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last update
28-Jan-2013

HSP Application note #29

GC of ICH solvents and Hansen Solubility Parameter (HSP)

2010.4.4

HSPiP Team Senior Developer, Dr. Hiroshi Yamamoto

 

Hansen Solubility Parameters (HSP)

Hansen Solubility Parameters(HSP) were developed by Charles M. Hansen as a way of predicting if one material will dissolve in another and form a solution. They are based on the idea that "like dissolves like" where one molecule is defined as being 'like' another if it bonds to itself in a similar way.
Specifically, each molecule is given three Hansen parameters, each generally measured in MPa0.5:
dD:The energy from dispersion bonds between molecules
dP:The energy from dipolar intermolecular force between molecules
dH:The energy from hydrogen bonds between molecules.
These three parameters can be treated as Vector for a point in three dimensions also known as the Hansen space. The nearer two molecules HSP Vector are in this three dimensional space, the more likely they are to dissolve into each other.

What can perhaps be surprising is that one can assign HSP to so many different things. Gases like carbon dioxide, solids like carbon-60, sugar, and biological materials like human skin, depot fat, DNA, and even some proteins all have HSP. The list can be continued with drugs, polymers, plasticizers, and in fact any organic material and even many inorganic materials like salts. The only requirement for an experimental confirmation is that the material must behave differently in a sufficient number of test solvents upon contact.

Pirika JAVA Demo Applet calculate HSP. HSPLight is available here.
Please refer to e-Book of HSPiP if you want know more about HSP.
About the Power Tools that handle HSP more effectively.

 

I got the GC data for Class 1 and Class 2 solvents from Agilent Technologies.
(If you want to know the meaning of class1 class 2, please read this article)

Hcode No Name BP RT
456 1 Methanol 337.85 1.749
239 2 1,1-Dichloroethylene 304.71 2.722
10 3 Acetonitrile 354.75 3.21
524 4 Methylene chloride 312.9 3.571
1228 5 trans-1,2-dichloroethylene 320.85 4.027
417 6 hexane 341.88 4.548
224 7 cis-1,2-dichloroethylene 333.65 6.11
531 8 Nitrobenzene 483.95 6.11
156 9 trichloromethane 334.33 6.881
122 10 carbon tetrachloride 349.79 7.607
181 11 Cyclohexane 353.87 7.607
647 12 1,1,1-trichloroethane 347.233 7.607
52 13 benzene 353.24 8.575
291 14 1,2-dimethoxyethane 357.75 8.575
367 15 1,2-dichloroethane 356.594 8.968
649 16 trichloroethylene 360.1 11.574
477 17 methyl cyclohexane 374.084 12.619
306 18 1,4-Dioxane 374.47 13.867
598 19 Pyridine 388.41 20.145
637 20 Toluene 383.78 20.82
474 21 2-Hexanone 400.7 22.676
148 22 chlorobenzene 404.87 23.488
333 23 ethylbenzene 409.35 23.684
297 24 DMF 425.15 23.814
5323 25 m-xylene 412.27 24.204
697 26 p-xylene 411.51 24.4
698 27 o-xylene 417.58 24.4
285 28 N,N-Dimethylacetamide 439.25 24.4
618 29 Tetralin 480.77 26.678

With HSPiP ver. 3. 0.25, I made GCRI simulation.

HSPiP(Hansen Solubility Parameters in Practice)

The first edition of HSPiP that appeared in November, 2008, greatly enhanced the usefulness of the Hansen solubility parameters (HSP).

The HSP values of over 1200++ chemicals and 500 polymers are provided in convenient electronic format and have been revised and updated using the latest data sources in the second edition (March, 2009).

A third edition of the HSPiP appeared in March, 2010. There are now 10,000 compounds in the HSP file which also includes data on density, melting point, boiling point, critical parameters, Antoine constants and much more. The user is able to carry out many different sorts of optimisations of solubility, evaporation, diffusion, adhesion, create their own datasets (automatically if required) and explore the huge range of applications for HSP in coatings, paints, nanoparticles, cosmetics, pharma, organic photovoltaics and much more.

The 3rd Edition v3.1 was released on 12 December 2010. Current users can upgrade free (now v3.1.09) by downloading the latest .msi installer from http://hansen-solubility.com

The 4th Edition v4.0.x was released on 2 Jan. 2013. The Current users can upgrade with free charge.

2013.1.28 The Visual How to manual of HSPiP. You can understand what HSPiP can do.
Please check the Functional Group List whether your targets are available with HSPiP.
How to purchase HSPiP
2013..1.2 The HSPiP ver. 4 include Power Tools for HSPiP power user.

If you have Smiles structure and HSPiP software, Y-MB function will calculate HSP immediately.

Smiles(Simplified Molecular Input Line Entry Syntax)

SMILES is a string obtained by printing the symbol nodes encountered in a depth-first tree traversal of a chemical graph.
"Organic subset" of B, C, N, O, P, S, F, Cl, Br, and I, brackets can be omitted.
Branches are described with parentheses, as in CCC(=O)O for propionic acid
Double and triple bonds are represented by the symbols '=' and '#'
Ring closure labels are used to indicate connectivity between non-adjacent atoms in the SMILES

Pirika JAVA Demo Applet getting Smiles. Draw2Smiles is available here.
Now we have Power Tool "Draw 2 Smiles", GUI HTML5 software on HSPiP ver. 4.

 

 

 

The result is not so good.
Especially, NO. 8 nitrobenzene.
I believed that is is not nitrobenzene but nitoroethane.
(I mailed to Agilent Technologies but not yet got the answer.
I got the answer. No.8 is nitromethane! Thanks.)

 

I used experimental boiling point instead of simulated boiling point.
(And No.8 as nitoromethane.)

The result become much better.
So, we can conclude that HSP simulation is not bad, but boiling point estimation need to improve for this GCRI simulation.

Y-MB Properties Estimation

Y-MB break Smiles into correspponding Functional Groups and Estimate various Properties. These estimation schemes are come from Pirika technologies.

Pirika JAVA Demo Applet calculate Properties. PirikaLight is available here.
Now we have Power Tool "Y-Predict", GUI HTML5 software on HSPiP ver. 4.

2011.2.7

Y-MB boiling point estimation improved for these compounds.

 

The last point, No. 29 Tetralin, maybe they change oven temperature so retention time become short.

Retention time for HPLC
HPLC analysis of PAHs
HPLC analysis of medicine of Epilepsia
HPLC analysis of Anti-oxidant.
HPLC analysis of Sulfa Drugs.
HPLC analysis of Plasticizer

Other topic of Bio Medical

GC data of class 1, class 2 solvents in Q3C:
HSP and Tamiflu: Solubility parameter of Tamiflu or other H1N1 antiviral compounds
HSP for Rabbit: How to design eau de Cologne for rabbit. what LD50(skin, rabbit) means.
HSP and logP: logP, logKow, it is just HSP volume.
HSP and Carcinogenicity: SOM(self organization map) analysis of Poly-chlorinated compounds
HSP and Endocrine Disruptor: categorize by SOM.
HSP and AntimicroBial. Sulfa Drugs and other kind of Drugs.
Gall stone solubilizer: How to dissolve Cholesterol base Gall Stone.
Caco-2 cell monolayer apparent Permeability:SOM analysis