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HSP Application note #20

Hansen Solubility parameter (HSP) of Polycyclic aromatic hydrocarbons


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.


HSPiP version 3 have function to estimate Gas Chromatography Retention Index (GCRI).

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.

GC retention time is depend on column length, oven temperature, carrier speed, so it is not predictable.
But if it comes to retention index, we can predict with
solubility to poly dimethyl siloxane(PDMS)
vaporization from PDMS

I found a very interesting paper refer to GCRI for polycyclic aromatic hydrocarbons.
I got 17 compounds' GCRI.

name BP GCRI Hcode CAS#
Naphthalene 220.7 530 91-20-3
Acenaphthylene 279 1402 8961 208-96-8
Fluorene 293.6 1522 877 86-73-7
Acenaphtylene 298.9 1429 8961 208-96-8
Anthracene 337.4 1709 5441 120-12-7
Phenanthrene 337.4 1700 5442 85-01-8
Fluoranthene 375 1960 7768 206-44-0
pyrene 404 2000 7769 129-00-0
benz[a]anthracene 436.7 2327 10515 56-55-3
Chrysene 448 2323 7779 218-01-9
benz[e]acephenanthrylene 467.5 2609 21879 205-99-2
benzo[k]fluoranthene 480 2605 20712 207-08-9
benzo[a]pyrene 495 2679 11548 50-32-8
indeno[1.2.3.-cd]pyrene 497.1 2910 21420 193-39-5
benzo[ghi]perylene 501 2959 21880 191-24-2
Dibenz[a,h]anthracene 524.7 2916 20633 53-70-3

Only what you need is smiles notation.

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.

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.


Run HSPiP ver.3 and choose GC from menu bar.
Copy smiles and paste it to text field and push calculator button.
You will get GCRI value.

The absolute value is not good for especially large molecules, but from only structure information, we can estimate GCRI. This would be very powerful tool.

I also got HPLC data for PAHs.


The most popular column for HPLC is ODS column and this column contains Silica-gel covered by Octadecyl. When we insert some chemicals into this column, some chemicals dissolve to octadecyl alkyl chain deeply and some do not. So, highly interacted chemicals will delay to elute. Or some chemicals which are very easily dissolve to carrier liquid, elute very early.

We can evaluate these solubility with Hansen Solubility Parameters (HSP). Molecular size also play important role.

Pirika Java Demo Applet design Carrier Solvent. HPLCDemo is available here.



no name Hcode CAS Hcode RT
1 Naphthalene 530 91-20-3 530 2.137
2 1-Methylnaphthalene 500 90-12-0 500 2.882
3 Acenaphthene 8961 208-96-8 8961 3.436
4 Fluorene 877 86-73-7 877 3.761
5 Phenanthrene 5442 85-01-8 5442 4.282
6 Anthracene 5441 120-12-7 5441 5.153
7 Fluoranthene 7768 206-44-0 7768 6.199
8 Pyrene 7769 129-00-0 7769 6.654
9 Triphenylene 9026 217-59-4 9026 7.335
10 Benzo-[a]-anthracene 10515 56-55-3 10515 8.017
11 Chrysene 7779 218-01-9 7779 8.311
12 Benzo-[b]-fluoranthene 21879 205-99-2 21879 9.415
13 Benzo-[k]-fluoranthene 20712 207-08-9 20712 9.96
14 Benzo-[a]-pyrene 11548 50-32-8 11548 10.616
15 DiBenz-[a,h]-anthracene 20633 53-70-3 20633 12.112
16 Benzo-[g,h,i]-perylene 21880 191-24-2 21880 12.634
17 Indeno-[1,2,3-cd]pyrene 21420 193-39-5 21420 13.413

I do not know the reason, but retention time and molecular volume have very strong correlation. HSP of these molecules are almost same, so solubility to ODS is almost identical. They separate with just size.

If you draw several molecules and calculate each molecules' properties, program will simulate Retention Time (RT) of OSD column for HPLC. If you want to know how to draw molecules, please refer to PowerTools applications. I have full version of this HPLC RT simulation program at PowerTools+ Applications.

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

GC analysis of solvents.