A New Predictive Group-Contribution Ideal-Heat-Capacity Model and Its Influence on Second-Derivative Properties Calculated Using a Free-Energy Equation of State

Abstract

A statistical-thermodynamics-based group contribution (GC) method, commensurate with the GC methodology used in SAFT-γ Mie, is proposed to model ideal heat capacities. Special treatment of halogenated groups allows many halogenated molecules to be modeled with few parameters. Parameters for small, single-group species agree well with experimental vibrational temperatures. Parameters corresponding to groups used for larger species highlight effects such as anharmonicity and torsional modes. The proposed correlation consistently demonstrates higher accuracy than that of Joback and Reid. Ideal heat capacities are seldom used in isolation, but contribute to other properties that may be used to assess the quality of an equation of state. The importance of the ideal free energy to various second-derivative properties, as calculated using the SAFT-γ Mie equation of state, is examined. In the majority of cases, using the proposed correlation to calculate the ideal free energy results in more-accurately estimated second-derivative propertiessometimes substantially so. Further studies of the contribution of the ideal free energy are carried out revealing interesting behavior near the critical point that may relate to the Widom-Fisher and Widom lines.

Group Contribution and Machine Learning Approaches to Predict Abraham Solute Parameters, Solvation Free Energy, and Solvation Enthalpy

“…We take this unique approach because it allows one to use the experimental solute parameter data of a replaced compound and simply apply halogen corrections to get more accurate estimates for a halogenated compound. While this approach is inspired by various works, 90,91 it is primarily based on the hydrogen bond increment (HBI) method devised by Lay et al, 90 in which a radical correction is applied to a saturated compound datum to get a thermochemistry estimate for a radical compound. For the SoluteML model, the training set consists of solute SMILES as input and their corresponding solute parameters as output to the neural network.…”

Clapeyron.jl: An extensible, open-source fluid-thermodynamics toolkit

“…Clapeyron.jl also supports group-contribution (GC) models, where parameters are associated with groups which are combined to represent species. Some GC models that we currently support include SAFT-γ Mie 47 equation of state, the UNIFAC 48 activity-coefficient model and, Walker's model 49 and the Joback Method 50 for ideal-gas heat capacities. In order to form species from groups within Clapeyron.jl, one can specify the type and number of groups within a species as using a tuple containing the name of the species, and a list of key-value pairs where the key is the name of the group and the value is the group multiplicity:…”

“…Often overlooked as they have no impact on equilibrium properties, the ideal contribution to any equation of state can represent the dominant contribution to various properties, particularly second-derivative properties. 49 As such, within Clapeyron.jl, we've provided both basic and more-advanced ideal contribution models. Firstly, astute readers may have noticed that, whenever a model is created, one of the sub-types it contains is BasicIdeal.…”

“…74 , the Joback method50 and Walker's model49 . All three of these will account for the rotational and vibrational modes missing from the BasicIdeal model.…”

Continuum-scale modelling of polymer blends using the Cahn–Hilliard equation: transport and thermodynamics

“…and m i corresponds to the number of spherical segments present in the chain representing component i. a HC is likely to play a significant role in modelling polymer blends, especially considering the typically large number of segments used to represent such species. 68 It should be noted that, in the case of polymers, the spherical segments do not represent the monomers present in a chain nor, therefore, does m i represent the number of monomers (in a chain of species i). Indeed, m i need not be an integer value.…”