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Application of the HLD Microemulsion Model for the Development of Phase Stable SOW Type Hard Surface Cleaner Formulation 105 th AOCS Annual Meeting and.

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Presentation on theme: "Application of the HLD Microemulsion Model for the Development of Phase Stable SOW Type Hard Surface Cleaner Formulation 105 th AOCS Annual Meeting and."— Presentation transcript:

1 Application of the HLD Microemulsion Model for the Development of Phase Stable SOW Type Hard Surface Cleaner Formulation 105 th AOCS Annual Meeting and Expo Division of Surfactants and Detergents, Session 4.1b May 4-7, 2014, San Antonio, TX E. Szekeres, M.M. Knock, R. Zhang, R. Khan, and D.R. Scheuing

2 Outline Background on ready to use (RTU) cleaner formulations Goal and Strategy HLD model use for formulation support Experimental testing of model predictions Conclusions

3 RTU Cleaners and HLD model Ready to use (RTU) cleaners: hard surface spray cleaners, wipe lotions, etc. Typical Composition: Surfactants below 5% (lower is preferred) Electrolytes (buffering/pH adjustment agents, etc.) Fragrance below ~ 0.3% Lots of water  water to oil ratio is extreme! Extreme high water to oil ratio may influence applicability of HLD model These systems are single phase, unsaturated microemulsions; may influence applicability of HLD model

4 We like our RTU cleaners sparkling clear Phase separation causes clouding, inhomogeneity Phase separation is typically driven by fragrance Fragrance oils have low water solubility Surfactant micelles must solubilize fragrance well Fragrance type impacts surfactant choice Surfactant and fragrance oil hydrophobicity must be appropriately matched Must have enough surfactant to completely solubilize the fragrance Surfactant system design can be very time consuming  rely on HLD model to speed up work

5 Goal and Strategy Goal Determine how well HLD model works for RTU surfactant design Strategy Use the HLD model to select surfactants for a two-surfactant system that solubilizes a model fragrance oil Test the surfactant selection in the lab under realistic RTU conditions Compare HLD predictions with lab findings Observe limitations

6 Model system Composition 2% model oil ( EACN = 5.3) – represents the fragrance 0.5% NaCl – represent electrolytes No alcohol/cosolvent Two surfactants - Use the HLD model for surfactant selection Design Criteria Single phase system Robust to temperature change Minimized surfactant concentration

7 HLD model predicts microstructure of the self- assembly HLD Model Electrolyte Oil Surfactant Temperature Cosolvent HLD value InputOutput HLD > 0 w/o HLD < 0 o/w HLD = 0 bicontinuous Look for negative HLD, but close to zero

8 Two-surfactant formulation Use HLD model Select one hydrophobic surfactant with HLD > 0 Select one hydrophilic surfactant with HLD < 0 Determine optimized surfactant mixing ratio to get to o/w microemulsion region Ignore potential non-linearity of surfactant mixing Go to the lab Do surfactant mixing ratio scan with WOR ~ 1 system to test surfactant hydrophobicities and optimized surfactant mixing ratio predicted by HLD model Do ratio scan under RTU conditions to see if predictions still hold

9 The HLD model equations For anionic surfactants: choose this as the hydrophobic surfactant For nonionic surfactants: choose this as the hydrophilic surfactant Electrolyte Type/conc. Oil type Surfactant parameters Temperature coefficient Cosolvent function Electrolyte coefficient depends on surfactant Sign of temperature term opposite of anionic

10 Select anionic and nonionic surfactant for a model oil (EACN = 5.3) Salinity, NaCl wt%0.5 T, Celsius20 Oil EACN5.3 k0.16 α T, 1/Celsius0.01 Optimum Cc at 20C1.49 Anionic surfactants* (Sulfonates, sulfosuccinates) Non-ionic surfactants** (Ethoxylates) Salinity, NaCl wt%0.5 T, Celsius20 Oil EACN5.3 k0.16 α T, 1/Celsius0.1 b0.13 Optimum Cc at 20C1.28 at 2C : Cc optimum = 1.31 at 49C: Cc optimum = 1.78 at 2C: Cc optimum = 3.08 at 49C: Cc optimum = -1.62 Choose AOT as the hydrophobic surfactant (Cc = 2.55*) because its Cc > 1.78 Choose Surfonic L12-8 as the hydrophilic surfactant (Cc = - 5.7**) because its Cc < - 1.62 * Formulating with the HLD-NAC; by Edgar J. Acosta, April 25-27, 2012. Pleasanton, California, USA **based on Colloids and Surfaces A: Physicochem. Eng. Aspects 320 (2008) 193–204

11 Phase Inversion Predictions w/o o/w Formulation must remain o/w type across temperature range Blue line shows phase inversion between 0.7 – 0.9 AOT weight fraction Model predicts only slight mixing ratio drift with temperature

12 WOR ~ 1 systems: Test tubes in line with HLD predictions “Fish”-like conditions (WOR=1.94, 3% surfactant) at 20C Surfonic L12-8 is hydrophilic as predicted AOT is hydrophobic as predicted Liquid crystals form near phase inversion Model predicts phase inversion at AOT/Surfonic = 0.8 Test tubes suggest phase inversion between AOT/Surfonic = 0.73 and 0.82 Ignoring synergy is not detrimental Model predicts phase inversion at AOT/Surfonic = 0.8 Test tubes suggest phase inversion between AOT/Surfonic = 0.73 and 0.82 Ignoring synergy is not detrimental AOT rich side Surfonic rich side w/o o/w Inversion LC zone 3 phase system

13 RTU conditions: Test tubes in line with predictions RTU cleaner-like conditions (WOR=40, 3% surfactant, 2% oil) at 20C Surfactants keep their hydrophobicity/hydrophilicity Liquid crystal impacted region expands “formulation” to be shifted in the hydrophilic direction to avoid LC region Liquid crystals obscure phase inversion Phase inversion remains around AOT/Surfonic = 0.73 and 0.82 Liquid crystals must be tracked for formula optimization Liquid crystals obscure phase inversion Phase inversion remains around AOT/Surfonic = 0.73 and 0.82 Liquid crystals must be tracked for formula optimization AOT side w/o o/w Inversion/LC zone Single phase tube Excess oil AOT rich side Surfonic rich side

14 RTU systems: optimizing robustness requires lab work Total surfactant concentration, wt% AOT weight ratio HLD model outages: Ignores liquid crystals – surfactant mixing ratio deviation between model and experiment increases at higher surfactant concentrations Doesn’t predict total surfactant concentrations (NAC model needed) Phase behavior map of AOT, Surfonic L12-8, 2% model oil, 0.5% NaCl at T=20C

15 Testing the effect of temperature in lab Model prediction of phase boundaries reflect realistic temperature effect trends Liquid crystals cause deviation between model and experimental data 3% surfactant AOT weight ratio

16 Conclusions HLD model predictions quite worked well for WOR~1 systems For RTU type systems the HLD model gave Appropriate surfactant selection guidance, Approximate surfactant mixing ratio range for optimization Realistic temperature effect trends Liquid crystalline phases cause deviation; lab work necessary to stay away from LC regions Model gives good starting point for surfactant selection, and can help save time for product development

17 We could choose the surfactant(s) appropriately For the oil to be solubilized We could check the effect of temperature, salt, etc. To engineer sufficiently robust formulation We would be able to select appropriate surfactants quickly But we would have to still keep our lab coats! So, if we knew the parameters……

18 Acknowledgments Clorox S&D Division, AOCS Edgar Acosta for helpful discussions – And You, The Audience and Consumer !

19 Appendix – Calculation of the optimum Cc parameters Calculation of the optimum Cc parameters For the anionic surfactant in the absence of alcohols the HLD equation becomes At optimum Rearranging For the non-ionic surfactant the HLD equation becomes Rearranging

20 Appendix Predicting the optimum surfactant mixing ratio Using linear mixing rule where x = mole fraction of surfactant 1 (the anionic surfactant) in the anionic/non-ionic surfactant mixture Term f(A) drops out of the HLD equations in the absence of alcohol Subscript 1 refers to the anionic surfactant Subscript 2 refers to the non-ionic surfactant At the phase inversion (optimum) point The surfactant mixing ratio that brings about the phase inversion (optimum)


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