On the optimal design of gas-expanded liquids based on process performance

AbstractGas-expanded liquids (GXLs) are mixed solvents composed of an organic solvent and a compressible gas, usually carbon dioxide (CO2) due to its environmental and economic advantages. The best choice of GXL, as defined by the specific organic solvent and the CO2 composition, depends strongly on the process in which the solvent is to be used. Given the large range of possible choices, there is a need to predict the impact of GXL design on process performance from economic and environmental perspectives. In this work, we present a design methodology in which limited experimental data are used to build a predictive model which allows a wider design space to be assessed. The proposed methodology for the integrated design of CO2-expanded solvent and process is applied to the Diels–Alder reaction of anthracene and 4-phenyl-1,2,4-triazoline-3,5-dione (PTAD). Three organic co-solvents are studied: acetonitrile, methanol and acetone. Given that the process cost is sensitive to the operating pressure and reactor volume, a trade-off between reaction rate constant and solubility is required in order to design an optimal process from a cost perspective. From a total cost perspective and in terms of energy consumption, it is found that designs with small amounts of CO2 or, in the case of acetone, without any CO2, offer the best performance. However, CO2 use is found to lead to a significant reduction in organic solvent inventory, up to 70 % in some cases. In this work the importance of taking multiple performance criteria, including process metrics, into account when designing GXLs is demonstrated

Advanced thermodynamic and processing modelling integration for amine scrubbing in post-combustion CO~2~ capture

The reduction in CO~2~ emissions from anthropogenic sources has become a topic of widespread interest over the past number of years. As the power generation sector is by far the largest stationary-point-source of CO~2~, being responsible for approximately 35% of total global CO~2~ emissions^1^ this question has special relevance for this industry. As the inclusion of carbon capture facilities incurs a significant energy penalty on the efficiency coal-fired power-stations, there is a strong requirement for the improvement of these systems in terms of the minimisation of operation and maintenance costs, capital costs and the maximisation of efficiency and flexibility. This last issue has relevance for start-up times and ramp-rates. Post-combustion capture methods based on the chemisorption of CO~2~ in aqueous amine solutions are among the most mature and accepted technologies for CO2 capture from power plants^2^. However, amines are complex, associating solvents requiring a sophisticated thermodynamic model, capable of modelling the hydrogen bonding interactions that occur in these systems. One such model is provided by the statistical associating fluid theory (SAFT^3^). This is a molecular approach, specifically suited to hydrogen-bonding, chain-like fluids. In this contribution we use the SAFT approach for potentials of variable range (SAFT-VR^4^) to model the thermodynamics and phase equilibria of a number of amines including ammonia and monoethanolamine. The molecules are modelled as homonuclear chains of tangentially bonded square-well segments of variable range, and a number of short-ranged off-centre attractive square-well sites are used to mediate the anisotropic effects due to association in the fluids. We also determine values of the binary parameters for mixtures and then use these parameters to predict the phase equilibria of amine+water, amine+carbon dioxide as well as water+carbon dioxide mixtures. We then consider the phase equilibria of the ternary mixtures of amine+water+carbon dioxide and finally that of quaternary mixtures of amine+water+carbon dioxide+nitrogen. A good quantitative understanding of the phase behaviour of these quaternary mixtures is essential for accurate modelling of absorption processes for carbon dioxide capture. 

1. Steeneveldt, R., Berger, B. & Torp, T.A., ChERD, 84(A9): 739-763, 2006
2. Rao, A.B.; Rubin, E.S., 2002. A Technical, Economic, and Environmental Assessment of Amine-Based CO2 Capture Technology for Power Plant Greenhouse Gas Control. Environ. Sci. Technol. 36, 4467-4475
3. Chapman, W.G., Gubbins, K.E., Jackson, G. & Radosz, M., Ind. Eng. Chem. Res., 1990. 29, 1709-1721
3. Gil-Villegas, A., Galindo, A., Whitehead, P. J., Mills, S. J. & Jackson, G., J. Chem. Phys. 106 (10), 8 March 199

Rationalising the difference in crystallisability of two sulflowers using efficient in silico methods

The molecular structures of the first and second generation sulflowers, sulflower and persulfurated coronene (PSC), are remarkably similar: carbon ring structures decorated with sulfur atoms, without any additional moiety

Hybrid QSPR models for the prediction of the free energy of solvation of organic solute/solvent pairs

© 2019 The Authors. Published by the Royal Society of Chemistry. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.1039/C8CP07562JDue 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 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−1 for the training set. The best PLS model includes six latent variables, and has an R2 value of 0.91 and a RMSE of 0.52 kcal mol−1. 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.Financial support from Eli Lilly via the Lilly Research Award Program (LRAP) and from the UK Engineering and Physical Sciences Research Council (EPSRC) of the UK via a Leadership Fellowship (EP/J003840/1) is gratefully acknowledged.Published onlin

Computer aided design of solvent blends for hybrid cooling and antisolvent crystallization of active pharmaceutical ingredients

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

Predicting the solvation of organic compounds in aqueous environments: from alkanes and alcohols to pharmaceuticals

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

Predicting enhanced absorption of light gases in polyethylene using simplified PC-SAFT and SAFT-VR

International audienceAbsorption of light gases in polyethylene (PE) is studied using two versions of the Statistical Associating Fluid Theory (SAFT): SAFT for chain molecules with attractive potentials of variable range (VR) and simplified perturbed-chain (PC) SAFT. Emphasis is placed on the light gases typically present during ethylene polymerisation in the gas-phase reactor (GPR) process. The two approaches are validated using experimental binary-mixture data for gas absorbed in PE, and predictions are made for mixtures of more components. For most cases studied both SAFT versions perform equally well. For the case of ternary mixtures of two gases with PE, it is predicted that the less-volatile of the two gases acts to enhance the absorption of the more-volatile gas, while the more-volatile gas inhibits the absorption of the less-volatile gas. This general behaviour is also predicted in mixtures containing more gases, such as typical reactor mixtures. The magnitude of the effect may vary considerably, depending on the relative proximity of the gas-mixture saturation pressure to the reactor pressure; for example it is predicted that the absorption of ethylene may be approximately doubled if diluent gases, propane or nitrogen, are partially or completely replaced by less-volatile butane or pentane for a reactor pressure similar to 2 MPa. In the case of a co-polymerisation reaction, it is predicted that increases in absorption of both co-monomers may be obtained in roughly equal proportion. Our findings cast light on the so-called co-monomer effect, in which substantial increases in the rate of ethylene polymerisation are observed in the presence of hexene co-monomer, while suggesting that the effect is more general and not restricted to co-monomer. For example, similar rate increases may be expected in the presence of, e.g., pentane instead of hexene, but without the change in the branch structure of the produced polymer that is inevitable when the amount of co-monomer is increased