Experimental Investigation and Modeling of the Performance of Pure and Mixed Surfactant Inhibitors: Aggregation, Adsorption, and Corrosion Inhibition on Steel Pipe in Aqueous Phase
Source abstract
Abstract
Two models for the prediction of corrosion inhibition efficiency of various pure surfactant and mixed surfactants in salt-containing solution are developed, compared, and validated. The two prediction models are based on a modified Langmuir adsorption (MLA) sub-model and a modified Quantitative Structure Activity Relation (MQSAR) sub-model. Each of the sub-models is combined with the critical micelle concentration (cmc) prediction sub-model to create an overall corrosion inhibition prediction model separately. Each of the created overall models is very robust in predicting corrosion inhibition of various surfactants in a variety of testing systems. The model derivation is mainly based on the mixed homologous benzalkonium chlorides in NaCl-containing aqueous solution and further validated using various testing systems of surfactants. The developed corrosion inhibition prediction models provide potential methods to evaluate the effectiveness of various surfactants in corrosion inhibition under various testing solution conditions. In addition, the adsorption and inhibition mechanisms of surfactants in the corresponding testing system were investigated.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Corrosion Behavior and Inhibition · Concrete Corrosion and Durability · Structural Integrity and Reliability Analysis
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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