Predicting the Performance of Functional Materials Composed of Polymeric Multicomponent Systems Using Artificial Intelligence-Formulations of Cleansing Foams as an Example

Cleansing foam is a common multicomponent polymeric functional material. It contains ingredients in innumerable combinations, which makes formulation optimization challenging. In this study, we used artificial intelligence (AI) with machine learning to develop a cleansing capability prediction system that considers the effects of self-assembled structures and chemical properties of ingredients. Over 500 cleansing foam samples were prepared and tested. Molecular descriptors and Hansen solubility index were used to estimate the cleansing capabilities of each formulation set. We used five machine-learning models to predict the cleansing capability. In addition, we employed an in silico formulation by generating virtual formulations and predicting their cleansing capabilities using an established AI model. The achieved accuracy was R2 = 0.770. Our observations revealed that mixtures of cosmetic ingredients exhibit complex interactions, resulting in nonlinear behavior, which adds to the complexity of predicting cleansing performance. Nevertheless, accurate chemical property descriptors, along with the aid of in silico formulations, enabled the identification of potential ingredients. We anticipate that our system will efficiently predict the chemical properties of polymer-containing blends.

Automated summary

In this study, an AI-based prediction system was developed to predict the cleansing capabilities of foam cleansers by considering the self-assembled structures and chemical properties of ingredients. The system achieved an accuracy of R2 = 0.770 by utilizing molecular descriptors and Hansen solubility index. The complex interactions between cosmetic ingredients were found to contribute to the nonlinear behavior of cleansing performance, but accurate chemical property descriptors and in silico formulations enabled the identification of potential ingredients.