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20 years of the COSMO-RS theory

Congratulations …!!!

From COSMO-RS thermodynamic of fluid phase equilibriato conceptual design of new industrial processes. Integration of the COSMO-RS methodology into

commercial process simulators

2000. l. E. Grossmann, A. W. Westerberg. Research Challenges inProcess Systems Engineering. AIChE J. 46, 1700-1703

Chemical Engineering “… is concerned with the understanding and development of … chemical process systems, ranging from microsystems to industrial-scale … processes …”

The Chemical Supply Chain

This concept has two different consequences for Chemical Engineering:

1.

• Process performance is determined by “molecular factors”

• More efficient industrial processes can be developed by controlling adequately its molecular level

1 Å 1 nm 1 µm 1 mm meters

Molecules, clustersand aggregates

Pure substances and mixtures

Process Units and Plants

Nano/Micro-Scale Meso-Scale Macro-Scaleps

ns

µs

s

min

hours

years

Distance

Tim

e

1 Å 1 nm 1 µm 1 mm meters

Molecules, clustersand aggregates

Pure substances and mixtures

Process Units and Plants

Nano/Micro-Scale Meso-Scale Macro-Scaleps

ns

µs

s

min

hours

years

Distance

Tim

e

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2.

• Industrial processes can be designed using the information generated by molecular modelling

COSMO-RS theory

This is the contribution of the COSMO-RS theory we want highlight

It is necessary a suitable way to estimate fluid properties using “only” de results of the molecular calculations

Integrating COSMO-RS results into commercial process simulators:

• Allows access to the complete design of a new process using “only” the information obtained by theoretical methods,

• Reducing the expenses in previous laboratory and pilot plant experiments

Understanding both the: • Structure of the Process Engineering • Contents of its integrating parts

Integration of the COSMO-based methodologies into process simulators is related to the conceptual design of new processes

Nu

mb

er of altern

atives to

be evalu

ated

Accu

racy of th

e evalu

ation

Detailed Engineering

Basic Engineering

CO

SMO

-RS

the

ory

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• 70 - 80 % of the capital cost of a new project is determined during its Conceptual Engineering

• Around 50 % accuracy in the total costs may be acceptable

Particularly interesting to propose industrial processes involving new components NOT existing in the database of the process simulators

• At the present about 15 millions of chemical compounds are known, a lot of them with potential interest for chemical industry

• However, only less than 50 thousand of them are available in the databanks of the process simulators

No-inclusion of a compound in the database of a process simulator is usually due to the lack of experimental data of its properties

COSMO-based methods have been incorporated only to the Aspen Technology´s process simulators

The implementation of the COSMO-based methodologies into the Aspen Technology´s programs was not straightforward

It happened through the COSMO-SAC (Lin and Sandler, 2002) derivation of the COSMO-RS model

Property model COSMOSAC

2002: Shiang-Tai Lin, Stanley I. Sandler. A Priori PhaseEquilibrium Prediction from a Segment Contribution SolvationModel. IECR, 41, 899-913.

COSMOSAC property model in Aspen Plus:

• COSMO-SAC model (Lin y Sandler, 2002), Code 1

• COSMO-RS model (Klamt, 1995), Code 2

• COSMO-SAC model modified by P. M. Mathias, Code 3

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Pure component information needed to specify the COSMOSAC Property model in Aspen Plus:

• Molecular volumen (Å3)

• Sigma profile

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• This is the procedure we use to introduce the COSMO-based methodologies into Aspen Plus

• The information is obtained by COSMOthermXcalculations and manually transferred to Aspen Plus

The last question to be solved:

How the new components are introduced in the database of the process simulator …?

Pseudo-components

Specifying:• Molecular weight• Boiling Temperature• Density

The unknown properties are estimated by the methods and models of the Property System

COSMOthermX Aspen Plus

For properties “poorly integrated” to the Property System of the process simulator,

Empirical correlations are used (as a rule)

Parameters are obtained from experimental data

T

BAln

Example: viscosity

Viscosity-to-temperature Andrade equation

2014. J. de Riva, V. R. Ferro, L. del Olmo, E. Ruiz, R. Lopez, J. Palomar. Statistical refinement and fitting of experimental viscosity-to-temperature data in ionic liquids. IECR, 53, 10475-10484

A and B are regressed from experimental data (when available) or obtained using the QSPR model implemented in COSMOthermX

Fields of application we have explored:

Bioprocesses

Separation processes with Ionic Liquids (ILs)

• ILs are designer solvents …

• Separation processes with ILs are a good example of the practical value and strength of the integration of COSMO-based methods to process simulators

Process simulation stage in the Multi-scale Approachhas certain dual character

New criteria for IL design/selection

Conceptualdevelopment of

industrial processes basedon ionic liquids

Examples:

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1. IL regeneration in separation processes

2. Acetone and toluene (VOCs) absorption

3. Separation of aromatic hydrocarbons from naphtha by extraction with ILs

4. CO2 capture by physical and chemical absorption with ILs

5. Thermodynamic performance of absorption refrigeration cycles with ILs as absorbers

6. Conceptual design of fluid transport operations with ILs and their mixtures

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2012. V. R. Ferro, E. Ruiz, J. de Riva, J. Palomar. Introducing process simulation in ionic liquid design/selection for separation processes based on operational and economic

criteria through the example of their regeneration. Separation and Purification Technology, 97, 195-204.

Separation ProcessLL Extraction

IL Recovery ProcessDistillation

IL

Solvent+Solute(e.g. Aromatic+Aliphatic)

IL+Solute

IL

Solute

Solv.

CRITERION

Separat ion Capacit y

CRITERION

IL Recovery Cost

Simulación de procesos ASPEN

ILs regeneration from their mixtures with organic solvents by vacuum distillation

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ILs regeneration from their mixtures with organic solvents by vacuum distillation

Operating conditions

Energy needs

Capital and operating costs

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5 kPa < PRegenerator (T = 150 ºC) < 30 kPa

145 < QRegeneration (kJ/kg IL regenerated) < 315

ILs regeneration from their mixtures with organic solvents by vacuum distillation

Preliminary cost estimations for the regeneration step in separation processes with ILs were made

IL regeneration from their mixtures with organic solvents: operational conditions and energy duties

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Ace

ton

e ab

sorp

tio

n w

ith

ILs

2012. E. Ruiz, V. R. Ferro, J. Palomar, J. Ortega, J. J. Rodriguez. Interactions of ionic liquids and acetone: thermodynamic properties, quantum-chemical calculation and, NMR

analysis . Journal of Physical Chemistry B, 117, 7388-7398.

X

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Ace

ton

e ab

sorp

tio

n w

ith

ILs

eim[PF6]

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Acetone absorption with ILs

+ [PF6]-

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Acetone absorption with ILs

+ [eim]+

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Clean gas

IL

regenerator

Absorber Acetone

Vacuum pump

Liquid

Regenerated IL

Gas In

IL

Acetone (20 mol%) + N2

Acetonerecovery 99%

T = 15

0 ºC

IL 99 %mol purity

Acetone absorption with ILs

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Cost factors considered:

Vapor Electricity

euro/kgCF

Seuro/kgCost onRegenerati

inM

Absortion

.

Acetone absorption with ILs

(S/F)Min.

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Acetone absorption with ILs

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Acetone absorption with ILs

PF6 BF4 C2H5SO4 C2H6PO4 CH3SO3

4

8

12

16

20

Ab

so

rptio

n c

ost,

eu

ro/t

on

Anion

Separation of aromatic hydrocarbons from naphtha

2013. V. R. Ferro, J. de Riva, D. Sanchez, E. Ruiz, J. Palomar. Conceptual design of unit operations to separate aromatic hydrocarbons from naphtha using ionic liquids. COSMO-based process simulations with multi-component “real” mixture feed. Chemical Engineering Research and Design, 94, 632-647

• Probably, the application of the ILs in separation processes most investigated up to now

• Usually studied using the model of binary (aromatic + aliphatic) hydrocarbon mixtures (benzene + hexane), (toluene + heptane), etc.

• Subject of several process simulations and, perhaps, of the first conceptual development of a separation process with ILs (Meindersma and de Haan, 2008)

• Investigated in long term pilot plant experiments (Meindersma et al., 2012)

Separation of aromatic hydrocarbons from naphtha

98% aromatic recovery in extractOp. Cond. 40 ºC, 1 atm

99 %mole (purity) IL regeneratedOp. Cond. 230-330 ºC

Sep

arat

ion

of

aro

mat

ic h

ydro

carb

on

s fr

om

nap

hth

aComponent wt%

Benzene 1.8

Toluene 3.3

Ethylbenzene 2.0

m-Xylene 2.9

n-Hexane 43.2

n-Heptane 15.8

n-Octane 31.0

Mixture 1

Mixture 2

28 components• Alkanes• Cycloalkanes• Aromatics

Individual ILs:

• CnmimNTf2

• CnmimTfO

• 4-mebupyBF4

• 3-mebupyDCN

• binary, ternary and quaternary mixtures of them

Extracting solvent:

Sep

arat

ion

of

aro

mat

ic h

ydro

carb

on

s fr

om

nap

hth

a

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CO2 capture by physical absorption with ILs

2011. J. Palomar, M. Gonzalez-Miguel, A. Polo, F. Rodriguez. Understanding the physical absorption of CO2 in ionic liquids using the COSMO-RS method. IECR, 50, 3452-3463

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5. CO2 capture by physical absorption with ILs

Absorption controlled by:

• Equilibrium• Mass transfer (kinetic control)

TMaximum correlates with the IL viscosity

Thermodynamic control

Kinetic control (Rate-based absorption)

5. CO2 capture by physical absorption with ILs

• Preliminary costs (capital + operating) for the CO2

capture with ILs (physical absorption) are similar or slightly higher than those obtained for CO2 capture with amines but,

• In both cases the capture cost seems to be higher than the U.S. Department of Energy’s target (40 $/metric ton of CO2 captured) for new energy generation technologies

CO2 capture by chemical absorption with ILs

CO2 capture by physical absorption with ILs

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Au

tho

rsh

ip

Juan de Riva Silva

José Suárez Reyes Elia Ruiz Pachón Daniel Moreno Fernández

José Palomar Herrero

Co

llab

ora

tio

n

Víctor Ferro Fernandez