Molecular Modeling of Surfactant Micellization Using Solvent-Accessible Surface Area

Area of Science:

• Computational chemistry
• Physical chemistry
• Materials science

Background:

• Surfactant self-assembly is crucial for many industrial applications.
• Accurate prediction of surfactant behavior requires robust simulation models.
• Existing models often struggle to simultaneously capture critical micelle concentration (cmc) and aggregation numbers.

Purpose of the Study:

• To develop a novel implicit solvent simulation model for surfactant self-assembly.
• To accurately predict critical micelle concentrations (cmc) and micellar aggregation numbers.
• To provide a generalizable model for diverse amphiphilic systems.

Main Methods:

• Developed a new implicit solvent model based on solvent-accessible surface area (SASA) changes.
• Employed histogram-reweighting grand canonical Monte Carlo simulations.
• Calibrated the model using a single phenomenological surface tension parameter (γSASA).

Main Results:

• The SASA-based model successfully matched experimental cmc and aggregation numbers for poly(oxyethylene) monoalkyl ether (CmEn) surfactants.
• The model demonstrated excellent transferability across a range of alkyl (m=6-12) and poly(oxyethylene) (n=1-9) chain lengths.
• The model accurately predicted experimental data with a single adjustable parameter.

Conclusions:

• The proposed SASA-based implicit solvent model offers a powerful and accurate method for simulating surfactant self-assembly.
• The model's generalizability allows for its application to more complex systems, including branched surfactants and hydrocarbon mixtures.
• This work advances the computational study of amphiphilic systems, bridging simulation and experimental observations.