319 results found
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., J Phys Chem B
Developing molecular equations of state to treat electrolyte solutions is challenging due to the long-range nature of the Coulombic interactions. Seminal approaches commonly used are the mean spherical approximation (MSA) and the Debye-Hückel (DH) theory to account for ion-ion interactions and, often, the Born theory of solvation for ion-solvent interactions. We investigate the accuracy of the MSA and DH approaches using each to calculate the contribution of the ion-ion interactions to the chemical potential of NaCl in water, comparing these with newly computer-generated simulation data; the ion-ion contribution is isolated by selecting an appropriate primitive model with a Lennard-Jones force field to describe the solvent. A study of mixtures with different concentrations and ionic strengths reveals that the calculations from both MSA and DH theories are of similar accuracy, with the MSA approach resulting in marginally better agreement with the simulation data. We also demonstrate that the Born theory provides a good qualitative description of the contribution of the ion-solvent interactions; we employ an explicitly polar water model in these simulations. Quantitative agreement up to moderate salt concentrations and across the relevant range of temperature is achieved by adjusting the Born radius using simulation data of the free energy of solvation. We compute the radial and orientational distribution functions of the systems, thereby providing further insight on the differences observed between the theory and simulation. We thus provide rigorous benchmarks for use of the MSA, DH, and Born theories as perturbation approaches, which will be of value for improving existing models of electrolyte solutions, especially in the context of equations of state.
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.
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
Walker PJ, Zhao T, Haslam AJ, et al., 2022, Ab initio development of generalized Lennard-Jones (Mie) force fields for predictions of thermodynamic properties in advanced molecular-based SAFT equations of state, JOURNAL OF CHEMICAL PHYSICS, Vol: 156, ISSN: 0021-9606
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
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.
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.
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.
Papadopoulos AI, Perdomo FA, Tzirakis F, et al., 2021, Molecular engineering of sustainable phase-change solvents: From digital design to scaling-up for CO2 capture, CHEMICAL ENGINEERING JOURNAL, Vol: 420, ISSN: 1385-8947
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.
Watson OL, Jonuzaj S, McGinty J, et al., 2021, Computer aided design of solvent blends for hybrid cooling and antisolvent crystallization of active pharmaceutical ingredients, Organic Process Research and Development, Vol: 25, Pages: 1123-1142, ISSN: 1083-6160
Choosing a solvent and an antisolvent for a new crystallization process is challenging due to the sheer number of possible solvent mixtures and the impact of solvent composition and crystallization temperature on process performance. To facilitate this choice, we present a general computer aided mixture/blend design (CAMbD) formulation for the design of optimal solvent mixtures for the crystallization of pharmaceutical products. The proposed methodology enables the simultaneous identification of the optimal process temperature, solvent, antisolvent, and composition of solvent mixture. The SAFT-γ Mie group-contribution approach is used in the design of crystallization solvents; based on an equilibrium model, both the crystal yield and solvent consumption are considered. The design formulation is implemented in gPROMS and applied to the crystallization of lovastatin and ibuprofen, where a hybrid approach combining cooling and antisolvent crystallization is compared to each method alone. For lovastatin, the use of a hybrid approach leads to an increase in crystal yield compared to antisolvent crystallization or cooling crystallization. Furthermore, it is seen that using less volatile but powerful crystallization solvents at lower temperatures can lead to better performance. When considering ibuprofen, the hybrid and antisolvent crystallization techniques provide a similar performance, but the use of solvent mixtures throughout the crystallization is critical in maximizing crystal yields and minimizing solvent consumption. We show that our more general approach to rational design of solvent blends brings significant benefits for the design of crystallization processes in pharmaceutical and chemical manufacturing.
Lindeboom T, Zhao B, Jackson G, et al., 2021, On the liquid demixing of water plus elastin-like polypeptide mixtures: bimodal re-entrant phase behaviour, PHYSICAL CHEMISTRY CHEMICAL PHYSICS, Vol: 23, Pages: 5936-5944, ISSN: 1463-9076
Jackson G, Perdomo Hurtado FA, Khalit SH, et al., 2021, Description of the thermodynamics and fluid-phase behaviour of aqueous solutions of linear, branched, and cyclic amines, AIChE Journal, Vol: 67, Pages: 1-19, ISSN: 0001-1541
The SAFT‐ɣ Mie group‐contribution equation of state is used to represent the fluid‐phase behaviour of aqueous solutions of a variety of linear, branched, and cyclic amines. New group interactions are developed in order to model the mixtures of interest, including the like and unlike interactions between alkyl primary, secondary, and tertiary amine groups (NH2, NH, N), cyclic secondary and tertiary amine groups (cNH, cN), and cyclohexylamine groups (cCHNH, cCHN) with water (H2O). The group‐interaction parameters are estimated from appropriate experimental thermodynamic data for pure amines and selected mixtures. By taking advantage of the group‐contribution nature of the method, one can describe the fluid‐phase behaviour of mixtures of molecules comprising those groups over broad ranges of temperature, pressure, and composition. A number of aqueous solutions of amines are studied including linear, branched aliphatic, and cyclic amines. Liquid‐liquid equilibria (LLE) bounded by lower critical solution temperatures (LCSTs) have been reported experimentally and are reproduced here with SAFT‐ɣ Mie approach. The main feature of the approach is the ability not only to represent accurately the experimental data employed in the parameter estimation, but also to predict the vapour‐liquid, liquid‐liquid, and vapor‐liquid‐liquid equilibria, and LCSTs with the same set of parameters. Pure compound and binary phase diagrams of diverse types of amines and their aqueous solutions are assessed in order to demonstrate the main features of the thermodynamic and fluid‐phase behaviour.
Lee YS, Galindo A, Jackson G, et al., 2021, An approach for simultaneous computer-aided solvent design and process design for CO<inf>2</inf> chemical absorption processes, Computer Aided Chemical Engineering, Pages: 167-172
In the field of Computer-Aided Molecular and Process Design (CAMPD), a variety of solution methods have been developed to handle the complexities associated with the non-convexity and non-linearity of molecular structure-property and process models. However, mostalgorithms are prone to failing to generate feasible solutions when the integrated solvent-process model renders a significant portion of the search space infeasible. In this work, we propose a solution approach for the integrated design of an optimal chemical absorption process in which tailored feasibility tests are incorporated into a process optimisation problem. The solution approach allows the exploration of a design space without unnecessary difficulties by recognising infeasibilities. The effectiveness of the approach is demonstrated on an aqueous amine solvent-based CO2 capture process.
Haslam AJ, Gonzalez-Perez A, Di Lecce S, et al., 2020, Expanding the Applications of the SAFT-gamma Mie Group-Contribution Equation of State: Prediction of Thermodynamic Properties and Phase Behavior of Mixtures, JOURNAL OF CHEMICAL AND ENGINEERING DATA, Vol: 65, Pages: 5862-5890, ISSN: 0021-9568
Morgado P, Barras J, Galindo A, et al., 2020, Modeling the Fluid-Phase Equilibria of Semifluorinated Alkanes and Mixtures of (n-Alkanes plus n-Perfluoroalkanes) with the SAFT-gamma Mie Group-Contribution Approach, JOURNAL OF CHEMICAL AND ENGINEERING DATA, Vol: 65, Pages: 5909-5919, ISSN: 0021-9568
Jackson G, 2020, OBITUARY Ian R. McDonald (1938-2020), Molecular Physics: An International Journal at the Interface Between Chemistry and Physics, Vol: 118, Pages: 1-2, ISSN: 0026-8976
Kohns M, Lazarou G, Forte E, et al., 2020, Predictive models for the phase behaviour and solution properties of weak electrolytes: nitric, sulfuric and carbonic acid, Physical Chemistry Chemical Physics, Vol: 22, Pages: 15248-15269, ISSN: 1463-9076
The distribution of ionic species in electrolyte systems is important in many fields of science and engineering, ranging from the study of degradation mechanisms to the design of systems for electrochemical energy storage. Often, other phenomena closely related to the ionic speciation, such as ion pairing, clustering and hydrogen bonding, which are difficult to investigate experimentally, are also of interest. Here, we develop an accurate molecular approach, accounting for reactions as well as association and ion pairing, to deliver a predictive framework that helps validate experiment and guides future modelling of speciation phenomena of weak electrolytes. We extend the SAFT-VRE Mie equation of state [D. K. Eriksen et al., Mol. Phys., 2016, 114, 2724–2749] to study aqueous solutions of nitric, sulphuric and carbonic acid, considering complete and partially dissociated models. In order to incorporate the dissociation equilibria, correlations to experimental data for the relevant thermodynamic equilibrium constants of the dissociation reactions are taken from the literature and are imposed as a boundary condition in the calculations. The models for water, the hydronium ion, and carbon dioxide are treated as transferable and are taken from our previous work. Here we present new molecular models for nitric acid, and the nitrate, bisulfate, sulfate, and bicarbonate anions. The resulting framework is used to predict a range of phase behaviour and solution properties of the aqueous acids over wide ranges of concentration and temperature, including the degree of dissociation, as well as the activity coefficients of the ionic species, and the activity of water and osmotic coefficient, density, and vapour pressure of the solutions. The SAFT-VRE Mie models obtained in this manner provide a means of elucidating the mechanisms of association and ion pairing in the systems studied, complementing the experimental observations reported in the literature.
Bernet T, Mueller EA, Jackson G, 2020, A tensorial fundamental measure density functional theory for the description of adsorption in substrates of arbitrary three-dimensional geometry, JOURNAL OF CHEMICAL PHYSICS, Vol: 152, ISSN: 0021-9606
Blas FJ, Galindo A, Jackson G, 2020, Thermodynamics 2019 Conference-Punta Umbria, Costa de la Luz, Huelva, Spain, 26-28 June 2019, MOLECULAR PHYSICS, Vol: 118, ISSN: 0026-8976
Morgado P, Colaco B, Santos V, et al., 2020, Modelling the thermodynamic properties and fluid-phase equilibria ofn-perfluoroalkanes and their binary mixtures with the SAFT-gamma Mie group contribution equation of state, MOLECULAR PHYSICS, Vol: 118, ISSN: 0026-8976
Di Lecce S, Lazarou G, Khalit SH, et al., 2020, Correction: Modelling and prediction of the thermophysical properties of aqueous mixtures of choline geranate and geranic acid (CAGE) using SAFT-γ Mie, RSC Advances: an international journal to further the chemical sciences, Vol: 10, Pages: 19463-19465, ISSN: 2046-2069
Correction for ‘Modelling and prediction of the thermophysical properties of aqueous mixtures of choline geranate and geranic acid (CAGE) using SAFT-γ Mie’ by Silvia Di Lecce et al., RSC Adv., 2019, 9, 38017–38031. DOI: 10.1039/C9RA07057E
Lee L, Graham E, Galindo A, et al., 2020, A comparative study of multi-objective optimization methodologies for molecular and process design, Computers and Chemical Engineering, Vol: 136, ISSN: 0098-1354
The need to consider multiple objectives in molecular design, whether based on techno-economic, environmental or health and safety metrics is increasingly recognized. There is, however, limited understanding of the suitability of different multi-objective optimization algorithm for the solution of such design problems. In this work, we present a systematic comparison of the performance of five mixed-integer non-linear programming (MINLP) multi-objective optimization algorithms on the selection of computer-aided molecular design (CAMD) and computer-aided molecular and process design (CAMPD) problems. The five methods are designed to address the discrete and nonlinear nature of the problem, with the aim of generating an accurate approximation of the Pareto front. They include: a weighted sum approach without global search phases (SWS), a weighted sum approach with simulated annealing (SA), a weighted sum approach with multi level single linkage (MLSL), the sandwich algorithm with MLSL and the non dominated sorting genetic algorithm-II (NSGA-II). The algorithms are compared systematically in two steps. The effectiveness of the global search methods is evaluated with SWS, WSSA and WSML. WSML is found to be most effective and a comparative analysis of WSML, SDML and NSGA-II is then undertaken. As a test set of these optimization techniques, two of CAMD and one CAMPD problems of varying dimensionality are formulated as case studies. The results show that the sandwich algorithm with MLSL provides the most efficient generation of a diverse set of Pareto points, leading to the construction of an approximate Pareto front close to exact Pareto front.
Papadopoulos A, Shavalieva G, Papadokonstantakis S, et al., 2020, An approach for simultaneous computer-aided molecular design with holistic sustainability assessment: Application to phase-change CO2 capture solvents, COMPUTERS & CHEMICAL ENGINEERING, Vol: 135, ISSN: 0098-1354
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