In Silico Search for Alternative Green Solvents

  • Laurianne Moity
  • Morgan Durand
  • Adrien Benazzouz
  • Valérie Molinier
  • Jean-Marie Aubry
Chapter
Part of the Green Chemistry and Sustainable Technology book series (GCST)

Abstract

The selection of the most appropriate alternative solvents requires efficient predictive tools that avoid resorting to time-consuming trial and error experiments. Several classifications of organic solvents exist but they most often require the knowledge of one or more experimental characteristics, which might be an obstacle in the case of emerging candidates. This chapter gives an overview of existing tools for the characterisation and classification of organic solvents and particular attention is given to purely predictive methods, such as the COnductor-like Screening MOdel for Real Solvents (COSMO-RS). A panorama of the currently available sustainable solvents is given, and these “green” alternatives are compared to the classical organic solvents, thanks to a completely in silico approach. Examples of substitutions are given to illustrate the methodology that can also be used to design new alternatives.

Keywords

Biomass Fermentation Ozone Chlorinate Alkane 

References

  1. 1.
    Reichardt C (1988) Solvents and solvent effects in organic chemistry, 2nd edn. Wiley, New YorkGoogle Scholar
  2. 2.
    Kamlet MJ, Taft RW (1976) The solvatochromic comparison method. 1. The β-scale of solvent hydrogen-bond acceptor (HBA) basicities. J Am Chem Soc 98:377–383CrossRefGoogle Scholar
  3. 3.
    Taft RW, Kamlet MJ (1976) The solvatochromic comparison method. 2. The α-scale of solvent hydrogen-bond donor (HBD) acidities. J Am Chem Soc 98:2886–2894CrossRefGoogle Scholar
  4. 4.
    Kamlet MJ, Abboud JLM, Taft RW (1977) The solvatochromic comparison method. 6. The π* scale of solvent polarities. J Am Chem Soc 99:6027–6038CrossRefGoogle Scholar
  5. 5.
    Abraham MH (1993) Scales of solute hydrogen-bonding: their construction and application to physico-chemical and biochemical processes. Chem Soc Rev 22:73–83CrossRefGoogle Scholar
  6. 6.
    Taft RW, Abboud JLM, Kamlet MJ, Abraham MH (1985) Linear solvation energy relations. J Solution Chem 14:153–186CrossRefGoogle Scholar
  7. 7.
    Katritzky AR, Fara Dan C, Yang H, Tamm K, Tamm T, Karelson M (2004) Quantitative measures of solvent polarity. Chem Rev 104:175–198CrossRefGoogle Scholar
  8. 8.
    Murray JS, Politzer P, Famini GR (1998) Theoretical alternatives to linear solvation energy relationships. Theochem-J Mol Struc 454:299–306CrossRefGoogle Scholar
  9. 9.
    Brinck T, Murray JS, Politzer P (1993) Octanol/water partition coefficients expressed in terms of solute molecular surface areas and electrostatic potentials. J Org Chem 58:7070–7073CrossRefGoogle Scholar
  10. 10.
    Lowrey AH, Cramer CJ, Urban JJ, Famini GR (1995) Quantum chemical descriptors for linear solvation energy relationships. Comput Chem 19:209–215CrossRefGoogle Scholar
  11. 11.
    Katritzky AR, Fara DC, Kuanar M, Hur E, Karelson M (2005) The classification of solvents by combining classical QSPR methodology with principal component analysis. J Phys Chem A 109:10323–10341CrossRefGoogle Scholar
  12. 12.
    Hildebrand J, Scott R (1950) The solubility of nonelectrolytes, 3rd edn. Reinhold, New YorkGoogle Scholar
  13. 13.
    Stefanis E, Panayiotou C (2008) Prediction of Hansen solubility parameters with a new group-contribution method. Int J Thermophys 29:568–585CrossRefGoogle Scholar
  14. 14.
    Benazzouz A, Moity L, Pierlot C, Sergent M, Molinier V, Aubry JM (2013) Selection of a greener set of solvents evenly spread in the Hansen space by space-filling design. Ind Eng Chem Res 52:16585–16597CrossRefGoogle Scholar
  15. 15.
    Gharagheizi F, Sattari M, Angaji MT (2006) Effect of calculation method on values of Hansen solubility parameters of polymers. Polym Bull 57:377–384CrossRefGoogle Scholar
  16. 16.
    Benazzouz A, Moity L, Pierlot C, Molinier V, Aubry JM (2014) Hansen approach versus COSMO-RS for predicting the solubility of an organic UV filter in cosmetic solvents. Colloids Surf A Physicochem Eng Asp (in press). doi: 10.1016/j.colsurfa.2014.03.065Google Scholar
  17. 17.
    Hansen CM (2004) 50 years with solubility parameters – past and future. Prog Org Coat 51:77–84CrossRefGoogle Scholar
  18. 18.
    Cartier A, Rivail JL (1987) Electronic descriptors in quantitative structure-activity relationships. Chemometr Intell Lab 1:335–347CrossRefGoogle Scholar
  19. 19.
    Klamt A, Schueuermann G (1993) COSMO: a new approach to dielectric screening in solvents with explicit expressions for the screening energy and its gradient. J Chem Soc Perk T 2:799–805CrossRefGoogle Scholar
  20. 20.
    Klamt A (1995) Conductor-like screening model for real solvents: a new approach to the quantitative calculation of solvation phenomena. J Phys Chem 99:2224–2235CrossRefGoogle Scholar
  21. 21.
    Klamt A (2005) COSMO-RS: from quantum chemistry to fluid phase thermodynamics and drug design. Elsevier, AmsterdamGoogle Scholar
  22. 22.
    Wichmann K, Diedenhofen M, Klamt A (2007) Prediction of blood–brain partitioning and human serum albumin binding based on COSMO-RS σ-moments. J Chem Inf Model 47:228–233CrossRefGoogle Scholar
  23. 23.
    Klamt A, Eckert F, Diedenhofen M, Beck ME (2003) First principles calculations of aqueous pKa values for organic and inorganic acids using COSMO−RS reveal an inconsistency in the slope of the pKa scale. J Phys Chem A 107:9380–9386CrossRefGoogle Scholar
  24. 24.
    Durand M, Molinier V, Kunz W, Aubry JM (2011) Classification of organic solvents revisited by using the COSMO-RS approach. Chem-Eur J 17:5155–5164CrossRefGoogle Scholar
  25. 25.
    Chastrette M (1979) Etude statistique des effets de solvant—I: principes et applications à l’évaluation des paramètres de solvant et à la classification. Tetrahedron 35:1441–1448CrossRefGoogle Scholar
  26. 26.
    Kerton FM (2009) Alternative solvents for green chemistry. RSC Publishing, CambridgeGoogle Scholar
  27. 27.
    Plechkova NV, Seddon KR (2008) Applications of ionic liquids in the chemical industry. Chem Soc Rev 37:123–150CrossRefGoogle Scholar
  28. 28.
    Ranke J, Stolte S, Störmann R, Arning J, Jastorff B (2007) Design of sustainable chemical products. Chem Rev 107:2183–2206CrossRefGoogle Scholar
  29. 29.
    Klein R, Zech O, Maurer E, Kellermeier M, Kunz W (2011) Oligoether carboxylates: task-specific room-temperature ionic liquids. J Phys Chem B 115:8961–8969CrossRefGoogle Scholar
  30. 30.
    Imperato G, König B, Chiappe C (2007) Ionic green solvents from renewable resources. Eur J Org Chem 7:1049–1058CrossRefGoogle Scholar
  31. 31.
    Moity L, Durand M, Benazzouz A, Pierlot C, Molinier V, Aubry JM (2012) Panorama of sustainable solvents using the COSMO-RS approach. Green Chem 14:1132–1145CrossRefGoogle Scholar
  32. 32.
    Jessop PG (2011) Searching for green solvents. Green Chem 13:1391–1398CrossRefGoogle Scholar
  33. 33.
    Danaché B, Févotte J, Work team of Matgéné (2009) Éléments techniques sur l’exposition professionnelle à cinq solvants chlorés (trichloroéthylène, perchloroéthylène, chlorure de méthylène, tétrachlorure de carbone, chloroforme) – matrices emplois – expositions à cinq solvants chlorés. Institut de veille sanitaire, Umrestte Lyon, Saint-MauriceGoogle Scholar
  34. 34.
    Abel S (1990) Fate and exposure assessment of aqueous and terpene cleaning substitutes for chlorofluorocarbons and chlorinated solvents. U.S. Environmental Protection Agency Office of Toxic Substances Exposure Assessment Branch, Washington, DCGoogle Scholar
  35. 35.
    Tanzi C, Vian M, Ginies C, Elmaataoui M, Chemat F (2012) Terpenes as green solvents for extraction of oil from microalgae. Molecules 17:8196–8205CrossRefGoogle Scholar
  36. 36.
    Hansen CM (2007) Hansen solubility parameters. CRC Press, Taylor & Francis Group, Boca RatonCrossRefGoogle Scholar
  37. 37.
    Heintz J, Touche I, Teles dos Santos M, Gerbaud V (2012) An integrated framework for product formulation by computer aided mixture design. Comput Aided Chem Eng 30:702–706CrossRefGoogle Scholar
  38. 38.
    Moity L, Molinier V, Benazzouz A, Barone R, Marion P, Aubry JM (2014) In silico design of bio-based commodity chemicals: application to itaconic acid based solvents. Green Chem 16:146–160CrossRefGoogle Scholar
  39. 39.
    Barone R, Chanon M, Vernin G, Parkanyi C (2005) Generation of potentially new flavoring structures from thiamine by a new combinatorial chemistry program. In: Mussinan CJ, Ho CT, Tatras Contis E, Parliment TH (eds) Food flavor and chemistry: explorations into the 21st century. RSC, Cambridge, pp 175–212Google Scholar
  40. 40.
    Barone R, Chanon M, Vernin G, Parkanyi C (2010) Computer-aided organic synthesis as a tool for generation of potentially new flavoring compounds from ascorbic acid. In: Ho CT, Mussinan CJ, Shahidi F, Tatras Contis E (eds) Recent advances in food and flavor chemistry: food flavors and encapsulation, health benefits, analytical methods and molecular biology of functional foods. RSC, Cambridge, pp 81–126Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Laurianne Moity
    • 1
  • Morgan Durand
    • 1
  • Adrien Benazzouz
    • 1
  • Valérie Molinier
    • 1
  • Jean-Marie Aubry
    • 1
  1. 1.EA 4478 Chimie Moléculaire et FormulationUniversity of Lille, USTL, ENSCLVilleneuve d’AscqFrance

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