Computerized Optimization of Emulsifiers for Pesticide Emulsifiable

Jul 23, 2009 - The art of developing emulsifiers and emulsifier blends for pesticide emulsifiable concentrates has been practiced for many years. In a...
2 downloads 0 Views 1MB Size
9 Computerized Optimization of Emulsifiers for Pesticide Emulsifiable Concentrates KEN MEUSBURGER

Downloaded by CORNELL UNIV on October 7, 2016 | http://pubs.acs.org Publication Date: June 5, 1984 | doi: 10.1021/bk-1984-0254.ch009

Thompson-Hayward Chemical Company, Kansas City, KS 66106

The art of developing emulsifiers and emulsifier blends for pesticide emulsifiable concentrates has been practiced f o r many years. In a large number of cases, due to the complexity of emulsion systems and the time pressure placed on the p r a c t i t i o n e r , emulsif i e r s are designed by empirical test data coupled with i n t u i t i o n and experience. This t a l k will discuss a logical, numeric method of a) defining an emulsification problem i n terms of averaging e a s i l y understood parameters foroilmixtures, defining the water types, and emulsifier types desired; b) mathematically determining a near neighborhood "best" emulsifier combination to solve the emulsification problem; and c) a subsequent, computerization of the mathematical methods described above. The a g r i c u l t u r a l formulation chemist i s faced with myriad v a r i ables to evaluate i n the development of a new product. This i s an ideal type of problem environment for the employment of a s u i t able conçuter program. The computer program, based on a mathematical model, should be of such character to allow: 1) 2)

Ease of input data c o l l e c t i o n Logical evaluation of a l l pertinent variables and data within a clear, understandable, mathematical model 3) Generation of output data i n a sorted c o l l e c t i o n of "near-neighborhood" best results

For the development of agricultural emulsifiable concentrates the application of the principles of Cohesive Energy Density yields a mathematical model. This model, when written into a computer program, s a t i s f i e s the c r i t e r i a above. To demonstrate the effectiveness of t h i s approach, a review of the C.E.D. p r i n c i p l e s , with an example application, i s given 0097-6156/ 84/ 0254-0121 $06.00/ 0 © 1984 American Chemical Society

Scher; Advances in Pesticide Formulation Technology ACS Symposium Series; American Chemical Society: Washington, DC, 1984.

122

ADVANCES IN PESTICIDE FORMULATION TECHNOLOGY

below. The concept of Cohesive Energy Density was f i r s t develop­ ed by Hildebrand and Scott (1,2) i n t h e i r research to define a physical parameter which would predict the m i s c i b i l i t y of solvents. They found that the square root of the heat of vaporization divided by the molar volume of a solvent gave a useful s o l u b i l i t y parameter. Thus AHy - R T ^ 6 =

=

ΝπΓ» Hfc—>

where AHy i s the heat of vaporization, V i s the molar volume, and RT (3) i s a correction factor involving the universal gas constant and temperature. This parameter squared has the physical dimensions of calories per cubic centimeter. The theory implies, when considering two solvents, that i f t h e i r parameters d i f f e r by a value of less than 2, they are miscible, and i f t h e i r parameters d i f f e r by more than 3.5, they are immiscible. Using these paramemeters, Hildebrand was able to formulate an expression to de­ termine the energy of mixing and an approximate heat of mixing for the combination of two solvents (2)

Downloaded by CORNELL UNIV on October 7, 2016 | http://pubs.acs.org Publication Date: June 5, 1984 | doi: 10.1021/bk-1984-0254.ch009

m

Μ

Μ

ΔΗ ,ΔΕ =φ Φ Α

Β

(X V * X V ) ( 6 - δ / A

A

B

B

A

This equation uses the volume fractions of the two solvents, nominally A and B; the molar fractions of the two solvents φ Λ and φ ; the molar volumes of the two solvents and V ; and the difference between t h e i r respective C.E.D. parameters squared. This approach makes very reasonable predictions concerning the interactions of solvents. Charles M. Hansen (4) was working i n the area of paint tech­ nology. He was aware οΓ the Hildebrand/Scott s o l u b i l i t y param­ eter, and explored the use of the s o l u b i l i t y parameter i n poly­ mer-solvent interactions. He began his research with the con­ sideration of the thermodynamic equation f o r the energy of mixing Β

B

^MIX

=

TAS

^ I X " MIX

SOLUBILITY * AS Η^χ Ψ He noted that the s o l u b i l i t y increased f o r the interaction of two materials as the heat of mixing decreased. He, therefore, took note of the Hildebrand expression f o r the approximation of the heat of mixing

He found that the C.E.D. parameter d i f f e r e n t i a l was not accurate enough for his purposes. Further research showed that added precision could be given to the bulk parameter by considering that parameter as being composed of three d i s t i n c t types of

Scher; Advances in Pesticide Formulation Technology ACS Symposium Series; American Chemical Society: Washington, DC, 1984.

MEUSBURGER

9.

Computerized Optimization of Emulsifiers

123

interactive energies. He postulated that these three s p e c i f i c cohesive energies were attributed to the London cohesive energy, the Keesom cohesive energy, and the hydrogen bonding cohesive energy. He further postulated that these three energy contri­ butions to the bulk cohesive energy density parameter could be described i n a straightforward vector summation expression

Downloaded by CORNELL UNIV on October 7, 2016 | http://pubs.acs.org Publication Date: June 5, 1984 | doi: 10.1021/bk-1984-0254.ch009

6 2

= έ δ

+

6

P

+

δ

Α

He then proceeded to break up the solvent bulk parameter into respective dispersion forces: Keesom, or p o l a r i t y forces; hydrogen bonding forces; and London forces. He did the same for the polymers which were under his consideration. He compared these parameters for solvents and polymers term-wise, and ana­ lyzed their d i f f e r e n t i a l s i n order to make predictions concern­ ing t h e i r s o l u b i l i t y interactions. In conducting 10,000 inter­ action experiments involving solvents and polymers, he found that he could make accurate predictions i n 97% of the cases using his C.E.D. refinements. A. Beerbower and J.R. Dickey (5) were also concerned with the interactions of solvents and polymers as they were working i n an area concerning the effects of hydraulic f l u i d s on hoses and l i n i n g s . In applying the Hansen approach to their particu­ l a r set of polymers and solvents, they found that accurate pre­ dictions required the addition of a correction factor:

^

6

= ( DA "

+

δ

< ΡΑ - W

2

+

δ

< ΗΑ " W

2

2

"