Molecular dynamics simulation for hair care viscosity modulation

Overview

This solution leverages Molecular Dynamics (MD) simulations to investigate the interaction between viscosity modifiers and hair keratin, crucial for optimizing hair care formulations. By understanding these interactions at an atomistic level, the methodology aids in adjusting concentrations of compounds like glycerol and surfactants to achieve desired viscosities, enhancing product performance and consumer satisfaction.

Technical specifications

Key features:

• Utilizes MD simulations for detailed analysis of compound interactions with hair keratin.
• Applies Einstein’s and Green-Kubo methods for calculating viscosity changes.
• Focuses on common hair product compounds such as Sodium Laureth Sulfate, Cetyl Alcohol, Glycerol, Lactic Acid, and Sodium Chloride.
• Plans to develop a machine learning model for predicting system viscosities based on simulation data.

Technology readiness level

The technology is currently at TRL 3, indicating experimental proof of concept. Future validation will involve extensive testing of viscosity modifiers with keratin using MD simulations, with plans to evaluate multiple calculation methods for accuracy in predicting interactions.