254 results found
Valsecchi M, Galindo A, Jackson G, 2023, Modeling Sorption of Hydrocarbons in Polyethylene with the SAFT-γ Mie Approach Combined with a Statistical-Mechanical Model to Describe Semicrystalline Polymers., Macromolecules, Vol: 56, Pages: 9952-9968, ISSN: 0024-9297
A recently developed statistical-mechanical model is applied systematically to estimate the fraction of tie-molecules (polymer chains linking different crystals directly or via entanglements) in semicrystalline polyethylene (PE) samples. The amorphous domains of the polymer are divided into constrained interlamellar domains and "free" outer-lamellar domains. A set of model parameters is assigned to each sample by correlating previous experimental measurements and minimizing the difference between the predicted solubility of pure hydrocarbons in the sample and the experimental values. We show that the sorption isotherms of multiple pure fluids in each sample can be described by a single parameter set, proving that the polymer-solute interactions (described accurately by the SAFT-γ Mie EoS) are decoupled from the sample-specific properties of the polymer. We find that ∼30% of the crystalline stems in the lamellae of PE are connected to tie-molecules, within the bounds suggested by previous theoretical and computational work. The transferability of the sample-specific parameters is assessed by predicting cosolubility effects and solubility at different temperatures, leading to good agreement with experimental data.
Herdes C, Galindo A, Jackson G, 2023, Thermodynamics 2022 conference, University of Bath, Bath, UK, 7-9 September 2022, MOLECULAR PHYSICS, ISSN: 0026-8976
Gui L, Yu Y, Oliyide TO, et al., 2023, Integrating model-based design of experiments and computer-aided solvent design, Computers & Chemical Engineering, Vol: 177, Pages: 1-15, ISSN: 0098-1354
Computer-aided molecular design (CAMD) methods can be used to generate promising solvents with enhanced reaction kinetics, given a reliable model of solvent effects on reaction rates. Herein, we use a surrogate model parameterised from computer experiments, more specifically, quantum-mechanical (QM) data on rate constants. The choice of solvents in which these computer experiments are performed is critical, considering the cost and difficulty of these QM calculations. We investigate the use of model-based design of experiments (MBDoE) to identify an information-rich solvent set and integrate this within a QM-CAMD framework. We find it beneficial to consider a wide range of solvents in designing the solvent set, using group contribution techniques to predict missing solvent properties. We demonstrate, via three case studies, that the use of MBDoE yields surrogate models with good statistics and leads to the identification of solvents with enhanced predicted performance with few iterations and at low computational cost.
Lee YS, Galindo A, Jackson G, et al., 2023, Enabling the direct solution of challenging computer-aided molecular and process design problems: chemical absorption of carbon dioxide, Computers and Chemical Engineering, Vol: 174, Pages: 1-24, ISSN: 0098-1354
The search for improved CO₂ capture solvents can be accelerated by deploying computer-aided molecular and process design (CAMPD) techniques to explore large molecular and process domains systematically. However, the direct solution of the integrated molecular-process design problem is very challenging as nonlinear interactions between physical properties and process performance render a large proportion of the search space infeasible. We develop a methodology that enables the direct and reliable solution of CAMPD for absorption–desorption processes, using the state-of-the-art SAFT-γ Mie group contribution approach to predict phase and chemical equilibria. We develop new feasibility tests and show them to be highly efficient at reducing the search space, integrating them in an outer-approximation algorithm. The framework is applied to design an aqueous solvent and CO₂ chemical absorption–desorption process, with 150 CAMPD instances across three case studies solved successfully. The optimal solvents are more promising than those obtained with sequential molecular design approaches.
Wehbe M, Haslam AJ, Garcia-Munoz S, et al., 2023, Thermodynamic modelling of the nature of speciation and phase behaviour of binary and ternary mixtures of formaldehyde, water and methanol, MOLECULAR PHYSICS, ISSN: 0026-8976
Ramirez-Carpio V, Galindo A, Gil-Villegas A, 2023, Modelling the solid-liquid-vapour phase behaviour of n-alkanes in a TPT-1 framework, MOLECULAR PHYSICS, ISSN: 0026-8976
Perdomo FA, Khalit SH, Graham EJ, et al., 2023, A predictive group-contribution framework for the thermodynamic modelling of CO absorption in cyclic amines, alkyl polyamines, alkanolamines and phase-change amines: New data and SAFT- Mie parameters, Fluid Phase Equilibria, Vol: 566, Pages: 1-27, ISSN: 0378-3812
A significant effort is under way to identify improved solvents for carbon dioxide (CO) capture by chemisorption. We develop a predictive framework that is applicable to aqueous solvent + CO mixtures containing cyclic amines, alkyl polyamines, and alkanolamines. A number of the mixtures studied exhibit liquid–liquid phase separation, a behaviour that has shown promise in reducing the energetic cost of CO capture. The proposed framework is based on the SAFT- Mie group-contribution (GC) approach, in which chemical reactions are described via physical association models that allow a simpler, implicit, treatment of the chemical speciation characteristic of these mixtures. We use previously optimized group interaction parameters between some amine groups and water (Perdomo et al., 2021), and develop new group interactions for the cNH, cN, NH2, NH, N, cCHNH, and cCHN groups with CO2; a set of second-order group parameters are also developed to account for proximity effects in some alkanolamines. A combination of literature data and new experimental measurements for the absorption of CO2 in aqueous cyclohexylamine systems obtained in our current work, are used to develop and test the proposed models. The SAFT- Mie GC approach is used to predict the thermodynamics of selected mixtures, including ternary phase diagrams and mixing properties relevant in the context of CO2 capture. The current work constitutes a substantial extension of the range of aqueous amine-based solvents that can be modelled and thus offers the most comprehensive thermodynamically consistent platform to date to screen novel candidate solvents for CO2 capture.
Gui L, Adjiman CS, Galindo A, et al., 2023, Uncovering the most kinetically influential reaction pathway driving the generation of HCN from oxyma/DIC adduct: a theoretical study, Industrial & Engineering Chemistry Research, Vol: 62, Pages: 874-880, ISSN: 0888-5885
The combination of ethyl (hydroxyimino)cyanoacetate (Oxyma) and diisopropylcarbodiimide (DIC) has demonstrated superior performance in amino acid activation for peptide synthesis. However, it was recently reported that Oxyma and DIC could react to generate undesired hydrogen cyanide (HCN) at 20 °C, raising safety concerns for the practical use of this activation strategy. To help minimize the risks, there is a need for a comprehensive investigation of the mechanism and kinetics of the generation of HCN. Here we show the results of the first systematic computational study of the underpinning mechanism, including comparisons with experimental data. Two pathways for the decomposition of the Oxyma/DIC adduct are derived to account for the generation of HCN and its accompanying cyclic product. These two mechanisms differ in the electrophilic carbon atom attacked by the nucleophilic sp2-nitrogen in the cyclization step and in the cyclic product generated. On the basis of computed “observed” activation energies, ΔGobs⧧, the mechanism that proceeds via the attack of the sp2-nitrogen at the oxime carbon is identified as the most kinetically favorable one, a conclusion that is supported by closer agreement between predicted and experimental 13C NMR data. These results can provide a theoretical basis to develop a design strategy for suppressing HCN generation when using Oxyma/DIC for amino acid activation.
Fayaz Torshizi M, Graham E, Adjiman C, et al., 2023, SAFT-Υ force field for the simulation of molecular fluids 9: Coarse-grained models for polyaromatic hydrocarbons describing thermodynamic, interfacial, structural, and transport properties, Journal of Molecular Liquids, Vol: 369, ISSN: 0167-7322
Coarse-grained models of polyaromatic hydrocarbons parametrized by employing the SAFT- Mie approach are presented and assessed by comparison with experimental data and all-atom models in their ability to describe liquid densities, isothermal compressibilities, thermal expansivities, viscosities, and interfacial tensions. The structural behaviour characterized by the center of mass and angular radial distribution functions are also benchmarked. The SAFT- Mie force field models are shown to deliver quantitatively accurate predictions while promising significant speedups in the computational cost of performing molecular dynamics simulations.
Perdomo FA, Jackson G, Galindo A, et al., 2023, An approach for modelling simultaneous fluid-phase and chemical-reaction equilibria in multicomponent systems via Lagrangian duality: The Reactive HELD algorithm., Computer Aided Chemical Engineering, Pages: 973-978
An approach for the calculation of simultaneous phase and chemical-reaction equilibria and stability that does not require any assumptions on the number of stable phases and is applicable to any number of reactions is presented. It is based on an extension of the dual extremum principle concept for non-reactive systems (HELD) formulated in terms of the Helmholtz energy, where additional constraints are introduced that relate molar amounts and extents of reaction. The extended R-HELD algorithm is applied to reacting mixtures such as the esterification of acetic acid and the formation of methyl tert-butyl ether.
Bernet T, Wehbe M, Febra SA, et al., 2023, Modeling the Thermodynamic Properties of Saturated Lactones in Nonideal Mixtures with the SAFT-γ Mie Approach, Journal of Chemical and Engineering Data, ISSN: 0021-9568
The prediction of the thermodynamic properties of lactones is an important challenge in the flavor, fragrance, and pharmaceutical industries. Here, we develop a predictive model of the phase behavior of binary mixtures of lactones with hydrocarbons, alcohols, ketones, esters, aromatic compounds, water, and carbon dioxide. We extend the group-parameter matrix of the statistical associating fluid theory SAFT-γ Mie group-contribution method by defining a new cyclic ester group, denoted cCOO. The group is composed of two spherical Mie segments and two association electron-donating sites of type e1 that can interact with association electron-accepting sites of type H in other molecules. The model parameters of the new cCOO group interactions (1 like interaction and 17 unlike interactions) are characterized to represent target experimental data of physical properties of pure fluids (vapor pressure, single-phase density, and vaporization enthalpy) and mixtures (vapor-liquid equilibria, liquid-liquid equilibria, solid-liquid equilibria, density, and excess enthalpy). The robustness of the model is assessed by comparing theoretical predictions with experimental data, mainly for oxolan-2-one, 5-methyloxolan-2-one, and oxepan-2-one (also referred to as γ-butyrolactone, γ-valerolactone, and ϵ-caprolactone, respectively). The calculations are found to be in very good quantitative agreement with experiments. The proposed model allows for accurate predictions of the thermodynamic properties and highly nonideal phase behavior of the systems of interest, such as azeotrope compositions. It can be used to support the development of novel molecules and manufacturing processes.
Muhieddine MH, Viswanath SK, Armstrong A, et al., 2022, Model-based solvent selection for the synthesis and crystallisation of pharmaceutical compounds, CHEMICAL ENGINEERING SCIENCE, Vol: 264, ISSN: 0009-2509
Kournopoulos S, Santos MS, Ravipati S, et al., 2022, The Contribution of the Ion-Ion and Ion-Solvent Interactions in a Molecular Thermodynamic Treatment of Electrolyte Solutions, JOURNAL OF PHYSICAL CHEMISTRY B, Vol: 126, Pages: 9821-9839, ISSN: 1520-6106
Valsecchi M, Ramadani J, Williams D, et al., 2022, Influence of Tie-Molecules and Microstructure on the Fluid Solubility in Semicrystalline Polymers., J Phys Chem B - Special Issue in Honor of Doros N. Theodorou
Predicting the absorption of gases and liquids in semicrystalline polymers is of critical importance for numerous applications; the mechanical and transport properties of these materials are highly dependent on the amount of solutes dissolved in their bulk. For most semicrystalline polymers which are in contact with an external fluid, the observed uptake of the solute is found to be lower than that predicted by treating the amorphous domains of the polymer as subcooled polymer melts at the same thermodynamic state. This observation has recently led to the hypothesis that the amorphous domains effectively behave as polymer liquids subject to an additional "constraint pressure" which reduces the equilibrium solubility in the domains. We present a new statistical mechanical model of semicrystalline polymers. The constraint pressure emerges naturally from our treatment, as a property of the interlamellar amorphous domains caused by the stretching and localization in space of the tie-molecules (polymer chains linking different lamellae). By assuming that the interlamellar domains exchange monomers reversibly with the lamellae, the model allows one to simultaneously predict the increase of constraint pressure at low temperatures and the variation of the lamellar thickness as a function of temperature─a phenomenon known as premelting. The sorption isotherms of a range of fluids in different polyethylene and polypropylene samples are determined experimentally and the data is compared with calculations of the new model using the SAFT-VR Mie EoS. In order to accurately predict the absorption close to the vapor pressure of the penetrant, we find that it is essential to include the "free", unconstrained amorphous domains in the description, resulting in a multiscale model with two adjustable parameters (the fractions of tie-molecules and free amorphous domains) that characterize the morphology of a given semicrystalline polymer sample. The trends observed fo
Graham EJ, Forte E, Burger J, et al., 2022, Multi-objective optimization of equation of state molecular parameters: SAFT-VR Mie models for water, Computers and Chemical Engineering, Vol: 167, ISSN: 0098-1354
The determination of a suitable set of molecular interaction parameters for use with an equation of state (EoS) can be viewed as a multi-objective optimization (MOO) problem, where each objective quantifies the quality of the description for a particular type of thermodynamic property. We outline a methodology for the determination of a set of Pareto-optimal interaction parameters. The Pareto front is generated efficiently using a sandwich algorithm where one solves a sequence of weighted-sum scalarized single objective optimization problems. The algorithm presented can be used for any number of objective functions, allowing for the consideration of multiple thermodynamic property types as competing objectives in the MOO. The methodology is applied to the determination of suitable parameter sets for models of water within the SAFT-VR Mie framework. Three competing property targets are considered as objective functions: saturated-liquid density, vapour pressure and isobaric heat capacity. Two different types of molecular models are considered: spherical models of water, and non-spherical model of water. We analyse the two- and three-dimensional Pareto surfaces and parameter sets obtained for different property combinations in the MOO. The proposed methodology can be used to provide a rigorous comparison between different model types. Numerous Pareto-optimal parameter sets for SAFT-VR Mie water models are documented, and we recommend two new models (one spherical model and one non-spherical model) with an appropriate compromise between the competing objectives.
Pinto JSR, Ferrando N, de Hemptinne J-C, et al., 2022, Temperature dependence and short-range electrolytic interactions within the e-PPC-SAFT framework, FLUID PHASE EQUILIBRIA, Vol: 560, ISSN: 0378-3812
Wehbe M, Haslam AJ, Jackson G, et al., 2022, Phase behaviour and pH-solubility profile prediction of aqueous buffered solutions of ibuprofen and ketoprofen, FLUID PHASE EQUILIBRIA, Vol: 560, ISSN: 0378-3812
Kournopoulos S, Haslam AJ, Jackson G, et al., 2022, Molecular theory of the static dielectric constant of dipolar fluids, The Journal of Chemical Physics, ISSN: 0021-9606
Alkhatib III, Galindo A, Vega LF, 2022, Systematic study of the effect of the co-solvent on the performance of amine-based solvents for CO<sub>2</sub> capture, SEPARATION AND PURIFICATION TECHNOLOGY, Vol: 282, ISSN: 1383-5866
Muhieddine MH, Viswanath SK, Armstrong A, et al., 2022, Multi-objective optimisation for early-stage pharmaceutical process development, Computer Aided Chemical Engineering, Pages: 2161-2166
The pharmaceutical industry is under constant pressure to deliver its products quickly and effectively while minimising development costs and pursuing green pharmaceutical manufacturing methods. Given the many considerations in process development, a model-based method that takes multiple performance metrics into account is proposed for early process development. Several key performance indicators are identified, namely environmental footprint, cost, and conversion, selectivity, and yield. We employ multi-objective optimisation to assess the trade-offs between capital cost as one objective, and selectivity or conversion as a second objective, while exploring the interdependencies between all performance indicators. The approach is applied to two multiphasic reactions, each occurring in a 6-stage cascade CSTR: the hydrogenation of 4-Isobutylacetophenone (4-IBAP) to 1-(4-Isobutylphenyl) ethanol (4-IBPE) and the carbonylation of 4-IBPE to Ibuprofen (IBP).
Jonuzaj S, Burcham CL, Galindo A, et al., 2022, Optimizing the selection of drug-polymer-water formulations for spray-dried solid dispersions in pharmaceutical manufacturing, Computer Aided Chemical Engineering, Pages: 2185-2190
In this work we present a systematic computer-aided design methodology for identifying optimal drug-polymer-water formulations with desired physical and chemical properties that are used in the spray drying of drug products. Within the proposed method, the UNIFAC model is employed to predict the solubility and miscibility of binary and ternary mixtures, whereas the Gordon-Taylor equation is used to estimate the glass transition temperature of a wide range of chemical blends. The design methodology is applied to the selection of optimal drug-polymer blends that maximize the loading of naproxen, while ensuring that stable formulations are designed. Finally, we explore the trade-offs between two competing objectives through multiobjective optimization, where the drug loading and water-content of API-polymer-water blends are maximized simultaneously. A ranked list of optimal solutions (mixtures with different chemicals and compositions) that can be used to guide experimental work is obtained by introducing integer cut inequalities into the model.
Gui L, Armstrong A, Galindo A, et al., 2022, Computer-aided solvent design for suppressing HCN generation in amino acid activation, Computer Aided Chemical Engineering, Pages: 607-612
A highly toxic compound, hydrogen cyanide (HCN), was discovered to result from the reaction between Ethyl cyano (hydroxyimino) acetate (Oxyma) and diisopropylcarbodiimide (DIC), a popular reagent combination for amino acid activation. The reaction solvent has been found to influence the amount of HCN produced so that judicious solvent choice offers a route to suppressing HCN formation. Given the safety implications and the time-demanding nature of experimental solvent selection, we employ a methodology of quantum mechanical computer-aided molecular design (QM-CAMD) to design a new reaction solvent in order to minimize the amount of HCN formed. In this work, we improve on the original QM-CAMD approach with an enhanced surrogate model to predict the reaction rate constant from several solvent properties. A set of solvents is selected for model regression using model-based design of experiments (MBDoE), where the determinant of the information matrix of the design, known as D-criterion, is maximized. The use of a model-based approach is especially beneficial here as it links the large discrete space of solvent molecules to the reduced space of solvent properties. The resulting surrogate model exhibits an improved adjusted coefficient of determination and leads to more accurate predicted rate constants than the model generated without using MBDoE. The proposed DoE-QM-CAMD algorithm reaches convergence in one iteration. In the future, the main reaction of amino acid activation will be considered to design a solvent that maintains the rate of the main reaction while minimizing HCN generation.
Muhieddine MH, Jonuzaj S, Viswanath SK, et al., 2022, Model-based solvent selection for integrated synthesis, crystallisation and isolation processes, Computer Aided Chemical Engineering, Pages: 601-606
We present a systematic process-wide solvent selection tool based on computer-aided mixture/blend design (CAMbD) (Gani, 2004) for the integrated synthesis, crystallisation and isolation of pharmaceutical compounds. The method proposed simultaneously identifies the solvent and/or anti-solvent mixture, mixture composition and process temperatures that optimise one or more key performance indicators. Additionally, the method entails comprehensive design specifications for the integrated process, such as the miscibility of the synthesis, crystallisation and wash solvents. The design approach is illustrated by identifying solvent mixtures for the synthesis, crystallisation and isolation of mefenamic acid. Furthermore, a multi-objective CAMbD problem is formulated and shows that a mefenamic acid with purity of 98.8% can be achieved without significant loss of process performance in terms of the solvent E-factor.
Lee YS, Jackson G, Galindo A, et al., 2022, Development of a Bi-Objective Optimisation Framework for Mixed-Integer Nonlinear Programming Problems and Application to Molecular Design, Computer Aided Chemical Engineering, Pages: 1225-1230
We present a novel algorithm (SDNBI) to tackle the numerical challenges associated with the solution of bi-objective mixed-integer nonlinear programming problems (BO- MINLPs), with a focus on the exploration of nonconvex regions of the Pareto front. The performance of the algorithm as measured by the accuracy of the resulting approximation of the Pareto front in the disconnected and nonconvex domain of Pareto points is assessed relative to two multi-objective optimisation (MOO) approaches: the sandwich algorithm (SD) and the modified normal boundary intersection (mNBI) method. The features of these MOO algorithms are evaluated using two published benchmark models and a molecular design problem. Initial results indicate that the new algorithm presented outperforms both the SD and the mNBI method in convex, nonconvex-continuous, combinatorial problems, both in terms of computational cost and of the overall quality of the Pareto-optimal set.
Papadopoulos AI, Perdomo FA, Tzirakis F, et al., 2021, Molecular engineering of sustainable phase-change solvents: From digital design to scaling-up for CO<sub>2</sub> capture, CHEMICAL ENGINEERING JOURNAL, Vol: 420, ISSN: 1385-8947
Ravipati S, Simoes Santos M, Economou I, et al., 2021, Monte Carlo molecular simulation study of carbon dioxide sequestration into dry and wet calcite pores containing methane, Energy and Fuels, Vol: 35, Pages: 11393-11402, ISSN: 0887-0624
We perform grand canonical Monte Carlo (GCMC) simulations to study the adsorption of carbon dioxide in a calcite slit pore. The injection of carbon dioxide is simulated by increasing the chemical potential of carbon dioxide, which allows for an investigation of adsorption under varying carbon dioxide loadings. The study is carried out for three different environments: an empty pore; a pore containing methane; and a pore containing methane with trace amounts of water. We systematically investigate the impact of the presence of these other fluids on carbon dioxide adsorption. We study the influence of carbon dioxide loading on fluid density in the pore and examine individual fluid-density profiles (in the direction normal to the fluid–solid interface). The order of fluid adsorption affinity to the surface is found to be water > carbon dioxide > methane. The interpretation of our results is informed by the examination of free-energy-averaged fluid–substrate potentials, which are computed independently from the simulations. Our observations suggest that ignoring the presence of water could lead to overestimation not only of methane availability but also of carbon dioxide storage capacity in pores, with important consequences in, for example, modeling carbon dioxide sequestration in calcite-rich reservoirs. Ultimately, it is hoped that the molecular-level insights from this study will aid the multiscale modeling of reservoir fluids in the context of enhanced oil recovery and carbon dioxide sequestration.
Febra SA, Bernet T, Mack C, et al., 2021, Extending the SAFT-gamma Mie approach to model benzoic acid, diphenylamine, and mefenamic acid: Solubility prediction and experimental measurement, Fluid Phase Equilibria, Vol: 540, Pages: 1-20, ISSN: 0378-3812
The prediction of the solubility of active pharmaceutical ingredients (APIs) is a significant challenge whichis of importance in pharmaceutical applications and solvent selection. Here, we extend the table of groupinteractions (3 like interactions, 47 unlike interactions) of the SAFT-γ Mie group-contribution equation ofstate to model the phase behaviour and solubility of mefenamic acid, a nonsteroidal anti-inflammatorydrug, in a range of solvents. In addition to mefenamic acid, we also consider its molecular synthons:benzoic acid and diphenylamine. New experimental solubility data are presented for the three moleculesin a range of solvents, and three new SAFT-γ Mie functional groups are defined (aCCOOH, aCNHaC andCH3CO) and characterised, together with their interactions with solvent groups. Literature data for thevapour pressure, single-phase density, saturation density, vapourisation enthalpy, bubble temperature,dew temperature, and bubble pressure are used to characterise the new group interactions. Solubilitydata are used to characterise the new group-group interactions only if there are no other experimentaldata available. The transferability and predictive accuracy of the new models are assessed by comparing the theoretical predictions with the experimental solubility data. Our comparison includes alcohols,ketones, and esters as families of solvents and mixed-solvent solubility predictions.
Diamanti A, Ganase Z, Grant E, et al., 2021, Mechanism, kinetics and selectivity of a Williamson ether synthesis: elucidation under different reaction conditions, REACTION CHEMISTRY & ENGINEERING, Vol: 6, Pages: 1195-+, ISSN: 2058-9883
Morgado P, Barras J, Galindo A, et al., 2021, Solubility of water in mixtures of (n-alkanes + n-perfluoroalkanes) and in n-perfluoroalkylalkanes: experimental and modeling with the SAFT-γ Mie group-contribution approach, Molecular Physics: An International Journal at the Interface Between Chemistry and Physics, Vol: 119, ISSN: 0026-8976
The solubility of water in liquid n-perfluorohexane and in an equimolar mixture of n-hexane + n-perfluorohexane is experimentally determined as a function of temperature. The solubility of water in the equimolar mixture is significantly higher than the average of the solubilities in the pure solvents suggesting, for the first time, that mixing hydrogenated and perfluorinated chains enhances the solubility of water. The solubility in the equimolar mixture of n-hexane + n-perfluorohexane is also determined theoretically with the SAFT-γ Mie group-contribution approach, allowing a direct quantitative estimate of how much the large deviations from ideality contribute to the solubility of water in the mixture. In addition, the SAFT-γ Mie approach is used to represent the solubility of water in a number of n-perfluoroalkylalkanes, covering a range of relative lengths of the hydrogenated and perfluorinated chains. The theory can be used to predict the relative extent of the solubility of water in the different solvents, in good agreement with the experimental data. This is accomplished by using a single parameter to describe the strong attractive interaction between water and the CH2CF2 group at the junction between the hydrogenated and perfluorinated segments, which is known to be responsible for the increased solubility of water in these substances.
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