Emulsion Stability Matt Vanden Eynden, Ph.D. Formulaction, Inc. - - PowerPoint PPT Presentation

Effect of Fragrances on Perfume Emulsion Stability

Matt Vanden Eynden, Ph.D. Formulaction, Inc.

Presentation Outline

• Fragrances, once introduced into cosmetic and personal

care applications, can occasionally impact the cohesion and stability of end-products and lead to instabilities.

• The disruption of the emulsion or the movement kinetics
• f the fragrance component can cause visual phase

separation, redispersibility issues and performance issues that render the material unlike the unaged

• version. It is essential to provide stable products to avoid

customer dissatisfaction.

• While visual shelf life analysis is a direct method for

investigation it can become time consuming and can also be a subjective measurement.

• Therefore, it is of interest to the formulator to design a

test or have access to data that will quantify these destabilizations.

Presentation Outline

• A group at Givaudan (Switzerland) provided stability data on some perfume and fabric care

emulsions, demonstrating the stability of the materials and how they are analyzed inside of their labs.

• Monitoring is done in less than a day to provide quantitative stability results for these emulsions.

• Turbiscan technology (Formulaction, FR)

utilizes an 880 nm light source and a moving reading head to analyze the static light scattering data at all points in transparent (transmission) and opaque (backscatter) samples.

• By detecting the light intensities at every 40

µm of sample height, a resolved picture of the particle migration and particle size change can be quantitatively determined.

• Samples as high as 95% volume fraction of

particles can be analyzed, allowing materials to remain in their native state for analysis.

Turbiscan: Instrument Technology and Theory

Backscattering and transmission signals are dependent upon two factors: d : particle size Φ : particle concentration

Scans are made over the entire sample height and over time: Signal variation ➠ Variation in the sample ➠ Monitoring of stability

Turbiscan: Instrument Technology and Theory

Repetition of the measurement provides: Δd : change in particle size Δ Φ : change in particle concentration

Sedimentation

Top of vial: signal decrease (clarification) Bottom of vial: signal increase (sediment)

Data analysis Sedimentation and Creaming

Creaming

Top of vial: signal increase (creaming) Bottom of vial: signal decrease (clarification)

Sedimentation Layer Quantification

A B B A B A Sample A particle migration

• Higher sedimentation thickness
• Higher phase concentration

Phase separation thickness (bottom of sample) Concentration variation (bottom of sample) Data Analysis Destabilization Kinetics

Data Analysis Flocculation and Coalescence

Size change

Entire sample: signal decrease/increase

1st 2nd 2nd Flocculation Creaming

Data Analysis Multiple Destabilization Events

Complete understanding of the destabilization and kinetic of each phenomena

One-click Stability Criteria : Turbiscan Stability Index

Sample Name TSI (8 days) Test 1 4.1 Test 2 1.5 Ref 1.1 Test 3 0.6 More stable Less stable

 One-click parameter  No additional information required  Takes in account ALL DESTABILIZATIONS  One unique number to rank & compare samples

Data Analysis Turbiscan Stability Index (TSI)

50 100 150 200 250 300 2010 2011 2012 2013 2014 2015 2016 2017 Number of publications

Publications using the

 SMLS covers a wider concentration area than DLS (17% of samples)

(B) (G) (E) (F) (D) (C) (I) (J) (L) (K) (M) (H) (N) (P) (Q) (A) (O)

Mean diameter (µm) Concentration (%v/v) Particle Refractive index

S-MLS DLS

Type of sample

Particle

Suspension

I TiO2 H SiO2 K Polystyrene G ZnO F CaCO3 E

SiO2

D Talc C TiO2 B Al2O3 A Ludox (colloidal silica) J Polystyrene

Protein

L Bovine Serum Albumin

Emulsions

P Emulsion with sunflower oil (surfactant tween 20) N Emulsion O Emulsion with sunflower oil (surfactant sodium caseinate) M

Healthcare emulsion

Foam

Q Hair foam

Hair foam (155 µm @ 60%) ZnO (13 nm) TiO2 (@ 0.001%)

Data Analysis Mean Particle Size Calculations

Stability Applications Home & Personal Care

Stability Applications Perfume Stability: Experiment Design

• A standard perfumed base is tested for stability by incorporating three different fragrances at

varying dosages.

 Quick analysis to optimize each formulation.

• Each fragrance is currently on the market in a standard emulsion formulation. Here, the same

fragrances will be tested in a new emulsion to track the stability of the new formula.

 Controls stability from formula to formula – match, mimic, and predict shelf life.

• The experiment is performed for 2 hours at 45 ºC, scanning once per minute. This allows full

destabilization profiles to be seen by the Turbiscan while no visual phase separation is seen by the naked eye.

 Extensive shelf life studies are not required (days, weeks, months).

• After the analysis, global stability (TSI) is tracked to quickly analyze the formulations as acceptable
• r non-acceptable.

 One-click analysis to understand the impact of destabilization kinetics.

• If needed, individual kinetics can be analyzed for a more in-depth understanding of the

phenomena.

 Detailed information about each formulation as it ages.

Stability Applications Perfume Stability: Results

• Data can be split into three regions in the bottom, middle, and top of the sample in order to show

specific destabilization phenomena.

 Bottom of sample: decrease in BS signal – particles migrating away from this region  Middle of sample: global change in BS signal = particle size increase  Top of sample: local decrease in BS signal – oil layer formation + coalescence

Stability Applications Perfume Stability: Results

• Utilizing the TSI function, all destabilization phenomena are derived into a single number and the

kinetics of this global function are plotted for each variable.

• Dosed at 1% and 1.75%, the lower amount of fragrance A is similar to the un-perfumed formulation,

signifying a similar stability for the two emulsions.

Stability Applications Perfume Stability: Results

• Fragrance B shows a much better overall stability (TSI = 1.6 and 1.2) than that of fragrance A (TSI =

1.1 and 4.4).

• In fact, dosing at 1.75% shows better destabilization kinetics than when the emulsion is dosed at

1%.

Stability Applications Perfume Stability: Results

• Interestingly, a 1% dosing of fragrance C increased the stability of the formulation when compared

to the un-fragranced emulsion. Dosing at 1.75% showed a clear decrease in stability.

Stability Applications Perfume Stability: Results

• Graphing the TSI values at the end of the experiment gives a better display as to the effect of the

formulation differences.

• Internally, this customer set a stability threshold of TSI = 2. Everything above that is considered a

“fail” and will not be optimized further, in favor of the alternate formulations.

Stable sample

This 2-hour experiment provides quantitative stability data and fast formulation optimization.

Stability Applications Detergent Stability

• A “heavy duty” liquid fabric detergent is monitored in order to optimize the perfume identity in the

emulsion for maximum stability.

• The experiment is performed at 45 ºC for 7 hours.
• In a similar manner as before, full destabilization profiles are captured and then analyzed with the

TSI in order to optimize the formulation without excessive visual shelf life studies.

Stability Applications Detergent Stability: Results

• Data can be split into three regions in the bottom, middle, and top of the sample in order to show

specific destabilization phenomena.

 Bottom of sample: decrease in BS signal – particles migrating away from this region  Middle of sample: no change = no flocculation or coalescence events  Top of sample: local increase in BS signal – creaming of oil layer

Stability Applications Detergent Stability: Results

• The large TSI observed in only a few hours of the original perfume provides an unstable, phase-

separated emulsion.

• Modification to an alternate perfume provides a much greater enhancement to stability.

The best additive is quickly identified and can be further optimized

Stability Applications Fabric Softener Stability

• A fabric softener formulation was

deemed unstable, but contains many components.

• Each component was tested

individually and the culprit was the encapsulated perfume that was used.

• Knowing this, the formulation can be

modified to further enhance stability. Differences are seen after 1 hour = significant time savings

Thank you! Visit us at booth #223

matt@formulactionusa.com Formulaction.com