A scientific and systematic methodology for development of microemulsions for use in

household and industrial cleaners

Alan Mortensen, Ph.D.

06-05-2014 1

Background • Esti Chem: Manufacturer of ESTISOL fatty acid esters as alternatives

to hydrocarbon solvents for more than 20 years. • ESTISURFTM microemulsion packages have been offered for more

than 10 years. • Growing legislative pressure on hazardous solvents has generated a

need for cleaning agents free from such solvents but with equal or better cleaning performance.

• Esti Chem took up this challenge and established a 1 year basic R&D project with the goal of formulating ESTISURFTM microemulsion packages with a superior cleaning profile.

• This presentation explains the project work, testing methods and the key results obtained.

06-05-2014 2

Goal

• Develop a product that:

– Is efficient for hard surface cleaning

– Does not pose a risk to the environment

– Pose a low risk to human health (e.g. lower alkalinity)

– Is cost effective

– Can be diluted and rinsed with water

06-05-2014 3

Emulsion vs. Microemulsion

Emulsion

• Opaque

• Droplet size: micron

• Requires energy to form

• UNSTABLE

Microemulsion

• Clear/translucent

• Droplet size: nanometer

• Forms spontaneously

• STABLE

06-05-2014 4

Microemulsions vs. Emulsifiers

• Microemulsions include a solvent that helps to remove types of dirt that can only be cleaned by emulsifers with difficulty

– Asphalt

– Heavy duty dirt

– Grease

06-05-2014 5

Fatty Acid Esters

• Benefits compared to hydrocarbon solvent-based cleaning systems:

– Microemulsions based on fatty acid esters pose low risk to health and environment

– Fatty acid esters are based on renewable resources

06-05-2014 6

Test Methodology (1)

• Standard dirt

– Mixture of transmission oil, motor oil, vaseline, iron oxide, graphite, bentonite

• Painted stainless steel plates

– How to apply: dissolved in solvent using applicator?

• Gives an uneven layer or a layer that is too thick

• Another method of application is needed

06-05-2014 7

Test Methodology (2)

• Place 0.5 g dirt on plate

• Distribute with napkin until the layer is uniform

– Reproducibility acceptable

06-05-2014 8

Test Methodology (3)

• Apply dirt to plate

• Place cleaner samples on dirty plate

• Contact time typically 1-5 minutes

• Flush plate with air-pressurized water

– Reproducibility

– No mechanical cleaning – just the effects of chemistry

• Quantify performance

06-05-2014 9

Quantification

06-05-2014 10

• Visual inspection

– Prone to subjectivity

– Lack of reproducibility

• Color measurement

– Measure whiteness (L)

– Non-subjective

– Reproducible

Formulations (1)

Required components

• Solvent

• Emulsifier(s)

• Water

Desired components

• Solvent

• Emulsifier(s)

• Water

• Co-solvent(s)

• Co-emulsifer(s)

• Hydrotrope

06-05-2014 11

Formulations (2)

• In order to make the best product we would like to test a large number of components (78)

• How to test such a large number of components without having to do thousands of formulations?

– Maximum amount of information from a minimum of experiments

06-05-2014 12

Design of Experiments

• Principles – Vary more than one factor at a time instead of one factor at a

time to discover potential interactions between components

– Based on statistics develop a mathematical model that describes the measured data (whiteness, L) as a function of variables (concentrations of components)

L = a1·A + a2·B + … + b1·A·B + b2·A·C + …

– Specialized software required

06-05-2014 13

Making the Design (1)

• Add components

• Add ranges

06-05-2014 14

Making the Design (2)

• 4 components yield 20 formulations to test – 78 components would give an enormous number of

formulations to test

• SOLUTION – Divide the components into smaller groups

• Solvents

• Co-solvents

• …

– Screen each group and pick the best component

06-05-2014 15

The Model

• 10 components optimized with respect to concentration

06-05-2014 16

Sequential Model Sum of Squares [Type I] Sum of Mean F p-value Source Squares df Square Value Prob > F Mean vs Total 3.053E+005 1 3.053E+005 Linear vs Mean 6351.19 9 705.69 18.48 < 0.0001 Suggested Quadratic vs Linear 1791.51 45 39.81 1.33 0.3420 Sp Cubic vs Quadratic 46.29 4 11.57 0.26 0.8929 Aliased

06-05-2014 17

Design-Expert® Software

L-værdi

Color points by value of

L-værdi:

87.2

47.6

Actual

Pre

dic

ted

Predicted vs. Actual

40.00

50.00

60.00

70.00

80.00

90.00

40.00 50.00 60.00 70.00 80.00 90.00

L = -0.0083·A - 0.34·B + 1.14·C + 1.41·D + 0.74422·E + 4.59·F + 0.32·G + 0.89·H - 2.00·J - 0.43·K

Actual

Pre

dic

ted

Optimizing

• New design with wider boundaries (5 comp.) – Quadratic model

• Graphical optimization

• Numerical optimization – Multiple parameters

• L

• Concentrations

• Price

06-05-2014 18

Design-Expert® Software

Component Coding: Actual

Highs/Lows inverted by U_Pseudo coding

L-værdi (7,5%)

90.4

83.8

X1 = A: C9-11 + 4EO

X2 = B: C9-11 + 6EO

X3 = C: DPM

Actual Components

D: Amide CDEA = 7.649

E: Isotridecylalkohol + 3EO = 5.000

A (20.351) B (14.000)C (-0.649)

C (7.000)

84

85

86

87

88

89

90

91

L

-væ

rdi

(7,5

%)

A (28.000)

B (6.351)

Commercial product: ESTISURF MF10 (1)

• Optimised formulation based on project work

• Superior all-round performance

• Focused on difficult cleaning jobs

• Flexible formulations and wide dilution ratio with water

06-05-2014 19

Commercial product: ESTISURF MF10 (2)

06-05-2014 20

- Meet us outside, tell us about you cleaning challenge and have brochure!

- Or write to customerservice@estichem.com for product information

Water-in-oil Microemulsions

• Fatty acid esters as the continuous phase

• Water as internal phase

• Small amount of emulsifier

• Good for dissolving difficult-to-remove dirt

– Asphalt

06-05-2014 21

Acknowledgements

• The project was sponsored by the grant scheme for eco-innovation of The Danish Ministry of the Environment

06-05-2014 22