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.