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(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.

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.

SOM: Self Organization Map Neural Network 

The 2D Map of "Smilar vector map to similar 2D position".

If we split dH to dHdo, dHac then HSP vector become 4 dimensions.
That is the very bad news for user. Because the Sphere and GUI can not expand to 4 dimensions.
So we start to develop SOM program to check vector similarity.

Pirika JAVA Demo Applet calculate SOM. SOMDemo is available here.