Group contribution modeling selectivity

The subunits defined in the model are listed in Table I. Also shown are the group molar volume and the group contribution to the COj permeability and the CO2/CH4 permselectivity the best fit solution to the matrix of linear equations. The gas permeability of each polymer in the dataset was calculated firom the resultant subunit permeability indicated in Table I and the normalized structural equation for each polymer. The CO2 and CH4 permeability (in Barrers) predicted by the group contribution model is compared to experimental values in Figure 1. An excellent correlation is evident for both gases. The correlation between model predicted and experimental CO2/CH4 selectivity is shown in Figure 2. 

A new group contribution model has been developed which accurately describes the CO2 and CH4 permeability and selectivity of 87 polymers. Unlike previous group contribution models, it is not based on fiactional free volume estimated from density measurements but rather, in this approach, the volume fractions of the structural elements comprising the polymer serve as the basis for correlation. The volume of these groups were calculated from commercially available computer software. This new model quantifies a variety of structure-property relationships which have been reported in the literature. 

The relative retention a=k/ki is a measure of the separation selectivity for two compounds i and j with retention factors ki and kj, respectively, differing by one repeat structural unit, An=l.p in Equation 5.16 is the end-group contribution to the retention factor. The conventional theory describes adequately the retention of oligomers and lower homopolymers and copolymers up to the molar masses 10,000-30,000Da for higher polymers the accuracy of the determination of retention model parameters is too low [95]. 

Table 3.1 can be used to classify the solvents. These properties can lead to understanding of various physical phenomenon (Chiou and Kile, 1994). They can be used in selecting potential solvent alternatives. This is carried out, for example, through a group contribution molecular design of solvents (MOLDES) approach in molecular modeling (Pretel et al., 1994). 

The required activity coefficients can either be calculated (predicted) with the help of thermodynamic models (group contribution methods) or obtained from factual data banks. The procedure for the selection of selective solvents for extractive distillation processes is given in refs. 4 and 5. The capacity C, of extractants can be estimated using activity coefficients at infinite dilution. 

In the exploratory phases of product and process research and development, generally little or limited data are available for model parameterization. However, chemists and engineers need to evaluate a multitude of possible molecular or process variations. Rather than high accuracy, successful evaluation depends on the ability to discard the least viable options and select better options for further detailed studies. Estimation methods that give reliable results for new or unknown species are required. The well-known group-contribution methods, like UNIFAC, have demonstrated their value in cases where the molecules can be decomposed to functional groups for which parameters are already available. 

Free Wilson analyses may include far fewer variables than substituents, if group contributions being not significant are eliminated. Indicator variables for 28 different structural features and different test models and 15 interaction terms were investigated to describe the inhibition of dihydrofolate reductase by 2,4-diaminopyri-midines (52) 9 indicator variables and 2 interaction terms were selected and eq. 197 was derived out of the 2047 theoretically possible linear combinations of any numbers of these variables [412]. 

Mager [414 — 416] introduced the term reduced Free Wilson model for this modification and proposed the use of stepwise regression analysis to derive the equation some more examples of this approach have been published [417, 544, 545]. However, one should bear in mind that the significance of a certain group contribution not only depends on its confidence interval but also on the selection of the reference substituents [390, 391, 410]. 

ILs, fluoroalkyl-functionalized ILs exhibited a higher separation for CO2/CH4 and a lower one for CO2/N2. The authors tried to correlate the selectivity with the molar volume and the solubility parameters 5 derived from chemical group contributions [74] and concluded that the model was able to predict trends in CO2 separations however, no absolute values could be calculated via this method. 

For each optimal path previously selected, the output data from the different subprocesses in the network is combined and presented as total emissions of a compound. To perform that analysis, the impact assessment requires component-specific CFs, which are estimated based on a methodology implemented in LCSoft, in particular Tool-2 (Table 1.2) using group-contribution-H (GC-t) property models together with the US EPA USEtox database. 

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