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last update
29-Jan-2013

HSP Application note #6

Hansen Solubility Parameter (HSP) and Liquid-Liquid extraction

2010.5.31

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.

 

We started to study Liquid-Liquid(water) partition coefficient with using HSP.

We show you basic concept in above picture.
If the chemical is relatively easily dissolve to organic solvent, HSP distance is small.
So, the HSP distance from solute to organic solvent will become one of the index for liquid-liquid extraction.

HSP Distance

To calculate the distance (Ra) between Hansen parameters in Hansen space the following formula is used:

HSP distance(Ra)={4*(dD1-dD2)2 + (dP1-dP2)2 +(dH1-dH2)2 }0.5

 

But as we wrote Octanol-water partition coefficient (logP, logKow) case, there is no correlation.
Why this happen?
And how about other organic solvents?

We got several logKD data for Octanol, Chloroform, Carbon tetrachloride, Benzene, hexane(heptane) with Water.

Hcode 542 255
[16,5,11.9] 158.2 [15.49,2.9,4.6] 104.7
Solute Hcode dD dP dH
Vol
1-octanol
DistA
diethyl ether
DistB
methyl alcohol 456 14.7 12.3 22.3
40.6
-0.77
13.0
-1.15
20.1
ethyl alcohol 325 15.8 8.8 19.4
58.6
-0.31
8.4
-0.57
15.9
propyl alcohol 569 16 6.8 17.4
75.1
0.25
5.8
-0.02
13.4
butanol 92 16 5.7 15.8
92
0.88
4.0
0.89
11.6
1-pentanol 552 15.9 5.9 13.8
108.6
1.56
2.1
1.20
9.7
1-hexanol 930 15.9 5.8 12.5
135.8
2.03
1.0
1.80
8.5
1-heptanol 931 16 5.3 11.7
141.8
2.41
0.4
2.40
7.6
acetic acid 5 14.5 8 13.5
57.6
-0.17
4.5
-0.34
10.4
propanoic acid 576 14.7 5.3 12.4
75
0.33
2.7
0.27
8.3
butyric acid 114 15.7 4.8 12
92.6
0.79
0.6
0.61
7.7
hexanoic acid 1022 16.3 4.2 11.5
126.3
1.92
1.1
1.95
7.2
pentanoic acid 1023 15 4.1 10.3
109.5
1.39
2.7
1.00
5.9
Trichloroacetic Acid 861 18.3 7 13
101.6
1.33
5.1
1.21
10.9
dichloroacetic acid 945 18.2 8.1 12.2
83
0.92
5.4
1.31
10.7
chloroacetic acid 129 17.7 10.4 12.3
68.8
0.22
6.4
0.37
11.6
methyl acetate 464 15.5 7.2 7.6
79.8
0.18
4.9
0.43
5.2
ethyl acetate 328 15.8 5.3 7.2
98.6
0.73
4.7
0.93
3.6
acetone 7 15.5 10.4 7
73.8
-0.24
7.4
-0.21
7.9
ethylamine 331 15 5.6 10.7
65.6
-0.30
2.4
-1.18
6.7
propylamine 580 16 4.9 8.6
83
0.28
3.3
-0.54
4.6
o-vanillin 10812 19.3 11.1 13.9
127.7
1.37
9.2
1.35
14.6
i-vanillin 21944 19.3 11.1 13.9
127.7
0.97
0.82
isobutanol 431 15.1 5.7 15.9
91.9
0.65
4.4
0.53
11.7
Phenobarbital  20331 19.9 16.4 10.4
181.3
1.71
13.9
1.51
17.1
Pent​obarbital 21943 17.7 14.2 9.6
201.3
2.10
10.1
1.28
13.1

 

logKD KD=[A]solvent/[A]water [A] ml conetntration
156 122 52 417
[17.8,3.1,5.7] 80.5 [17.8, 0, 0.6] 97.1 [18.4,0,2] 89.5 [14.9,0,0] 131.4
chloroform DistC carbon tetrachloride DistD benzene DistE hexane DistF
-1.26
20.0
-2.10
25.7
-1.89
24.9
-2.80
25.5
-0.85
15.4
-1.40
21.1
-1.62
20.2
-2.10
21.4
-0.40
12.8
-0.82
18.5
-0.70
17.5
-1.52
18.8
0.45
11.0
-0.40
16.6
-0.12
15.7
-0.70
16.9
1.05
9.4
0.40
14.9
0.62
14.1
-0.40
15.1
1.69
8.2
0.95
13.8
1.30
13.0
0.46
13.9
2.41
7.3
1.67
12.8
1.91
12.1
1.01
13.0
-1.60
11.3
-2.45
16.6
-2.26
16.0
-3.06
15.7
-0.96
9.4
-1.60
14.3
-1.35
13.8
-2.14
13.5
-0.27
7.8
-0.97
13.1
-0.96
12.3
-1.76
13.0
1.15
6.6
0.57
12.1
0.30
11.2
-0.46
12.6
0.28
7.3
-0.42
11.9
-0.10
11.5
-1.00
11.1
-0.69
8.3
-1.66
14.3
-1.30
13.0
-2.63
16.3
-0.89
8.2
-2.31
14.2
-1.40
13.0
-2.72
16.1
-1.92
9.8
-2.56
15.7
-1.60
14.7
-3.14
17.1
1.16
6.4
0.32
11.0
0.53
10.8
-0.26
10.5
1.80
4.8
0.95
9.4
1.01
9.1
0.29
9.1
0.24
8.7
-0.30
13.0
-0.05
12.9
-0.91
12.6
-0.35
7.9
-1.27
12.8
-1.30
12.4
-1.77
12.1
0.26
5.0
-0.59
10.0
-0.52
9.5
-1.00
10.1
2.30
11.8
1.40
17.6
1.87
16.4
0.53
19.8
1.18
0.04
0.74
-0.85
0.34
11.8
-0.32
17.2
-0.11
16.4
-0.60
16.9
0.62
14.7
-0.63
19.6
-0.01
18.7
-2.22
21.8
1.38
11.8
-0.03
16.8
0.74
16.2
-1.30
18.0

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.

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.


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.

 

As we wrote at logP article, there is no correlation logP and HSP distance.
HSP Volume work much better.

 

 

If you want to know how to draw molecules, please refer to Power Tools applications. The full version of this estimation routine is implemented into Y-Predict Powert Tools in HSPiP ver. 4.

 

But, for hexane, logKD and HSP Distance have some correlation.
There are 2 lines.


So, we checked which solute belong to which line.

Alcohols and Amides compounds belong to upper line.

 

Carboxylic Acids, Ketones, Esters compounds belong to lower line.

 

And o-Vanillin, o-Anisic acid, p-hydroquinone, benzoic acid, p-hydroxybenzaldehyde are exceptions.

 

And amines compounds are so strange.

 

We already show a lot of HPLC data analyze with HSP.
With this result, we can understand why HSP can predict retention time of HPLC .

Chromatography

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.

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 Helper applications. I have full version of this HPLC RT simulation program at Helper Applications.

We need to handle with care for some exceptional compounds.

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
HPLC analysis of Carboxylic acid

For other type of organic solvents, Carbon tetrachloride, benzene are almost same tendency to hexane.

Alcohols and Amides compounds

 

Carboxylic Acids, Ketones, Esters compounds

Carbon tetrachloride, benzene and Hexane, we can estimate logKD from HSP distance.

 

Alcohols and Amides compounds

 

Carboxylic Acids, Ketones, Esters compounds

 

Chloroform-water, Diethyl Ether-water L-L extractions, it is a little bit hard for predict with HSP.

With this result, we ignored distance from water.
We soon make QSPR model with both distance.

Now we are trying to divid dH term into dH(donor) dH(acceptor) .
This technique may improve understanding these result.

Please refer to extraction of by product from product example.