HSP Application note #26
Yamamoto-Molecular Break (Y-MB) in HSPiP2010.3.21
HSPiP Team Senior Developer, Dr. Hiroshi Yamamoto
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. |
Y-MB Properties EstimationY-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. |
Please refer to Y-Predict, Power tool of HSPiP ver.4.
We re-build Y-MB routine with new functional groups set. In other word, HSP calculation result is bad for some specific functional group containing compounds, then we decide to introduce that functional group to our system. As the result, Y-MB calculation become so stable and high accuracy compare to other HSP estimation method.
The dD calculation, we can estimate plus minus 2.
The estimation values become large for these compounds.
3-Fluorooxetane, Chloromethylsulfide, 1,2,3-Benzotriazole, 1-butene, 1,1-Dibromoethylene, Furan, 2,2,3,5,5-pentafluorotetrahydro-, 1-Methyl Imidazole, hexafluorobenzene, bromotrifluoromethane, Myristicin
The Estimation values become small for these compounds.
Di-(2-Chloroethyl) Ether, methyl trichlorosilane, pyrocatechol, Propylene Carbonate, 3-Methyl Isoxazole, 1,2,3-benzenetriol, Dimethyl Sulfone, Acetylfluoride, Adrenalin, 2-Chloropropenoic Acid
We already fix official values or introduce new functional groups. So, it is very hard to find the reason of these estimation error.
For dP, Y-MB calculation have very large errors.
The estimation values become large for these compounds.
Succinaldehyde, Fumaronitrile, Butadione, Ethylene Methyl Sulfonate, Oxalylchloride, N-Ethyl Formamide, 4-Ethyl-1,3-Dioxolane-2-One, N-AcetylMorpholine, 2,4,6-trinitrotoluene, trichloroethylene
The Estimation values become small for these compounds.
Nitrosobenzene, Nonyl Phenoxy Ethanol, Dichloromethyl Methyl Ether, 1,1,1-trifluoroethane, 2-Nitrothiophene, trans-crotonitrile, Acetylfluoride, 1,2,3-Trichloro Propene, Thiazole, 4-Aminopyridine
These errors are mainly come from symmetry effect.
To determine larger functional groups the accuracy improved.
But some connectivity of FGs make result so complicated.
We have so a lot of to do for version 4 for this properties.
For dH, Y-MB calculation improve so much in version 3.
The estimation values become large for these compounds.
glycerol, Adonitol, 1,2,3-benzenetriol, ethylene glycol, 1,2-propanediol (propylene glycol), monoethanolamine, diethylene glycol, diethanolamine, 1-Ethoxy Ethoxy-2-Propanol, 1,3-propanediol
The Estimation values become small for these compounds.
Isooctyl Alcohol, methylacetylene, Methyl Cedrylone, Tetrahydrothiapyran, succinic anhydride, indene, Hexafluoro Isopropanol, tetrahydrofuran, ethylene oxide, Methyl Eugenol
Different from dP, dH estimation does not effect so much from symmetry.
So, accuracy improved with this version.
We also need to check official database values.
For example, i extract ester compounds from our database, and plot that dP values.
The lactone ester have very large dP values and completely different from other ester.
And Acetate ester and other ester make different lines.
But you can see 2 exceptions.
We need check these compounds and revise the official database values.
it take so a lot of time to do.
After revise the database, build new Y-MB.
We are continuously changing for official database.
Abietic Acid
For some molecules, there is no official HSP values.
At that time, we use Y-MB to calculate HSP.
The Smiles notation of Abietic Acid is
C[C@](C(CCC(C(C)C)=C3)C3=CC1)(CCC2)C1[C@@]2(C)C(O)=O
You just input Smiles into Y-MB text field and push calculate button.
You will get the result, [17.9, 3.2, 5.2] with version 3.
If you use the solubility data and use Sphere calculation, the result is
[17.71, 3.49, 4.32] Radius is 5.
If you use GA option to determine Sphere,
[18.22, 4.77, 4.45] Radius is 6.15
I can say Y-MB and Sphere calculation is almost same for this compound.
We can not available heat of vaporization for large molecules like this.
With that case, we use these technique to determine HSP.
We expand our official database continuously.
