A segmental interaction model for liquid–liquid equilibrium calculations for polymer solutions

Bogdanić, Grozdana; Vidal, J.

doi:10.1016/s0378-3812(00)00432-5

Cited by 38 publications

(38 citation statements)

References 27 publications

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“…Task S1-D2: AIs identification Activity: Retrieve from databases 23 the chemicals that are able to satisfy the product functions f 1 defined in subtask S1-D1.2; select the best performing chemicals in the list; retrieve from databases 23 and/or calculate through appropriate property models [18][19][20][21][22] the needed properties. Subtask S1-D2.1: Product Functions.…”

Section: Task S1-d1: Problem Definitionmentioning

confidence: 99%

“…Activity: For each of the AIs selected in subtask S1-D2.2, collect the necessary information/properties employing the databases 23 or calculate them by employing appropriate property models. [18][19][20][21][22] Assumption: Like dissolves like. 25 Note: The necessary information/properties to be collected in this subtask are:…”

Section: Task S1-d1: Problem Definitionmentioning

confidence: 99%

“…Posed as a reverse design problem, the target properties for the product become the known variables, and, therefore, input for the property models. Appropriate property models [18][19][20][21][22] are employed to estimate the target properties of the candidates so that they may be accepted or rejected. At the same time the mixture compositions that satisfy all the constraints are determined.…”

Section: Introductionmentioning

confidence: 99%

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Design of formulated products: A systematic methodology

2011

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In chemical product design one tries to find a product which exhibits the desired (target) behavior specified a priori. The identity of the ingredients of chemical-based products maybe unknown at the start, but some of their desired qualities and functions are usually known. A systematic model-based computer-aided methodology for design and verification of a class of chemical-based products (liquid formulations) is presented. This methodology is part of an integrated three-stage approach for design/ verification of liquid formulations where stage-1 generates a list of feasible product candidates and/or verifies a specified set through a sequence of predefined activities (work-flow). Stage-2 and stage-3 (not presented here) deal with the planning and execution of experiments, for product validation. Four case studies have been developed to test the methodology. The computer-aided design (stage-1) of a paint formulation and an insect repellent lotion are presented.

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Section: Task S1-d1: Problem Definitionmentioning

confidence: 99%

Section: Task S1-d1: Problem Definitionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Design of formulated products: A systematic methodology

2011

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“…Three mixing rules were used in the SRK equation: van der Waals (vdW) one-fluid, Wong-Sandler and LCVM. The latter two mixing rules incorporate the Bogdanic and Vidal activity coefficient model [67]. All these models involve two adjustable parameters.…”

Section: Modeling Polymeric Systems With Equations Of State Embodyingmentioning

confidence: 99%

“…Two mixing rules were coupled with SRK: the Wong-Sandler rule and the LCVM rule, both considering the activity coefficient model from Bogdanic and Vidal [67]. The models were evaluated using SLE data at atmospheric and high pressure, obtained from literature.…”

Section: Modeling Polymeric Systems With Equations Of State Embodyingmentioning

confidence: 99%

A Survey of Equations of State for Polymers

Guerrieri¹,

Pontes²,

Costa³

et al. 2012

Polymerization

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Activity Coefficient Models Part 2: Local Composition Models, from Wilson and NRTL to UNIQUAC and UNIFAC

Kontogeorgis

Folas

2009

Thermodynamic Models for Industrial Applications

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Traditional cubic EoS using the classical vdW1f mixing rules and activity coefficient models like the Margules and van Laar equations use 'average' or 'overall' compositions. They are models based on 'random mixing'. However, due to intermolecular forces, the mixing of molecules is never entirely random and a way to account for the non-randomness can lead to improved models and better descriptions of phase behavior. Since their advent with the Wilson equation in 1964, 1 local composition (LC) activity coefficient models have drastically changed the range of applicability of liquid phase models.There exist several models which employ the LC concept, which is illustrated in Figure 5.1. All of these models are based on the physical picture that the mixing of molecules is 'non-random' and this is accomplished by using the so-called 'local compositions' which are, in the general case, different from the average concentrations due to the short-range nature of intermolecular forces. Due to their basis in this different principle, LC models differ drastically from random-mixing-based models (Chapter 4). LC models allow for a certain degree of non-randomness and they can thus be expected to represent more realistically the phase behavior of complex mixtures. Of course, we need to know the distribution of the local fractions, which is given by a Boltzmann factor expression, and different functions are employed in the various LC models, see Table 5.1.As we will see, in most cases two interaction parameters per binary mixture in LC models are sufficient for obtaining good VLE results. The interaction parameters in LC models have, as seen from their derivation (see Appendix 5.A), an in-built temperature dependency and some theoretical significance. Moreover, LC models can be readily extended to multicomponent systems, easier than, for example, the van Laar and Margules equations. Two of the LC models, namely Wilson and UNIQUAC, have been further developed into predictive group contribution (GC) versions (ASOG and UNIFAC), suitable for preliminary design in the absence of

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A segmental interaction model for liquid–liquid equilibrium calculations for polymer solutions

Cited by 38 publications

References 27 publications

Design of formulated products: A systematic methodology

Design of formulated products: A systematic methodology

A Survey of Equations of State for Polymers

Activity Coefficient Models Part 2: Local Composition Models, from Wilson and NRTL to UNIQUAC and UNIFAC

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