Abstract
Surfactants and surfactant-like amphiphilic polymers play important roles in many industrial processes (e.g., home and personal care, laundry, paints and coatings, and biopharmaceuticals). In the past two decades, significant progress has been achieved in understanding and modeling crucial surfactant properties (e.g., critical micellization concentration [CMC], cloud points, adsorption, and stabilization of colloidal particles against flocculation), but many challenges still remain. In this review, several popular data-driven, atomistic, and coarse-grained modeling approaches are described that are used to study surfactant properties. Then, specific examples of how these approaches are used for specific applications are provided. Finally, opportunities and challenges for surfactant theory and modeling are discussed.
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