Computer Simulation evidence of the molecular mechanism of makeup removal using cleansing foam
～Is an “in-silico formulator” superior to a human formulator?～
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Presented by: Takahiro Yokoyama
Introduction
Cleansing foam is used to wash excess sebum and dirt from the skin, while a makeup remover is used, as implied by its name, to remove make-up cosmetics. Recently, in the interest of lessening application time and environmental impact, there is an increasing push toward combining cleansing foam and makeup remover into one product.
Solvent-based cleansing agents such as makeup remover oil have excellent removal strength, since oil is the main component, but there remain issues such as high environmental loads and material costs, in addition to the user feeling residual oiliness after a rinse. By contrast, surfactant-type cleansing agents such as cleansing foams have excellent rinsing properties but weak removability, since they are water-based. In this context, we aimed to improve the cleansing performance of cleansing foams. However, cleansing foams are typically composed of many ingredients, making it difficult to find the best formulation from an infinite number of combinations.
Simulations were used to understand the essential molecular mechanism of the cleansing process. Molecular simulations provide visualizations of the assembly structure and the cleansing process at nano spatial-temporal scales, which are difficult to observe experimentally. To clarify the molecular mechanism of cleansing will help reduce the high cost of formulation design; consequently, we performed investigations by reproducing various formulations using molecular simulations and comparing their structures and cleansing capability. Our study presents a guide to manipulating the cleansing performance of multi-surfactant solutions with regard to cosmetics.
Methods
Molecular simulation: The DPD method, one of the course-grained molecular techniques was used to reproduce the molecular structure of a multicomponent system containing various surfactants and polyols. In this method, a group of atoms is coarse-grained as a virtual particle which makes it possible to calculate larger systems, which have been difficult to apply due to computer limitations. Assuming each molecule moves according to Newton's laws of motion, the self-assembly structure and cleansing process can be directly observed.
Analysis: For the reproduced equilibrium structure, the surface tension, contact area of the structure/water interface, and dispersion of each component were calculated. The contribution of each molecule to cleansing performance was investigated by comparing these values with the corresponding experimental values.
Experimental data: Test samples were composed of ionic surfactants, non-ionic surfactants, polyols, and water, which were prepared by mixing thoroughly with heating and stirring. The cleansing capability was evaluated by obtaining the waterproof eyeliner-pencil residual ratio using a colorimeter.
Results and Discussion
Many self-assembled morphologies were obtained, depending on the formulation. These assemblies included vesicles, cylindrical micelles, lamellar structures, and high-order network structures. The surface tension, contact area, and dispersion were calculated for the equilibrium structures of all formulations, and the values increased as the structures shifted from simple structures such as micelles or vesicles to complex higher-order structures. To quantitatively link the cleansing performance with the assembled structure, these values were compared to the corresponding values obtained experimentally. It was found that with increasing surface tension and dispersion, cleansing capability also increased. This indicated that cleansing performance were related to self-assembly structures through characteristics such as dispersion and surface tension.
Next, we investigated the characteristics of formulations for which higher-order structures formed, in contrast with simple structures. We found that complex higher-order structures tended to form when the ratio of weakly hydrophilic polyols and non-ionic surfactants to anionic surfactants increased, the latter showing strong hydrophobic interactions in an aqueous solution. Furthermore, it was discovered that certain molecules, such as eicosaglycerol hexacaprylate, are captured inside the structure, increasing the complexity of the structure. Thus, we found that the addition of specific polyols and non-ionic surfactants is an effective method for achieving high cleansing performance.
Conclusion
In conclusion, we investigated the mechanism of cleansing by simulating the self-assembly structures of multicomponent systems. It was quantitatively shown that the self-assembly structures formed inside the aqueous solution were linked to the cleansing capability. Furthermore, higher order structures play an important role in cleansing performance, and weakly hydrophilic additives such as polyols and non-ionic surfactants can assist in their formation. Our study hopes to reduce the huge cost of iterative trials of formulations and is promising in establishing novel in-silico formulations.
Cleansing foam is used to wash excess sebum and dirt from the skin, while a makeup remover is used, as implied by its name, to remove make-up cosmetics. Recently, in the interest of lessening application time and environmental impact, there is an increasing push toward combining cleansing foam and makeup remover into one product.
Solvent-based cleansing agents such as makeup remover oil have excellent removal strength, since oil is the main component, but there remain issues such as high environmental loads and material costs, in addition to the user feeling residual oiliness after a rinse. By contrast, surfactant-type cleansing agents such as cleansing foams have excellent rinsing properties but weak removability, since they are water-based. In this context, we aimed to improve the cleansing performance of cleansing foams. However, cleansing foams are typically composed of many ingredients, making it difficult to find the best formulation from an infinite number of combinations.
Simulations were used to understand the essential molecular mechanism of the cleansing process. Molecular simulations provide visualizations of the assembly structure and the cleansing process at nano spatial-temporal scales, which are difficult to observe experimentally. To clarify the molecular mechanism of cleansing will help reduce the high cost of formulation design; consequently, we performed investigations by reproducing various formulations using molecular simulations and comparing their structures and cleansing capability. Our study presents a guide to manipulating the cleansing performance of multi-surfactant solutions with regard to cosmetics.
Methods
Molecular simulation: The DPD method, one of the course-grained molecular techniques was used to reproduce the molecular structure of a multicomponent system containing various surfactants and polyols. In this method, a group of atoms is coarse-grained as a virtual particle which makes it possible to calculate larger systems, which have been difficult to apply due to computer limitations. Assuming each molecule moves according to Newton's laws of motion, the self-assembly structure and cleansing process can be directly observed.
Analysis: For the reproduced equilibrium structure, the surface tension, contact area of the structure/water interface, and dispersion of each component were calculated. The contribution of each molecule to cleansing performance was investigated by comparing these values with the corresponding experimental values.
Experimental data: Test samples were composed of ionic surfactants, non-ionic surfactants, polyols, and water, which were prepared by mixing thoroughly with heating and stirring. The cleansing capability was evaluated by obtaining the waterproof eyeliner-pencil residual ratio using a colorimeter.
Results and Discussion
Many self-assembled morphologies were obtained, depending on the formulation. These assemblies included vesicles, cylindrical micelles, lamellar structures, and high-order network structures. The surface tension, contact area, and dispersion were calculated for the equilibrium structures of all formulations, and the values increased as the structures shifted from simple structures such as micelles or vesicles to complex higher-order structures. To quantitatively link the cleansing performance with the assembled structure, these values were compared to the corresponding values obtained experimentally. It was found that with increasing surface tension and dispersion, cleansing capability also increased. This indicated that cleansing performance were related to self-assembly structures through characteristics such as dispersion and surface tension.
Next, we investigated the characteristics of formulations for which higher-order structures formed, in contrast with simple structures. We found that complex higher-order structures tended to form when the ratio of weakly hydrophilic polyols and non-ionic surfactants to anionic surfactants increased, the latter showing strong hydrophobic interactions in an aqueous solution. Furthermore, it was discovered that certain molecules, such as eicosaglycerol hexacaprylate, are captured inside the structure, increasing the complexity of the structure. Thus, we found that the addition of specific polyols and non-ionic surfactants is an effective method for achieving high cleansing performance.
Conclusion
In conclusion, we investigated the mechanism of cleansing by simulating the self-assembly structures of multicomponent systems. It was quantitatively shown that the self-assembly structures formed inside the aqueous solution were linked to the cleansing capability. Furthermore, higher order structures play an important role in cleansing performance, and weakly hydrophilic additives such as polyols and non-ionic surfactants can assist in their formation. Our study hopes to reduce the huge cost of iterative trials of formulations and is promising in establishing novel in-silico formulations.