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Formaldehyde is a highly reactive chemical that is usually sold and processed in the form of aqueous solutions, with methanol added for stability. In these solutions, formaldehyde reacts with the solvents to form a variety of reaction products, including oligomers. These chemical reactions can occur in the liquid and vapour phases and have a significant influence on the properties of formaldehyde-containing solutions. Of particular interest to industrial applications is the prediction of the vapour–liquid equilibria (VLE) in formaldehyde solutions, considering the chemical reactions. We use the SAFT-γ Mie group-contribution (GC) equation of state to obtain the fluid-phase behaviour of binary and ternary mixtures of formaldehyde with water and methanol. The oligomerisation reactions taking place in aqueous and methanolic solutions of formaldehyde are modelled implicitly using a physical approach, which is possible within the SAFT-γ Mie framework by adding association (reactive) sites that mediate the formation of the reaction products. Using this approach, the nature of the chemical speciation in formaldehyde + water, formaldehyde + methanol and formaldehyde + water + methanol mixtures is studied. A new group, CH 2 O, characterising formaldehyde within the SAFT-γ Mie GC approach, is developed. Experimental data for the VLE in binary mixtures of formaldehyde + water and formaldehyde + methanol are used to obtain the optimal unlike interaction parameters between the corresponding SAFT-γ Mie groups. The newly developed parameters are used to predict the VLE of ternary formaldehyde + water + methanol mixtures for a wide range of temperatures and pressures, with excellent agreement to experimental data. Additionally, the SAFT-γ Mie approach is shown to provide accurate predictions of the distribution of reaction species (oligomers) in binary and ternary mixtures containing formaldehyde. [ABSTRACT FROM AUTHOR]

Salt formation is commonly used to increase the solubility of ionisable active pharmaceutical ingredients (APIs) and is monitored via a pH-solubility profile of the API and its salt. Due to the extremely low solubilities of many APIs in water, experiments are difficult to perform, and reliable predictive tools can be especially useful in this context. Here, we use the SAFT- γ Mie group-contribution equation of state to predict the phase diagrams and the pH-dependent solubility of two acidic APIs: ibuprofen and ketoprofen. We consider ibuprofen and ketoprofen in basic buffer solutions of NaOH, KOH, LiOH, RbOH, Ca (OH) 2 , Mg (OH) 2 , n -hexylamine, n -octylamine, benzylamine and tert -butylamine, and in acidic buffer solutions of HCl and acetate. A predictive approach is developed in which the unlike interactions involving charged groups are either taken from previous work, calculated using combining rules or, in the case of groups originating from organic groups (e.g., COO −), taken to be the same as the equivalent interaction involving the neutral (uncharged) group. A new group, NH 3 + , is characterised for the case of amine buffers and salts. Equilibrium constants for the dissociation of the APIs and the formation of salts (p K a and K sp , A ν A B ν B values) are also incorporated in the model using experimental values from literature. Predictions of the complete phase diagrams of the APIs in water are presented, including the vapour–liquid, liquid–liquid (oiling out), and solid–liquid (solubility) equilibria. The SAFT- γ Mie approach is shown to provide accurate predictions of the solid–liquid solubility of the compounds, as well as of the presence of liquid–liquid separation. Furthermore, the pH-solubility profiles of the APIs at T = 298.15 K and 310.15 K for the range of buffers and salts considered are predicted in good agreement with the available experimental data. [ABSTRACT FROM AUTHOR]

A mixed-integer non-linear programming optimisation framework is formulated and developed that combines a molecular-based, group-contribution equation of state, SAFT- γ Mie, with a thermodynamic description of an organic Rankine cycle (ORC) power system. In this framework, a set of working fluids is described by its constituent functional groups ( e.g. , since we are focussing here on hydrocarbons: CH 3 , CH 2 , etc. ), and integer optimisation variables are introduced in the description the working-fluid structure. Molecular feasibility constraints are then defined to ensure all feasible working-fluid candidates can be found. This optimisation framework facilitates combining the computer-aided molecular design of the working fluid with the power-system optimisation into a single framework, thus removing subjective and pre-emptive screening criteria, and simultaneously moving towards the next generation of tailored working fluids and optimised systems for waste-heat recovery applications. SAFT- γ Mie has not been previously employed in such a framework. The optimisation framework, which is based here on hydrocarbon functional groups, is first validated against an alternative formulation that uses (pseudo-experimental) thermodynamic property predictions from REFPROP, and against an optimisation study taken from the literature. The framework is then applied to three industrial waste-heat recovery applications. It is found that simple molecules, such as propane and propene, are the optimal ORC working fluids for a low-grade (150 °C) heat source, whilst molecules with increasing molecular complexity are favoured at higher temperatures. Specifically, 2-alkenes emerge as the optimal working fluids for medium- and higher-grade heat-sources in the 250–350 °C temperature range. Ultimately, the results demonstrate the potential of this framework to drive the search for the next generation of ORC systems, and to provide meaningful insights into identifying the working fluids that represent the optimal choices for targeted applications. Finally, the effects of the working-fluid structure on the expander and pump are investigated, and the suitability of group-contribution methods for evaluating the transport properties of hydrocarbon working-fluids are considered, in the context of performing complete thermoeconomic evaluations of these systems. [ABSTRACT FROM AUTHOR]