Predicting surfactants characteristic curvature for HLD framework using shallow machine learning methods

Key Points

• Surfactant curvature is crucial for optimizing formulations, and accurate predictions can enhance product performance.
• Machine learning methods achieved significant accuracy, with a prediction error within 5% of true values for various surfactants.
• Analysis using shallow machine learning techniques demonstrated robust modeling capabilities across diverse datasets of surfactants.
• Future work may enable broader applications in formulation design, supporting industrial scaling and innovation.