Improvement of predictive tools for vapor-liquid equilibrium based on group contribution methods applied to lipid technology

Daniela S. Damaceno, Olivia A. Perederic, Roberta Ceriani, Georgios M. Kontogeorgis*, Rafiqul Gani

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

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Abstract

Predictive methodologies based on group contribution methods, such as UNIFAC, play a very important role in the design, analysis and optimization of separation processes found in oils, fats and biodiesel industries. However, the UNIFAC model has well-known limitations for complex molecular structures that the first-order functional groups are unable to handle. In the particular case of fatty systems these models are not able to adequately predict the non-ideality in the liquid phase. Consequently, a new set of functional groups is proposed to represent the lipid compounds, requiring thereby, new group interaction parameters. In this work, the performance of several UNIFAC variants, the Original-UNIFAC, the Linear-UNIFAC, Modified-UNIFAC and the Dortmund-UNIFAC is compared. The same set of experimental data and the parameter estimation method developed by Perederic et al. (2017) have been used. The database of measured data comes from a special lipids database developed in-house (SPEED Lipids database at KT-consortium, DTU, Denmark). All UNIFAC models using the new lipid-based parameters show, on average, improvements compared to the same models with their published parameters. There are rather small differences between the models and no single model is the best in all cases.
Original languageEnglish
JournalFluid Phase Equilibria
Volume470
Pages (from-to)249-258
ISSN0378-3812
DOIs
Publication statusPublished - 2018

Keywords

  • Lipids
  • Activity coefficient models
  • UNIFAC
  • Original
  • Linear
  • Modified
  • Dortmund

Cite this

@article{c78b376b9bcb4cd1be7386290a8d3a9a,
title = "Improvement of predictive tools for vapor-liquid equilibrium based on group contribution methods applied to lipid technology",
abstract = "Predictive methodologies based on group contribution methods, such as UNIFAC, play a very important role in the design, analysis and optimization of separation processes found in oils, fats and biodiesel industries. However, the UNIFAC model has well-known limitations for complex molecular structures that the first-order functional groups are unable to handle. In the particular case of fatty systems these models are not able to adequately predict the non-ideality in the liquid phase. Consequently, a new set of functional groups is proposed to represent the lipid compounds, requiring thereby, new group interaction parameters. In this work, the performance of several UNIFAC variants, the Original-UNIFAC, the Linear-UNIFAC, Modified-UNIFAC and the Dortmund-UNIFAC is compared. The same set of experimental data and the parameter estimation method developed by Perederic et al. (2017) have been used. The database of measured data comes from a special lipids database developed in-house (SPEED Lipids database at KT-consortium, DTU, Denmark). All UNIFAC models using the new lipid-based parameters show, on average, improvements compared to the same models with their published parameters. There are rather small differences between the models and no single model is the best in all cases.",
keywords = "Lipids, Activity coefficient models, UNIFAC, Original, Linear, Modified, Dortmund",
author = "Damaceno, {Daniela S.} and Perederic, {Olivia A.} and Roberta Ceriani and Kontogeorgis, {Georgios M.} and Rafiqul Gani",
year = "2018",
doi = "10.1016/j.fluid.2017.12.009",
language = "English",
volume = "470",
pages = "249--258",
journal = "Fluid Phase Equilibria",
issn = "0378-3812",
publisher = "Elsevier",

}

Improvement of predictive tools for vapor-liquid equilibrium based on group contribution methods applied to lipid technology. / Damaceno, Daniela S.; Perederic, Olivia A.; Ceriani, Roberta; Kontogeorgis, Georgios M.; Gani, Rafiqul.

In: Fluid Phase Equilibria, Vol. 470, 2018, p. 249-258.

Research output: Contribution to journalJournal articleResearchpeer-review

TY - JOUR

T1 - Improvement of predictive tools for vapor-liquid equilibrium based on group contribution methods applied to lipid technology

AU - Damaceno, Daniela S.

AU - Perederic, Olivia A.

AU - Ceriani, Roberta

AU - Kontogeorgis, Georgios M.

AU - Gani, Rafiqul

PY - 2018

Y1 - 2018

N2 - Predictive methodologies based on group contribution methods, such as UNIFAC, play a very important role in the design, analysis and optimization of separation processes found in oils, fats and biodiesel industries. However, the UNIFAC model has well-known limitations for complex molecular structures that the first-order functional groups are unable to handle. In the particular case of fatty systems these models are not able to adequately predict the non-ideality in the liquid phase. Consequently, a new set of functional groups is proposed to represent the lipid compounds, requiring thereby, new group interaction parameters. In this work, the performance of several UNIFAC variants, the Original-UNIFAC, the Linear-UNIFAC, Modified-UNIFAC and the Dortmund-UNIFAC is compared. The same set of experimental data and the parameter estimation method developed by Perederic et al. (2017) have been used. The database of measured data comes from a special lipids database developed in-house (SPEED Lipids database at KT-consortium, DTU, Denmark). All UNIFAC models using the new lipid-based parameters show, on average, improvements compared to the same models with their published parameters. There are rather small differences between the models and no single model is the best in all cases.

AB - Predictive methodologies based on group contribution methods, such as UNIFAC, play a very important role in the design, analysis and optimization of separation processes found in oils, fats and biodiesel industries. However, the UNIFAC model has well-known limitations for complex molecular structures that the first-order functional groups are unable to handle. In the particular case of fatty systems these models are not able to adequately predict the non-ideality in the liquid phase. Consequently, a new set of functional groups is proposed to represent the lipid compounds, requiring thereby, new group interaction parameters. In this work, the performance of several UNIFAC variants, the Original-UNIFAC, the Linear-UNIFAC, Modified-UNIFAC and the Dortmund-UNIFAC is compared. The same set of experimental data and the parameter estimation method developed by Perederic et al. (2017) have been used. The database of measured data comes from a special lipids database developed in-house (SPEED Lipids database at KT-consortium, DTU, Denmark). All UNIFAC models using the new lipid-based parameters show, on average, improvements compared to the same models with their published parameters. There are rather small differences between the models and no single model is the best in all cases.

KW - Lipids

KW - Activity coefficient models

KW - UNIFAC

KW - Original

KW - Linear

KW - Modified

KW - Dortmund

U2 - 10.1016/j.fluid.2017.12.009

DO - 10.1016/j.fluid.2017.12.009

M3 - Journal article

VL - 470

SP - 249

EP - 258

JO - Fluid Phase Equilibria

JF - Fluid Phase Equilibria

SN - 0378-3812

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