, likely due in part to the highly nonequilibrium nature of soft materials phase spaces and the complexities associated with autonomous formulation preparation. Here, we report the design of the Autonomous Formulation Laboratory, a robust platform for the automated synthesis and measurement of complex liquid mixtures using X-ray and neutron scattering, readily extensible to system-specific complementary techniques such as spectroscopy and rheometry. We describe the application of the platform to generate dense, highly reproducible data sets on material systems ranging from silica nanoparticles to block copolymer micelles. We expect the platform to prove revolutionary to the understanding of the stability of complex liquid formulations and the resulting data sets to provide fertile ground for the development of machine learning techniques for complex soft materials phase spaces.

Dry Glass Reference Perturbation Theory Predictions of the Temperature and Pressure Dependent Separations of Complex Liquid Mixtures Using SBAD-1 Glassy Polymer Membranes.

In this work we apply dry glass reference perturbation theory (DGRPT) within the context of fully mutualized diffusion theory to predict the temperature and pressure dependent separations of complex liquid mixtures using SBAD-1 glassy polymer membranes. We demonstrate that the approach allows for the prediction of the membrane-based separation of complex liquid mixtures over a wide range of temperature and pressure, using only single-component vapor sorption isotherms measured at 25 °C to parameterize the model. The model was then applied to predict the membrane separation of a light shale crude using a structure oriented lumping (SOL) based compositional model of petroleum. It was shown that when DGRPT is applied based on SOL compositions, the combined model allows for the accurate prediction of separation performance based on the trend of both molecular weight and molecular class.

Measurement and modeling of methane diffusion in hydrocarbon mixtures

Methane (CH4) dissolution and diffusive mass transfer in liquid hydrocarbon mixtures is of key interest in the context of enhanced oil recovery from tight shales. In this paper, we have studied CH4 dissolution and diffusion in normal alkane mixtures at a temperature of 50 ⁰C and at pressures of ∼8 MPa. For the measurement of CH4 dissolution/diffusion in bulk liquid hydrocarbon mixtures, we have utilized a high pressure and temperature, constant-volume diffusion (CV-D) setup. We have studied CH4 diffusion in mixtures with three long-chain normal alkanes: decane (C10), dodecane (C12) and hexadecane (C16). We have measured CH4 solubility and diffusion in its binary mixtures with each of these three normal alkanes, as well as in ternary and quaternary mixtures. During the experiments, the swelling of the liquid mixture due to CH4 dissolution was measured in situ via a cathetometer and was subsequently integrated into the data analysis. A key conclusion from this study is that the solubility and transport properties of the multicomponent mixtures can be predicted accurately from binary mixture measurements using an appropriate Equation of State (EOS) and Wilke’s simplification of the classical Maxwell-Stefan (MS) diffusion theory. This observation can facilitate accurate prediction of diffusive mass transfer in more complex liquid hydrocarbon mixtures.

A model for the separation of complex liquid mixtures with glassy polymer membranes: A thermodynamic perspective

In this work, a new model is developed to predict the separation of organic solvent mixtures with glassy polymer membranes. Particular attention is paid to thermodynamic contributions such as guest solubility and guest-induced polymer swelling, and how these contributions affect the flux in multi-component mixtures. The thermodynamic contributions are complicated by the fact that the membranes are glassy polymers. The thermodynamic aspects of the diffusion problem are calculated using DGRPT (dry glass reference perturbation theory), which extends the non-equilibrium thermodynamics of glassy polymers (NETGP) such that polymer swelling is calculated self-consistently in the theory. The diffusion model for pure fluids diffusing through the membrane is obtained through Maxwell-Stefan equations where the polymer membrane is stationary. The mixture diffusion model is then constructed using a simple diffusivity averaging scheme on this pure fluid result. The model is then shown to accurately predict binary and complex mixture separations in SBAD-1, STARMEM-240, and Torlon membranes. We highlight the ability of the model accurately predict membrane based fractionation of crude oil, using only the sorption isotherms of toluene and octane as input to the model. • A new membrane model was proposed for multicomponent liquid mixtures in glassy polymer membranes. • The role of pressure in liquid phase reverse osmosis separations is discussed. • The model correctly predicts the separation of crude oil using only two experimental sorption isotherms.

Abatement of chlorobenzenes in aqueous phase by persulfate activated by alkali enhanced by surfactant addition

Sites polluted by dense non-aqueous phases (DNAPLs) constitute an environmental concern. In situ chemical oxidation (ISCO) application is limited since oxidation often occurs in the aqueous phase and contaminants are usually hydrophobic. In this work, ISCO enhanced by the surfactant addition (S–ISCO) was studied for a complex liquid mixture of chlorinated organic compounds (COCs) using persulfate (PS) activated by alkali (PSA) as oxidant and Emulse-3® as a commercial non-ionic surfactant. The reaction between E3 and PSA was investigated in the absence and presence of solubilized COCs in the following concentration ranges: COCs 1.2–50 mM, PS 84–336 mM, NaOH:PS molar ratio of 2, and surfactant concentration 1–10 g·L−1.In the experiments carried out in the absence of COCs, the unproductive consumption of PS was studied. The higher the surfactant concentration, the lower the ratio PS consumed to the initial surfactant concentration due to more complex micelle structures hindering the oxidation of surfactant molecules. This hindering effect was also noticed in the oxidation of solubilized COCs. The reduction of chlorobenzenes by PSA was negligible at surfactant concentrations above 2.5 g·L−1, independently of the COCs concentration solubilized. Instead, a surfactant concentration of about 1 and PS concentration of 168 mM yielded a significant decrease in the time required to abate a mass of DNAPL, compared with an ISCO process, with a bearable increase in the unproductive consumption of PS.

Tuning the properties of ionic liquids by mixing with organic solvents: The case of 1-butyl-3-methylimidazolium glutamate with alkanols

Binary liquid mixtures of 1-butyl-3-methylimidazolium glutamate acid ([bmim][glu]) with alkanols (1-propanol, isobutanol and 1,2-propanediol) are studied in the full composition range as a function of temperature using a combined experimental and computational chemistry approach. Experimental thermophysical information as well as derived excess and mixing properties allowed to characterize these complex liquid mixtures in terms of deviation from ideality as well their relationships with the developed intermolecular forces and changes with the type of considered alkanols. Theoretical studies using quantum chemistry and classical molecular dynamics simulations provided nanoscopic characterization on the studied fluids, with particular attention to the extension and nature of hydrogen bonding and its effects on molecular arrangements and mixed fluids’ properties. The reported study provides a micro and macroscopic characterization of the considered aminoacid-based ionic liquid mixtures, thus contributing to the knowledge of sustainable ionic liquid systems mixed with organic solvents for fine tuning properties and developing task specific applications.

The role of skin layer defects in organic solvent reverse osmosis membranes

The fractionation of complex liquid hydrocarbon mixtures is an important and emerging area of membrane science. Polymeric asymmetric hollow fiber membranes have the potential to be used for this purpose, especially if the size and number of defects in the membrane skin layer can be precisely engineered. Here, we fabricated various “defect-engineered” Torlon hollow fiber membranes by modifying hollow fiber spinning conditions and spin dopes to study the role of skin layer defects in the organic solvent reverse osmosis (OSRO) membranes. The quality of the membranes was investigated using several sets of pure gas permeation experiments, which provided input data for a permeation resistance model that estimates the pore size and surface porosity of the asymmetric hollow fiber membrane. We develop and experimentally validate a resistance permeation model for solvent permeation and utilize the surface properties derived from the gas permeation experiments to estimate the relative permeation rates of solvents in a mixture. The approach outlined here highlights the interconnection between gas permeation analysis and OSRO separation performance using Torlon hollow fiber membranes as an exemplar test case. The solvent permeation model is then utilized to provide quantitative insight on the differences between OSRO and organic solvent nanofiltration (OSN), and highlight the important transition region between these two modalities.

Determining Dielectric Constants for Complex Solvent Mixtures by Microwave Sensing and Model Prediction.

The frequency-dependent dielectric constant is a basic fluid property that is currently challenging to determine for complex liquid mixtures. Here, we report the determination of effective dielectric constants for various solvent mixtures under flow conditions using a simple in-line microwave Fabry-Pérot interferometer cable sensor. An ideal solution model-based mixing rule has been established and demonstrated for significantly improved prediction of dielectric constants for single-phase solvent mixtures. However, the current mixing rules exhibit large deviations for immiscible water/oil dispersions apparently because of the effects of strong interfacial polarizations on the overall mixture polarizability that are not accounted for by the models.

Resistive properties of Janson’s point contacts in the conditions of polarization inversion

The sensitive element of a new quantum sensor generation is the Janson dendritic point contact. Analytes that are in the space surrounding the sensitive element are able to interact with the freshly formed surface of the conduction channel of the Janson quantum point contact, as well as with the surface of the dendrite during its growth. This interaction provides the influence of the substances under study on the configuration of the output characteristic of the sensor, represented by the system conductivity histogram. The conductivity histogram is built on the basis of the chrono-resistogram of the self-oscillating point-contact cyclic switchover effect, which is directly recorded under self-oscillation conditions. In the structure of the sensor element, Janson's dendritic point contact is immersed in an electrolyte and in an electric field forms a chrono-resistogram, which depends on the environment composition. The paper considers one of the aspects of such chrono-resistograms formation. The features of a gapless electrochemical system in the process of realizing the point-contact cyclic switchover effect are analyzed. Modeling the sensitive element in the form of a gapless electrode system allowed explaining the mechanism and dynamics of the transition “Janson point contact – dendrite and counter electrode in the electrolyte”. The most important parameter of the gapless electrode system is the coordinate of the polarization inversion boundary. It is shown that the idea of the coordinate of the polarization inversion boundary plays a fundamental role in modeling the resistive properties of a point-contact system and its lifetime. The synthesized mathematical models describe well the experimentally obtained dependences of the resistance on the exposure time of the nanostructure in an electric field. It was found that the dependence of the contact resistance on the exposure time, obtained under the assumption of a linear distribution of the anodic polarization along the main axis of the conduction channel, is described by a differential equation in which the growth rate of resistance is directly proportional to the cube of this resistance. The materials obtained make it possible to purposefully optimize the design parameters and operating conditions of sensor devices based on Janson point contacts for the analysis of complex gaseous and liquid mixtures.

A study on droplets dispersion and deposition characteristics under supersonic spray flow for nanomaterial coating applications

Supersonic spray coating of nanomaterials, owing to high impact velocity of particles, offers significant potential to improve the physical and mechanical properties of target surfaces. Rather than handling individual light nano-scale particles directly with a number of limitations, aqueous nanomaterial colloids and suspensions can be supersonically deposited onto surfaces by converting these complex liquid mixtures into the form of atomized micro-scale droplets. Dispersion and deposition characteristics of these droplets play a vital role in the quality and efficacy of the resultant nanomaterial coating. In the present study, comprising numerical modeling and experimental validation, we investigate details of the dispersion and deposition characteristics of droplets under supersonic flow conditions. In the numerical study, a two-way coupled discrete phase modeling is used to track the discrete phase (i.e., droplets) and to investigate the interaction of droplets with the continuous gas phase (i.e., high-velocity driving gas) in regard to their properties and conditions. The results through computational fluid dynamics (CFD) show that driving gas properties (i.e., temperature, pressure, gas type) and droplet size play a prominent role in droplets dispersion and deposition phenomena. In particular, smaller droplets (≤2 μm) are observed to be more susceptible to turbulent dispersion and evaporation. In the experimental study, an atomization-based supersonic spray system is developed for model validation and a case example of nano-coating applications. The CFD modeling results are validated by particle image velocimetry (PIV) measurements. A case study of titanium dioxide (TiO2) nanomaterial coating on a polymer substrate (ITO/PET film) is performed to demonstrate the suitability of the present spray deposition system, which also addresses the current challenges of TiO2 coating onto ITO/PET surface.

On the behavior of quercetin + organic solvent solutions and their role for C60 fullerene solubilization

The nature of flavonoids in polar organic solvents solutions is studied using classical molecular dynamics simulations considering quercetin as an archetypical flavonoid and acetone, dimethylformamide and dimethyl sulfoxide as representatives of solvents with different polarity. The solvation, intermolecular forces (hydrogen bonding) and interactions of the flavonoid with the solvents are analyzed. Likewise, the role of quercetin on changing the solvent properties and the possibility of acting as a solubility enhancer for fullerenes (C60) are studied by considering the properties of C60 fullerene in quercetin plus polar solvents solutions. The reported results provide information on the nature of the considered complex liquid mixtures and analyze the possibility of using flavonoids as natural, non-toxic, modifiers of traditional polar organic solvents and to improve the solubility of complex solutes such as fullerene nanoparticles.

Framework for predicting the fractionation of complex liquid feeds via polymer membranes

The separation of complex liquid hydrocarbon mixtures was recently demonstrated using the glassy polymer SBAD-1, showing that small molecule fractionation is possible by such organic membrane materials. Here, we develop a framework that will enable workable predictions of permeate flux and composition in complex hydrocarbon liquids through intrinsically porous glassy polymers. The predictions are made by incorporating experimentally-derived unary sorption and diffusion parameters in a Maxwell-Stefan framework coupled with multicomponent sorption models and various distinct diffusion phenomena. Across the range of sorption and diffusion phenomena considered, both the conventional Flory-Huggins model and the proposed Langmuir + Flory-Huggins sorption model combined with a simple average guest diffusivity or a more complex free-volume theory-based transport resulted in the lowest prediction error for three chosen multicomponent separations. The proposed Maxwell-Stefan framework simply requires pure component transport parameters to allow a fast approximation of the separation of multicomponent liquid hydrocarbon feeds that can potentially be extended to more complex feeds such as crude oil fractions.

On interactions in binary mixtures used in solvent extraction: Insights from combined Isothermal Titration Calorimetry experiments and Molecular Dynamics simulations

Despite its importance, the description of liquid–liquid extraction is made difficult because the link between the experimental methods and the interactions present in the solution is not direct due to the many organisation phenomena that can occur. We propose a new methodology combining microcalorimetric measurements and molecular modelling to better describe the nature and strength of these interactions in these complex fluids by focusing on extractant-diluent mixtures (N,N-dialkylamides + n-alkanes). Enthalpies of dilution were obtained by microcalorimetric measurements at 298 K for each n-dodecane and n-heptane with DEHiBA and for n-dodecane with DEHBA. These results have been compared, thanks to a new method that we present here, to molecular dynamics simulations carried out on these same systems. We especially analyzed the influence of the alkyl branching of the extracting molecules and the role of the diluent. Globally, the excess enthalpy is such that these mixtures are energetically not very different from regular solutions but the detailed balance shows an important attraction between the extractants, which can lead to the formation of macromolecular entities favouring extraction. Calorimetry appears to be a method of choice for linking experiments and molecular modelling in these complex liquid mixtures, and experimental developments could benefit from using it more often, especially to validate force-fields.

MicroRNA (miRNA) Differential Expression and Exposure to Crude-Oil- Related Compounds.

This review summarizes studies on miRNA differential regulation related to exposure to crude oil and 20 different crude oil chemicals, such as hydrocarbons, sulphur, nitrogen, and metal- containing compounds. It may be interesting to explore the possibility of using early post-transcriptional regulators as a potential novel exposure biomarker.Crude oil has been defined as a highly complex mixture of solids, liquids, and gases. Given the toxicological properties of the petroleum components, its extraction and elaboration processes represent high-risk activities for the environment and human health, especially when accidental spills occur. The effects on human health of short-term exposure to petroleum are well known, but chronic exposure effects may variate depending on the exposure type (i.e., work, clean-up activities, or nearby residence).As only two studies are focused on miRNA differential expression after crude-oil exposure, this review will also analyse the bibliography concerning different crude-oil or Petroleum-Related Compounds (PRC) exposure in Animalia L. kingdom and how it is related to differential miRNA transcript levels. Papers include in vitro, animal, and human studies across the world.A list of 10 miRNAs (miR-142-5p, miR-126-3p, miR-24-3p, miR-451a, miR-16-5p, miR-28-5p, let-7b-5p, miR-320b, miR-27a-3p and miR-346) was created based on bibliography analysis and hypothesised as a possible “footprint” for crude-oil exposure. miRNA differential regulation can be considered a Big-Data related challenge, so different statistical programs and bioinformatics tools were used to have a better understanding of the biological significate of the most interesting data.

A Model for the Separation of Complex Liquid Mixtures with Glassy Polymer Membranes: A Thermodynamic Perspective

A Model for the Separation of Complex Liquid Mixtures with Glassy Polymer Membranes: A Thermodynamic Perspective