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Designing ionic liquid solvents for carbon capture using property-based visual approach

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Abstract

Recently, ionic liquids (ILs) have been introduced as potential carbon dioxide (CO2)-capturing solvents, as a substitute to conventional amine-based solvents. Conventional amine-based solvents that are used for CO2 capture show some drawbacks, such as high solvent loss, high regeneration energy requirement, and solvent degradation. These shortcomings can be potentially overcome if IL-based solvents are considered. ILs have negligible vapour pressure, high thermal stability, and wide range of thermophysical properties. Nonetheless, using experimentation to identify suitable ILs as CO2-capturing solvents is a tedious and costly task, as there are more than a million possible combinations of cations and anions that make up the ILs. Computer-aided tools have been previously developed for targeted IL design, which often involve non-linear programming. However, non-linear programming sometimes fails to converge, due to enlarged search space for optimal solution and its complex formulations. In this paper, the authors present a simple yet systematic visual approach to design IL solvents for carbon capture. Property integration framework is employed in this approach to systematically design IL, where the design problem can be mapped from the property domain into a cluster domain through clustering technique. The advantage of the visual approach is the ability to enumerate novel IL candidates. Group contribution (GC) method is included in the framework to estimate the properties of designed ILs. By combining property integration framework and GC method, the proposed approach is able to provide a property-based platform to visualise the performance of designed ILs on a ternary diagram. A case study is presented to illustrate the validity of the proposed approach.

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Abbreviations

AUP:

Augmented property index

CAMD:

Computer-aided molecular design

CCS:

Carbon capture and storage

GC:

Group contribution

IL:

Ionic liquid

[MIm]+ :

Methylimidazolium cation

[Py]+ :

Pyridinium cation

[MPyr]+ :

Methylpyrrolidinium cation

[BF4]− :

Tetrafluoroborate anion

[Cl]− :

Chloride anion

[Tf2N]− :

Bis(trifluoromethylsulfonyl)imide anion

[OTf]− :

Trifluoromethanesulfonate anion

d :

Property (d = 1, 2, …, N p)

i :

Component (i = 1, 2, …, p)

j :

Organic functional groups (j = 1, 2, …, r)

k :

Groups (k = 1, 2, …, q)

m :

Cation groups (m = 1, 2, …, s)

n :

Anion groups (n = 1, 2, …, t)

a mn :

UNIFAC group interaction parameter between group m and n

A i :

Constant for group i in Antoine equation

A k,μ :

Contribution of group k to parameter A for viscosity prediction

B i :

Constant for group i in Antoine equation

B k,μ :

Contribution of group k to parameter B for viscosity prediction

C i :

Constant for group i in Antoine equation

c p,k :

Specific heat capacity contribution of group k (J mol−1 K−1)

n k :

Free bond number of group k

P :

System pressure (MPa)

Q k , Q m , Q n :

Group surface area parameter in the UNIFAC model

R k :

Group volume parameter in the UNIFAC model

T :

System temperature (K)

A :

Coefficient in the model equation for the viscosity

AUP k :

Augmented property index for group k

B :

Coefficient in the model equation for the viscosity

C dk :

Property cluster for property d of group k

c p :

Specific heat capacity (J mol−1 K−1)

D :

Distance between two functional groups on ternary diagram

F i :

Auxiliary property for component i (surface fraction/mol fraction)

ΔH vap :

Heat of vaporisation (kJ mol−1)

M :

Molecular weight (g mol−1)

P S i :

Saturated vapour pressure of component i (MPa)

q i :

Parameter relative to the molecular van der Waals surface areas of pure component i

r i :

Parameter relative to the molecular van der Waals volumes of pure component i

V i :

Auxiliary property of component i

v k , v m :

Number of group k

v (i) k , v (i) m :

Number of group k or m in component i

x i :

Mole fraction of component i in liquid phase

x j :

Mole fraction of group j in the mixture

X m , X n :

Fraction of group m or n in the mixture

y i :

Mole fraction of component i in gas phase

μ :

Viscosity (Pa s)

ρ :

Density (g cm−3)

ρ c :

Critical density (g cm−3)

ρ k :

Density contribution of group k (g cm−3)

ρ 0 :

Adjustable parameter for density (g cm−3)

δ :

Reduced density

ϕ r :

Reduced dimensionless Helmholtz function

ϕ r δ :

Derivative of reduced dimensionless Helmholtz function

φ i (T,P,y i ):

Gas-phase fugacity coefficient of component i

γ i :

Activity coefficient of component i

γ C i :

Combinatorial contribution to the activity coefficient of component i

γ R i :

Residual contribution to the activity coefficient of component i

Γ K :

Residual activity coefficient of group k

Γ (i) K :

Residual activity coefficient of group k in pure component i

θ m :

Fraction of group m in a mixture of the liquid phase

ψ nm :

Group interaction parameter

τ d :

dth property

τ min d :

Lower bound of dth property

τ max d :

Upper bound of dth property

ψ d (τ di ):

Property operator of dth property of component i

ψ d (τ dk ):

Molecular property operator of dth property of functional group k

ψ ref d (τ d ):

Reference value for molecular property operator of dth property

Ω dk :

Normalised molecular property operator for dth property of group k

References

  • Abu-Zahra MRM, Abbas Z, Singh P, Feron PHM (2013) Carbon dioxide post-combustion capture: solvent technologies overview, status and future directions. In: Mendez-Vilas A (ed) Materials and processes for energy: communicating current research and technological developments. Formatex Research Center, Badajoz, pp 923–934

    Google Scholar 

  • Bates ED, Mayton RD, Ntai I, Davis JH (2002) CO2 capture by a task-specific ionic liquid. J Am Chem Soc 124:926–927

    Article  CAS  Google Scholar 

  • Blanchard LA, Hancu D, Beckman EJ, Brennecke JF (1999) Green processing using ionic liquids and CO2. Nature 399:28–29

    Article  Google Scholar 

  • Chávez-Islas LM, Vasquez-medrano R, Flores-tlacuahuac A (2011) Optimal molecular design of ionic liquids for high-purity bioethanol production. Ind Eng Chem Res 50:5153–5168

    Article  Google Scholar 

  • Chemmangattuvalappil NG, Eljack FT, Solvason CC, Eden MR (2009) A novel algorithm for molecular synthesis using enhanced property operators. Comput Chem Eng 33:636–643

    Article  CAS  Google Scholar 

  • Chemmangattuvalappil NG, Solvason CC, Bommareddy S, Eden MR (2010a) Reverse problem formulation approach to molecular design using property operators based on signature descriptors. Comput Chem Eng 34:2062–2071

    Article  CAS  Google Scholar 

  • Chemmangattuvalappil NG, Solvason CC, Bommareddy S, Eden MR (2010b) Combined property clustering and GC+ techniques for process and product design. Comput Chem Eng 34:582–591

    Article  CAS  Google Scholar 

  • Chong FK, Foo DCY, Eljack FT et al (2015) Ionic liquid design for enhanced carbon dioxide capture by computer-aided molecular design approach. Clean Technol Environ Policy 17:1301–1312

    Article  CAS  Google Scholar 

  • Eden MR, Jørgensen SB, Gani R, El-Halwagi MM (2004) A novel framework for simultaneous separation process and product design. Chem Eng Process 43:595–608

    Article  CAS  Google Scholar 

  • El-Halwagi MM, Glasgow IM, Qin X, Eden MR (2004) Property integration: componentless design techniques and visualization tools. AIChE J 50:1854–1869

    Article  CAS  Google Scholar 

  • Eljack FT, Eden MR (2008) A systematic visual approach to molecular design via property clusters and group contribution methods. Comput Chem Eng 32:3002–3010

    Article  CAS  Google Scholar 

  • Eljack FT, Eden MR, Kazantzi V, El-Halwagi MM (2006) Property clustering and group contribution for process and molecular design. In: Marquardt W, Pantelides C (eds) 16th European symposium on computer aided process engineering and 9th international symposium on process systems engineering. Elsevier B.V, Garmisch-Partenkirchen, pp 907–912

    Chapter  Google Scholar 

  • Eslick JC, Shulda SM, Spencer P, Camarda KV (2010) Optimization-based approaches to computational molecular design. In: Adjiman CS, Galindo A (eds) Molecular systems engineering. Wiley-VCH, Weinheim, pp 173–194

    Google Scholar 

  • Figueroa JD, Fout T, Plasynski S et al (2008) Advances in CO2 capture technology—The U.S. Department of Energy’s Carbon Sequestration Program. Int J Greenh Gas Control 2:9–20

    Article  CAS  Google Scholar 

  • Freemantle M (2010) An introduction to ionic liquids. The Royal Society of Chemistry, Cambridge

    Google Scholar 

  • Gani R (2004) Chemical product design: challenges and opportunities. Comput Chem Eng 28:2441–2457

    Article  CAS  Google Scholar 

  • Gardas RL, Coutinho JAP (2008a) A group contribution method for heat capacity estimation of ionic liquids. Ind Eng Chem Res 47:5751–5757

    Article  CAS  Google Scholar 

  • Gardas RL, Coutinho JAP (2008b) A group contribution method for viscosity estimation of ionic liquids. Fluid Phase Equilib 266:195–201

    Article  CAS  Google Scholar 

  • Hada S, Herring RH, Eden MR (2013) Design of ionic liquids using property clustering and decomposition techniques. In: Kraslawski A, Turunen I (eds) 23rd European symposium on computer aided process engineering. Elsevier, Amsterdam, pp 955–960

    Chapter  Google Scholar 

  • IEA (2015) World Energy Outlook Special Briefing for COP21. Paris

  • IPCC (2007) Climate Change 2007: Mitigation. Contribution of Working Group III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change

  • Karunanithi AT, Mehrkesh A (2013) Computer-aided design of tailor-made ionic liquids. AIChE J 59:4627–4640

    Article  CAS  Google Scholar 

  • Kheireddine HA, El-Halwagi MM, Elbashir NO (2013) A property-integration approach to solvent screening and conceptual design of solvent-extraction systems for recycling used lubricating oils. Clean Technol Environ Policy 15:35–44

    Article  CAS  Google Scholar 

  • Kim YS, Choi WY, Jang JH et al (2005) Solubility measurement and prediction of carbon dioxide in ionic liquids. Fluid Phase Equilib 228–229:439–445

    Article  Google Scholar 

  • Lei Z, Zhang J, Li Q, Chen B (2009) UNIFAC model for ionic liquids. Ind Eng Chem Res 48:2697–2704

    Article  CAS  Google Scholar 

  • Matsuda H, Yamamoto H, Kurihara K, Tochigi K (2007) Computer-aided reverse design for ionic liquids by QSPR using descriptors of group contribution type for ionic conductivities and viscosities. Fluid Phase Equilib 261:434–443

    Article  CAS  Google Scholar 

  • McLeese SE, Eslick JC, Hoffmann NJ et al (2010) Design of ionic liquids via computational molecular design. Comput Chem Eng 34:1476–1480

    Article  CAS  Google Scholar 

  • Miyafuji H (2013) Liquefaction of wood by ionic liquid treatment. In: Kadokawa J (ed) Ionic liquids—new aspects for the future. InTech, pp 299–314

  • Olajire AA (2010) CO2 capture and separation technologies for end-of-pipe applications—a review. Energy 35:2610–2628

    Article  CAS  Google Scholar 

  • Pires JCM, Martins FG, Alvim-Ferraz MCM, Simões M (2011) Recent developments on carbon capture and storage: an overview. Chem Eng Res Des 89:1446–1460. doi:10.1016/j.cherd.2011.01.028

    Article  CAS  Google Scholar 

  • Plechkova NV, Seddon KR (2008) Applications of ionic liquids in the chemical industry. Chem Soc Rev 37:123–150

    Article  CAS  Google Scholar 

  • Qiao Y, Ma Y, Huo Y et al (2010) A group contribution method to estimate the densities of ionic liquids. J Chem Thermodyn 42:852–855

    Article  CAS  Google Scholar 

  • Rafat A, Atilhan M, Kahraman R (2016) Corrosion behavior of carbon steel in CO2 saturated amine and imidazolium-, ammonium-, and phosphonium-based ionic liquid solutions. Ind Eng Chem Res 55:446–454

    Article  CAS  Google Scholar 

  • Rai G, Kumar A (2013) Calorimetric elucidation of ionic interactions in room temperature ionic liquid solutions. Clean Technol Environ Policy 16:1529–1536

    Article  Google Scholar 

  • Ramdin M, de Loos TW, Vlugt TJH (2012) State-of-the-art of CO2 capture with ionic liquids. Ind Eng Chem Res 51:8149–8177

    Article  CAS  Google Scholar 

  • Rockström J, Steffen W, Noone K et al (2009) A safe operating space for humanity. Nature 461:472–475

    Article  Google Scholar 

  • Rogers RD, Seddon KR (2003) Ionic liquids—solvents of the future? Science 302:792–793

    Article  Google Scholar 

  • Roughton BC, Christian B, White J et al (2012) Simultaneous design of ionic liquid entrainers and energy efficient azeotropic separation processes. Comput Chem Eng 42:248–262

    Article  CAS  Google Scholar 

  • Seddon KR (1997) Ionic liquids for clean technology. J Chem Technol Biotechnol 68:351–356

    Article  CAS  Google Scholar 

  • Shelley MD, El-Halwagi MM (2000) Component-less design of recovery and allocation systems: a functionality-based clustering approach. Comput Chem Eng 24:2081–2091

    Article  CAS  Google Scholar 

  • Shiflett MB, Yokozeki A (2006) Solubility and diffusivity of hydrofluorocarbons in room-temperature ionic liquids. AIChE J 52:1205–1219

    Article  CAS  Google Scholar 

  • Solvason CC, Chemmangattuvalappil NG, Eljack FT, Eden MR (2009) Efficient visual mixture design of experiments using property clustering techniques. Ind Eng Chem Res 48:2245–2256

    Article  CAS  Google Scholar 

  • Span R, Wagner W (1996) A new equation of state for carbon dioxide covering the fluid region from the triple point temperature to 1100 K at pressures up to 800 MPa. J Phys Chem Ref Data 25:1509–1596

    Article  CAS  Google Scholar 

  • The Dow Chemical Company (2003) Ethanolamines

  • U.S. Energy Information Administration (2013) International Energy Outlook 2013. Washington

  • Valencia-marquez D, Flores-tlacuahuac A, Vasquez-medrano R (2012) Simultaneous optimal design of an extractive column and ionic liquid for the separation of bioethanol–water mixtures. Ind Eng Chem Res 51:5866–5880

    Article  CAS  Google Scholar 

  • Verevkin SP (2008) Predicting enthalpy of vaporization of ionic liquids: a simple rule for a complex property. Angew Chem Int Ed Engl 47:5071–5074

    Article  CAS  Google Scholar 

  • Wappel D, Gronald G, Kalb R, Draxler J (2010) Ionic liquids for post-combustion CO2 absorption. Int J Greenh Gas Control 4:486–494

    Article  CAS  Google Scholar 

  • Zaman M, Lee JH (2013) Carbon capture from stationary power generation sources: a review of the current status of the technologies. Korean J Chem Eng 30:1497–1526

    Article  CAS  Google Scholar 

  • Zhang X, Zhang X, Dong H et al (2012) Carbon capture with ionic liquids: overview and progress. Energy Environ Sci 5:6668–6681

    Article  CAS  Google Scholar 

  • Zhou F, Liang Y, Liu W (2009) Ionic liquid lubricants: designed chemistry for engineering applications. Chem Soc Rev 38:2590–2599

    Article  CAS  Google Scholar 

Download references

Acknowledgments

This work was supported by the Ministry of Science, Technology and Innovation (MOSTI) Malaysia under the Grant No. 06-02-12-SF0224. The financial support from the University of Nottingham Research Committee via Dean’s PhD Scholarship is gratefully appreciated.

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Authors and Affiliations

  1. Department of Chemical and Environmental Engineering, Centre of Excellence for Green Technologies, University of Nottingham, Malaysia Campus, Broga Road, 43500, Semenyih, Selangor, Malaysia

    Fah Keen Chong, Nishanth G. Chemmangattuvalappil & Dominic C. Y. Foo

  2. Department of Chemical Engineering, College of Engineering, Qatar University, PO Box 2713, Doha, Qatar

    Fadwa T. Eljack & Mert Atilhan

Authors
  1. Fah Keen Chong
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  2. Nishanth G. Chemmangattuvalappil
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  3. Fadwa T. Eljack
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  4. Mert Atilhan
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  5. Dominic C. Y. Foo
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Correspondence to Nishanth G. Chemmangattuvalappil.

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Chong, F.K., Chemmangattuvalappil, N.G., Eljack, F.T. et al. Designing ionic liquid solvents for carbon capture using property-based visual approach. Clean Techn Environ Policy 18, 1177–1188 (2016). https://doi.org/10.1007/s10098-016-1111-5

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