The effects of surfactant concentration, adsorption, aggregation, and solution conditions on steel corrosion inhibition and associated modeling in aqueous media

• Corrosion inhibition of surfactants is evaluated by experiment and quantum calculation.
• Surface aggregation concentration and critical micelle concentration are evaluated.
• Langmuir adsorption model is modified to effectively predict corrosion inhibition.
• Model is developed to predict pure and mixed surfactants’ critical micelle concentration.
• Inhibition efficiency is well predicted for pure and mixed surfactants.

A potential model for the prediction of metal corrosion inhibition using relevant pure and mixed surfactants in salt solution has been developed and validated. This model is based on the combination of Langmuir adsorption (LA) and a newly-developed critical micelle concentration (cmc) prediction model for various pure and mixed surfactants. The collected data from benzalkonium chloride (BAC) surfactants was used for model illustration and derivation. The effects of surfactant concentration, adsorption, aggregation, and solution temperature on steel corrosion inhibition were investigated. The adsorption mechanism is discussed based on temperature, concentration, potential of zero charge, and density functional theory (DFT) calculation.

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