213 results found
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.
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
Di Lecce S, Lazarou G, Khalit SH, et al., 2020, Modelling and prediction of the thermophysical properties of aqueous mixtures of choline geranate and geranic acid (CAGE) using SAFT-gamma Mie (vol 9, pg 38017, 2019), RSC ADVANCES, Vol: 10, Pages: 19463-19465
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
Bowskill DHH, Tropp UE, Gopinath S, et al., 2020, Beyond a heuristic analysis: integration of process and working-fluid design for organic Rankine cycles, MOLECULAR SYSTEMS DESIGN & ENGINEERING, Vol: 5, Pages: 493-510, ISSN: 2058-9689
Galindo A, Trusler JPM, 2020, Preface, Fluid Phase Equilibria, Vol: 503, ISSN: 0378-3812
Ravipati S, Galindo A, Jackson G, et al., 2019, An investigation of free-energy-averaged (coarse-grained) potentials for fluid adsorption on heterogeneous solid surfaces, PHYSICAL CHEMISTRY CHEMICAL PHYSICS, Vol: 21, Pages: 25558-25568, ISSN: 1463-9076
Hall CK, Kofke DA, Galindo A, et al., 2019, Peter Cummings - a pillar in the field of statistical mechanics and molecular simulation FOREWORD, Molecular Physics: An International Journal at the Interface Between Chemistry and Physics, Vol: 117, Pages: 3479-3483, ISSN: 0026-8976
Di Lecce S, Galindo A, Khalit SH, et al., 2019, Modelling and prediction of the thermophysical properties of aqueous mixtures of Choline Geranate and Geranic acid (CAGE) using SAFT-g Mie, RSC Advances: an international journal to further the chemical sciences, Vol: 9, Pages: 38017-38031, ISSN: 2046-2069
Deep eutectic solvents and room temperature ionic liquids are increasingly recognised as appro-priate materials for use as active pharmaceutical ingredients and formulation additives. Aque-ous mixtures of choline and geranate (CAGE), in particular, have been shown to offer promisingbiomedical properties but the understanding of the thermophysical behaviour of these mixturesremains limited. Here, we develop interaction potentials for use in the SAFT–γgroup–contributionapproach, to study the thermodynamic properties and phase behaviour of aqueous mixtures ofcholine geranate and geranic acid. The determination of the interaction parameters betweenchemical functional groups is carried out in a successive fashion, characterising each group basedon those previously developed. The parameters of the groups relevant to geranic acid are esti-mated using experimental phase–equilibrium data such as vapour pressure and saturated–liquiddensity of simple pure components (n–alkenes, branched alkenes and carboxylic acids) and thephase equilibrium data of mixtures (aqueous solutions of branched alkenes and of carboxylicacids). Geranate is represented by further incorporating the anionic carboxylate group, COO−,which is characterised using aqueous solution data of sodium carboxylate salts, assuming fulldissociation of the salt in water. Choline is described by incorporating the cationic quaternaryammonium group, N+, using data on choline choride solutions. The osmotic pressure of aque-ous mixtures of CAGE at several concentrations is predicted and compared to experimental dataobtained as part of our work to assess the accuracy of the modelling platform. The SAFT–γMieapproach is shown to be predictive, providing a good description of the measured data for a widerange of mixtures and properties. Furthermore, the new group interaction parameters neededto represent CAGE extend the set of functional group
Febra SA, Aasen A, Adjiman CS, et al., 2019, Intramolecular bonding in a statistical associating fluid theory of ring aggregates, MOLECULAR PHYSICS, ISSN: 0026-8976
Borhani T, Garcia-Munoz S, Luciani C, et al., 2019, Hybrid QSPR models for the prediction of the free energy of solvation of organic solute/solvent pairs, Physical Chemistry Chemical Physics, Vol: 21, Pages: 13706-13720, ISSN: 1463-9076
Due to the importance of the Gibbs free energy of solvation in understanding many physicochemical phenomena, including lipophilicity, phase equilibria and liquid-phase reaction equilibrium and kinetics, there is a need for predictive models that can be applied across large sets of solvents and solutes. In this paper, we propose two quantitative structure property relationships (QSPRs) to predict the Gibbs free energy of solvation, developed using partial least squares (PLS) and multivariate linear regression (MLR) methods for 295 solutes in 210 solvents with total number of data points of 1777. Unlike other QSPR models, the proposed models are not restricted to a specific solvent or solute. Furthermore, while most QSPR models include either experimental or quantum mechanical descriptors, the proposed models combine both, using experimental descriptors to represent the solvent and quantum mechanical descriptors to represent the solute. Up to twelve experimental descriptors and nine quantum mechanical descriptors are considered in the proposed models. Extensive internal and external validation is undertaken to assess model accuracy s in predicting the Gibbs free energy of solvation for a large number of solute/solvent pairs. The best MLR model, which includes three solute descriptors and two solvent properties, yields a coefficient of determination (R2) of 0.88 and a root mean squared error (RMSE) of 0.59 kcal/mol for the training set. The best PLS model includes six latent variables, and has a R2 value of 0.91 and a RMSE of 0.52 kcal/mol. The proposed models are compared to selected results based on continuum solvation quantum chemistry calculations. They enable the fast prediction of the Gibbs free energy of solvation of a wide range of solutes in different solvents.
Lee YS, Graham E, Jackson G, et al., 2019, A comparison of the performance of multi-objective optimization methodologies for solvent design, Editors: Kiss, Zondervan, Lakerveld, Ozkan, Publisher: ELSEVIER SCIENCE BV, Pages: 37-42, ISBN: 978-0-12-819939-8
Kazepidis P, Papadopoulos AI, Seferlis P, et al., 2019, Optimal design of post combustion CO2 capture processes based on phase-change solvents, Editors: Kiss, Zondervan, Lakerveld, Ozkan, Publisher: ELSEVIER SCIENCE BV, Pages: 463-468, ISBN: 978-0-12-819939-8
Watson OL, Galindo A, Jackson G, et al., 2019, Computer-aided Design of Solvent Blends for the Cooling and Anti-solvent Crystallisation of Ibuprofen, Editors: Kiss, Zondervan, Lakerveld, Ozkan, Publisher: ELSEVIER SCIENCE BV, Pages: 949-954, ISBN: 978-0-12-819939-8
Galindo A, Rahman S, Lobanova O, et al., 2018, SAFT‑γ force field for the simulation of molecular fluids. 5. Hetero Group coarse-grained models of linear alkanes and the importance of intramolecular interactions, Journal of Physical Chemistry B, Vol: 122, Pages: 9161-9177, ISSN: 1520-5207
The SAFT-γ Mie group-contribution equation of state [Papaioannou J. Chem. Phys. 2014, 140, 054107] is used to develop a transferable coarse-grained (CG) force-field suitable for the molecular simulation of linear alkanes. A heterogroup model is fashioned at the resolution of three carbon atoms per bead in which different Mie (generalized Lennard-Jones) interactions are used to characterize the terminal (CH3–CH2–CH2−) and middle (−CH2–CH2–CH2−) beads. The force field is developed by combining the SAFT-γ CG top-down approach [Avendaño J. Phys. Chem. B 2011, 115, 11154], using experimental phase-equilibrium data for n-alkanes ranging from n-nonane to n-pentadecane to parametrize the intermolecular (nonbonded) bead–bead interactions, with a bottom-up approach relying on simulations based on the higher resolution TraPPE united-atom (UA) model [Martin; , Siepmann J. Phys. Chem. B 1998, 102, 2569] to establish the intramolecular (bonded) interactions. The transferability of the SAFT-γ CG model is assessed from a detailed examination of the properties of linear alkanes ranging from n-hexane (n-C6H14) to n-octadecane (n-C18H38), including an additional evaluation of the reliability of the description for longer chains such as n-hexacontane (n-C60H122) and a prototypical linear polyethylene of moderate molecular weight (n-C900H1802). A variety of structural, thermodynamic, and transport properties are examined, including the pair distribution functions, vapor–liquid equilibria, interfacial tension, viscosity, and diffusivity. Particular focus is placed on the impact of incorporating intramolecular interactions on the accuracy, transferability, and representability of the CG model. The novel SAFT-γ CG force field is shown to provide a reliable description of the thermophysical properties of the n-alkanes, in most cases at a level comparable to the that obtained with higher resolution models.
Ravipati S, Aymard B, Kalliadasis S, et al., 2018, On the equilibrium contact angle of sessile liquid drops from molecular dynamics, Journal of Chemical Physics, Vol: 148, ISSN: 0021-9606
We present a new methodology to estimate the contact angles of sessile drops from molec-ular simulations, by using the Gaussian convolution method of Willard and Chandler (J.Phys. Chem. B, Vol. 114, 1954-1958, 2010) to calculate the coarse-grained density fromatomic coordinates. The iso-density contour with average coarse-grained density valueequal to half of the bulk liquid density is identified as the average liquid-vapor (LV) inter-face. Angles between the unit normal vectors to the average LV interface and unit normalvector to the solid surface, as a function of the distance normal to the solid surface, arecalculated. The cosines of these angles are extrapolated to the three-phase contact line toestimate the sessile drop contact angle. The proposed methodology, which is relativelyeasy to implement, is systematically applied to three systems: (i) a Lennard-Jones (LJ)drop on a featureless LJ9-3surface; (ii) an SPC/E water drop on a featureless LJ9-3sur-face; and (iii) an SPC/E water drop on a graphite surface. The sessile drop contact anglesestimated with our methodology for the first two systems, are shown to be in good agree-ment with the angles predicted from Young’s equation. The interfacial tensions requiredfor this equation are computed by employing the test-area perturbation method for the cor-responding planar interfaces. Our findings suggest that the widely adopted spherical-capapproximation should be used with caution, as it could take a long time for a sessile dropto relax to a spherical shape, of the order of100ns, especially for water molecules initiatedin a lattice configuration on a solid surface. But even though a water drop can take a longtime to reach the spherical shape, we find that the contact angle is well established muchfaster and the drop evolves towards the spherical shape following a constant-contact-anglerelaxation dynamics. Making use of this observation, our methodology allows a good es-timation of the sessile drop
Carbon capture and storage (CCS) is broadly recognised as having the potential to play a key role in meeting climate change targets, delivering low carbon heat and power, decarbonising industry and, more recently, its ability to facilitate the net removal of CO2 from the atmosphere. However, despite this broad consensus and its technical maturity, CCS has not yet been deployed on a scale commensurate with the ambitions articulated a decade ago. Thus, in this paper we review the current state-of-the-art of CO2 capture, transport, utilisation and storage from a multi-scale perspective, moving from the global to molecular scales. In light of the COP21 commitments to limit warming to less than 2 °C, we extend the remit of this study to include the key negative emissions technologies (NETs) of bioenergy with CCS (BECCS), and direct air capture (DAC). Cognisant of the non-technical barriers to deploying CCS, we reflect on recent experience from the UK's CCS commercialisation programme and consider the commercial and political barriers to the large-scale deployment of CCS. In all areas, we focus on identifying and clearly articulating the key research challenges that could usefully be addressed in the coming decade.
Grant E, Pan Y, Richardson J, et al., 2018, Multi-Objective Computer-Aided Solvent Design for Selectivity and Rate in Reactions, Computer Aided Chemical Engineering, Pages: 2437-2442
© 2018 Elsevier B.V. A hybrid empirical computer-aided methodology to design the solvent for a reaction, incorporating both selectivity and rate, is presented. A small initial set of diverse solvents is used, for which experimental, in situ kinetic data are obtained. A surrogate model is utilized to correlate the reaction kinetics with solvent properties and a computer-aided molecular design (CAMD) multi-objective optimization problem is then formulated to identify solvents with improved performance compared with the initial solvent set. This methodology is applied to an SNAr reaction of 2,4-difluoroacetophenone with pyrrolidine, which demonstrates an interesting effect of solvent on both the selectivity of the ortho-:para-substitution ratio and the overall rate of the reaction. A set of Pareto optimal solutions is identified, highlighting the trade-off between reaction rate and selectivity.
Jackson G, dufal S, Lafitte T, et al., 2018, Corrigendum: The A in SAFT: developing the contribution of association to the Helmholtz free energy within a Wertheim TPT1 treatment of generic Mie fluids, Molecular Physics, Vol: 116, Pages: 283-285, ISSN: 0026-8976
Zhao B, Lindeboom T, Benner S, et al., 2017, Predicting the Fluid-Phase Behavior of Aqueous Solutions of ELP (VPGVG) Sequences Using SAFT-VR., Langmuir, Vol: 33, Pages: 11733-11745, ISSN: 0743-7463
The statistical associating fluid theory for potentials of variable range (SAFT-VR) is used to predict the fluid phase behavior of elastin-like polypeptide (ELP) sequences in aqueous solution with special focus on the loci of lower critical solution temperatures (LCSTs). A SAFT-VR model for these solutions is developed following a coarse-graining approach combining information from atomistic simulations and from previous SAFT models for previously reported relevant systems. Constant-pressure temperature-composition phase diagrams are determined for solutions of (VPGVG)n sequences + water with n = 1 to 300. The SAFT-VR equation of state lends itself to the straightforward calculation of phase boundaries so that complete fluid-phase equilibria can be calculated efficiently. A broad range of thermodynamic conditions of temperature and pressure are considered, and regions of vapor-liquid and liquid-liquid coexistence, including LCSTs, are found. The calculated phase boundaries at low concentrations match those measured experimentally. The temperature-composition phase diagrams of the aqueous ELP solutions at low pressure (0.1 MPa) are similar to those of types V and VI phase behavior in the classification of Scott and van Konynenburg. An analysis of the high-pressure phase behavior confirms, however, that a closed-loop liquid-liquid immiscibility region, separate from the gas-liquid envelope, is present for aqueous solutions of (VPGVG)30; such a phase diagram is typical of type VI phase behavior. ELPs with shorter lengths exhibit both liquid-liquid and gas-liquid regions, both of which become less extensive as the chain length of the ELP is decreased. The strength of the hydrogen-bonding interaction is also found to affect the phase diagram of the (VPGVG)30 system in that the liquid-liquid and gas-liquid regions expand as the hydrogen-bonding strength is decreased and shrink as it is increased. The LCSTs of the mixtures are seen to decrease as the ELP chain length is in
Hutacharoen P, Dufal S, Papaioannou V, et al., 2017, Predicting the solvation of organic compounds in aqueous environments: from alkanes and alcohols to pharmaceuticals, Industrial and Engineering Chemistry Research, Vol: 56, Pages: 10856-0876, ISSN: 0888-5885
The development of accurate models to predict the solvation, solubility, and partitioning of nonpolar and amphiphilic compounds in aqueous environments remains an important challenge. We develop state-of-the-art group-interaction models that deliver an accurate description of the thermodynamic properties of alkanes and alcohols in aqueous solution. The group-contribution formulation of the statistical associating fluid theory based on potentials with a variable Mie form (SAFT-γ Mie) is shown to provide accurate predictions of the phase equilibria, including liquid–liquid equilibria, solubility, free energies of solvation, and other infinite-dilution properties. The transferability of the model is further exemplified with predictions of octanol–water partitioning and solubility for a range of organic and pharmaceutically relevant compounds. Our SAFT-γ Mie platform is reliable for the prediction of challenging properties such as mutual solubilities of water and organic compounds which can span over 10 orders of magnitude, while remaining generic in its applicability to a wide range of compounds and thermodynamic conditions. Our work sheds light on contradictory findings related to alkane–water solubility data and the suitability of models that do not account explicitly for polarity.
Diamanti A, Adjiman CS, Piccione PM, et al., 2016, Development of Predictive Models of the Kinetics of a Hydrogen Abstraction Reaction Combining Quantum-Mechanical Calculations and Experimental Data, Industrial & Engineering Chemistry Research, Vol: 56, Pages: 815-831, ISSN: 0888-5885
The importance of developing accurate modeling tools for the prediction of reaction kinetics is well recognized. In this work, a thorough investigation of the suitability of quantum mechanical (QM) calculations to predict the effect of temperature on the rate constant of the reaction between ethane and the hydroxyl radical is presented. Further, hybrid models that combine a limited number of QM calculations and experimental data are developed in order to increase their reliability. The activation energy barrier of the reaction is computed using various computational methods, such as B3LYP, M05-2X, M06-2X, MP2 and PMP2, CBS-QB3, and W1BD, with a selection of basis sets. A broad range of values is obtained, including negative barriers for all of the calculations with B3LYP. The rate constants are also obtained for each method, using conventional transition state theory, and are compared with available experimental values at 298 K. The best agreement is achieved with the M05-2X functional with cc-pV5Z basis set. Rate constants calculated at this level of theory are also found to be in good agreement with experimental values at different temperatures, resulting in a mean absolute error of the logarithm (MAEln) of the calculated values of 0.213 over a temperature range of 200–1250 K and 0.108 over a temperature range of 300–499 K. Tunnelling and vibrational anharmonicities are identified as important sources of discrepancies at low and high temperatures, respectively. Hybrid models are proposed and found to provide good correlated rate-constant values and to be competitive with conventional kinetic models, i.e., the Arrhenius and the three-parameter Arrhenius models. The combination of QM-calculated and experimental data sources proves particularly beneficial when fitting to scarce experimental data. The parameters of the model built on the hybrid strategy have a significantly reduced uncertainty (reflected in the much narrower 95% confidence intervals) compa
Eriksen DK, Lazarou G, Galindo A, et al., 2016, Development of intermolecular potential models for electrolyte solutions using an electrolyte SAFT-VR Mie equation of state, Molecular Physics, Vol: 114, Pages: 2724-2749, ISSN: 1362-3028
We present a theoretical framework and parameterisation of intermolecular potentials for aqueous electrolyte solutions using the statistical associating fluid theory based on the Mie interaction potential (SAFT-VR Mie), coupled with the primitive, non-restricted mean-spherical approximation (MSA) for electrolytes. In common with other SAFT approaches, water is modelled as a spherical molecule with four off-centre association sites to represent the hydrogen-bonding interactions; the repulsive and dispersive interactions between the molecular cores are represented with a potential of the Mie (generalised Lennard-Jones) form. The ionic species are modelled as fully dissociated, and each ion is treated as spherical: Coulombic ion–ion interactions are included at the centre of a Mie core; the ion–water interactions are also modelled with a Mie potential without an explicit treatment of ion–dipole interaction. A Born contribution to the Helmholtz free energy of the system is included to account for the process of charging the ions in the aqueous dielectric medium. The parameterisation of the ion potential models is simplified by representing the ion–ion dispersive interaction energies with a modified version of the London theory for the unlike attractions. By combining the Shannon estimates of the size of the ionic species with the Born cavity size reported by Rashin and Honig, the parameterisation of the model is reduced to the determination of a single ion–solvent attractive interaction parameter. The resulting SAFT-VRE Mie parameter sets allow one to accurately reproduce the densities, vapour pressures, and osmotic coefficients for a broad variety of aqueous electrolyte solutions; the activity coefficients of the ions, which are not used in the parameterisation of the models, are also found to be in good agreement with the experimental data. The models are shown to be reliable beyond the molality range considered during parameter estimatio
Brand CV, Graham E, Rodriguez J, et al., 2016, On the use of molecular-based thermodynamic models to assess theperformance of solvents for CO₂capture processes:monoethanolamine solutions, Faraday Discussions, Vol: 192, Pages: 337-390, ISSN: 1364-5498
Predictive models play an important role in the design of post-combustion processes for the capture of carbon dioxide (CO2) emitted from power plants. A rate-based absorber model is presented to investigate the reactive capture of CO2 using aqueous monoethanolamine (MEA) as a solvent, integrating a predictive molecular-based equation of state: SAFT-VR SW (Statistical Associating Fluid Theory-Variable Range, Square Well). A distinctive physical approach is adopted to model the chemical equilibria inherent in the process. This eliminates the need to consider reaction products explicitly and greatly reduces the amount of experimental data required to model the absorber compared to the more commonly employed chemical approaches. The predictive capabilities of the absorber model are analyzed for profiles from 10 pilot plant runs by considering two scenarios: (i) no pilot-plant data are used in the model development; (ii) only a limited set of pilot-plant data are used. Within the first scenario, the mass fraction of CO2 in the clean gas is underestimated in all but one of the cases, indicating that a best-case performance of the solvent can be obtained with this predictive approach. Within the second scenario a single parameter is estimated based on data from a single pilot plant run to correct for the dramatic changes in the diffusivity of CO2 in the reactive solvent. This parameter is found to be transferable for a broad range of operating conditions. A sensitivity analysis is then conducted, and the liquid viscosity and diffusivity are found to be key properties for the prediction of the composition profiles. The temperature and composition profiles are sensitive to thermodynamic properties that correspond to major sources of heat generation or dissipation. The proposed modelling framework can be used as an early assessment of solvents to aid in narrowing the search space, and can help in determining target solvents for experiments and more detailed modelling.
Struebing H, Obermeier S, Siougkrou E, et al., 2016, A QM-CAMD approach to solvent design for optimal reaction rates, Chemical Engineering Science, Vol: 159, Pages: 69-83, ISSN: 1873-4405
The choice of solvent in which to carry out liquid-phase organic reactions often has a largeimpact on reaction rates and selectivity and is thus a key decision in process design. A systematicmethodology for solvent design that does not require any experimental data on the effect ofsolvents on reaction kinetics is presented. It combines quantum mechanical computations forthe reaction rate constant in various solvents with a computer-aided molecular design (CAMD)formulation. A surrogate model is used to derive an integrated design formulation that combineskinetics and other considerations such as phase equilibria, as predicted by group contributionmethods. The derivation of the mixed-integer nonlinear formulation is presented step-by-step.In the application of the methodology to a classic SN2 reaction, the Menschutkin reaction,the reaction rate is used as the key performance objective. The results highlight the tradeoffsbetween different chemical and physical properties such as reaction rate constant, solventdensity and solid reactant solubility and lead to the identification of several promising solventsto enhance reaction performance.
Papadopoulos AI, Badr S, Chremos A, et al., 2016, Computer-aided molecular design and selection of CO2 capture solvents based on thermodynamics, reactivity and sustainability, Molecular Systems Design & Engineering, Vol: 1, Pages: 313-334, ISSN: 2058-9689
The identification of improved carbon dioxide (CO2) capture solvents remains a challenge due to the vast number of potentially-suitable molecules. We propose an optimization-based computer-aided molecular design (CAMD) method to identify and select, from hundreds of thousands of possibilities, a few solvents of optimum performance for CO2 chemisorption processes, as measured by a comprehensive set of criteria. The first stage of the approach involves a fast screening stage where solvent structures are evaluated based on the simultaneous consideration of important pure component properties reflecting thermodynamic, kinetic, and sustainability behaviour. The impact of model uncertainty is considered through a systematic method that employs multiple models for the prediction of performance indices. In the second stage, high-performance solvents are further selected and evaluated using a more detailed thermodynamic model, i.e. the group-contribution statistical associating fluid theory for square well potentials (SAFT-γ SW), to predict accurately the highly non-ideal chemical and phase equilibrium of the solvent–water–CO2 mixtures. The proposed CAMD method is applied to the design of novel molecular structures and to the screening of a data set of commercially available amines. New molecular structures and commercially-available compounds that have received little attention as CO2 capture solvents are successfully identified and assessed using the proposed approach. We recommend that these solvents should be given priority in experimental studies to identify new compounds.
Gopinath S, Jackson G, Galindo A, et al., 2016, Outer approximation algorithm with physical domain reduction for computer-aided molecular and separation process design, AICHE Journal, Vol: 62, Pages: 3484-3504, ISSN: 0001-1541
Integrated approaches to the design of separation systems based on computer-aided molecular and process design (CAMPD) can yield an optimal solvent structure and process conditions. The underlying design problem, however, is a challenging mixed integer nonlinear problem, prone to convergence failure as a result of the strong and nonlinear interactions between solvent and process. To facilitate the solution of this problem, a modified outer-approximation (OA) algorithm is proposed. Tests that remove infeasible regions from both the process and molecular domains are embedded within the OA framework. Four tests are developed to remove subdomains where constraints on phase behavior that are implicit in process models or explicit process (design) constraints are violated. The algorithm is applied to three case studies relating to the separation of methane and carbon dioxide at high pressure. The process model is highly nonlinear, and includes mass and energy balances as well as phase equilibrium relations and physical property models based on a group-contribution version of the statistical associating fluid theory (SAFT-γ Mie) and on the GC+ group contribution method for some pure component properties. A fully automated implementation of the proposed approach is found to converge successfully to a local solution in 30 problem instances. The results highlight the extent to which optimal solvent and process conditions are interrelated and dependent on process specifications and constraints. The robustness of the CAMPD algorithm makes it possible to adopt higher-fidelity nonlinear models in molecular and process design.
Gopinath S, Galindo A, Jackson G, et al., 2016, A feasibility-based algorithm for Computer Aided Molecular and Process Design of solvent-based separation systems, 26th European Symposium on Computer Aided Process Engineering (ESCAPE 26), Publisher: Elsevier, Pages: 73-78, ISSN: 1570-7946
Computer-aided molecular and product design (CAMPD) can in principle be used to find simultaneouslythe optimal conditions in separation processes and the structure of the optimal solvents.In many cases, however, the solution of CAMPD problems is challenging. In this paper, we proposea solution approach for the CAMPD of solvent-based separation systems in which implicitconstraints on phase behaviour in process models are used to test the feasibility of the processand solvent domains. The tests not only eliminate infeasible molecules from the search space butalso infeasible combinations of solvent molecules and process conditions. The tests also providebounds for the optimization of the process model (primal problem) for each solvent, facilitatingnumerical solution. This is demonstrated on a prototypical natural gas purification process.
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