Electrochemical measurement, modeling, and prediction of corrosion inhibition efficiency of ternary mixtures of homologous surfactants in salt solution

Zhu, Yakun; Free, Michael L.; Yi, Gaosong

doi:10.1016/j.corsci.2015.05.050

Cited by 67 publications

(69 citation statements)

References 53 publications

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“…Therefore, the monolayer is much more effective with respect to corrosion protection and the formation of bilayers/multilayers or micelles do not contribute much to corrosion inhibition. b IE (%) calculated from LPR; c&d derived from the cathodic branch and β c due to lack of sensible linearity in the anodic branch in potentiodynamic scans as seen in Figure 4 [28].…”

Section: Potentiodynamic Scan and Linear Polarization Resistance Measmentioning

confidence: 99%

“…Corrosion inhibition assumes that the steel electrode corrodes uniformly and that the corrosion current density in the absence of surfactants, i corr,0 , is usually represented by the total number of surface sites available for corrosion, whereas the corrosion current density in the presence of low concentration of inhibitor (usually lower than the cmc or sac), i corr , is represented by the number of uncovered surface sites remaining after limited surfactant adsorption [28][29][30]. Thus, the surface coverage θ is equal to the fraction of surface sites covered by surfactant adsorption relative to the total surface sites and can be given by the expression below with the assumption that surfactant adsorption does not affect the metal dissolution kinetics of the surface which is not covered by the surfactant [31]: corr corr,0 corr corr,0 corr,0…”

Section: Traditional Modeling Backgroundmentioning

confidence: 99%

“…The associated polarization curves are presented in Figure 3. Tafel slopes were estimated from these curves to calculate corrosion current density using the Tafel slope method [28]. The corrosion inhibition efficiency, IE (%), was calculated using Equation (1) [28].…”

Section: Potentiodynamic Scan and Linear Polarization Resistance Measmentioning

confidence: 99%

See 2 more Smart Citations

Mixed-surfactant aggregation, adsorption, and associated steel corrosion inhibition in salt solution

Zhu¹,

Free²

2015

Int. J. Corros. Scale Inhib.

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The corrosion inhibition efficiency of mixtures of three homologous benzalkonium chlorides (BAC) surfactants was investigated using electrochemical measurements and modeling. The surface aggregation concentration (sac) and critical micelle concentration (cmc) of surfactant are useful to evaluate inhibition efficiency. A new cmc prediction model for ternary mixed homologous surfactants of interest has been developed. The model is applicable over a wide concentration range of dissolved salt in solution. The combination of the modified Langmuir adsorption model and the cmc prediction model provides a potential method for inhibition efficiency prediction of various mixed homologous surfactant systems at various dissolved salt concentrations.

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Section: Potentiodynamic Scan and Linear Polarization Resistance Measmentioning

confidence: 99%

Section: Traditional Modeling Backgroundmentioning

confidence: 99%

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Mixed-surfactant aggregation, adsorption, and associated steel corrosion inhibition in salt solution

Zhu¹,

Free²

2015

Int. J. Corros. Scale Inhib.

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“…The difference in E corr in the absence and presence of surfactant indicates that the steel surface was covered and protected by the inhibitor adsorption. According to Riggs Jr [27], it is feasible to classify one inhibitor as anodic type or catholic type if the presence of inhibitor shifts E corr at least +85 mV or -85 mV, respectively, relative to E corr in the absence of inhibitor. However, the positive shift of E corr of the investigated System I at the highest concentration of 360 μm is only around 85 mV suggesting that both the dissolution of iron at the anode and the hydrogen evolution at the cathode were affected.…”

Section: Polymer Sceiences Issn 2471-9935mentioning

confidence: 99%

Effects of Surfactant Aggregation and Adsorption on Steel Corrosion Inhibition in Salt Solution

Zhu

FreeM²

2016

Polym Sci

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“…However, it usually can be calculated from well-developed prediction models that have been introduced C703 previously. 34,35 The model outputs include monomer concentrations at equilibrium in oil and in water, the apparent cmc value of mixtures in water-oil environments, and molar fraction of each mixed surfactant component in mixed micelles. The surfactant distribution model, which is a combination of a partitioning sub-model, a partitioning coefficient calculation method, and the developed cmc prediction sub-model based on previous work, 34,35 provides a potential tool to evaluate the partitioning of surfactant mixtures in water-oil environments.…”

mentioning

confidence: 99%

Experimental Investigation and Modeling of the Performance of Pure and Mixed Surfactant Inhibitors: Partitioning and Distribution in Water-Oil Environments

Zhu

Free

2015

J. Electrochem. Soc.

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A critical model of water-oil surfactant distribution has been developed and validated for the evaluation of mixed surfactant partitioning and distribution in water-oil environments. The surfactant distribution model, which is a combination of surfactant partitioning sub-model, partitioning coefficient calculation method, and a developed critical micelle concentration (cmc) prediction sub-model based on previous work, provides a very powerful tool to evaluate the partitioning of mixed surfactants in water-oil environments. Different methods to calculate partitioning coefficients are introduced, which includes transfer free energy method and group contribution method. The partitioning data from model prediction and from experiment agree very well. The mixed micelles start to form in water-oil environments only after the apparent cmc is reached during partitioning. The selective partitioning of one particular surfactant in mixed surfactants can be explained by its apparent cmc which is interpreted as one characteristic of the hydrophobicity/hydrophilicity of that surfactant in water-oil environments. It is believed that the partitioning and distribution of non-homologous mixed surfactants in oil-water environments are evaluated theoretically and experimentally for the first time. The effect of partitioning on corrosion inhibition of mixed surfactants was initially evaluated by modified Langmuir adsorption and by electrochemical measurements. The corrosion inhibition efficiency from model prediction and from experimental measurements is comparable. The use of surfactant inhibitors has received extensive attention in the oil and gas industry for corrosion inhibition of production and transportation pipes (metallic materials, such as steel and copper) in a way that surfactant molecules usually adsorb on steel surface and form a protective film which acts as a barrier to prevent corrosive media penetration and attack. [1][2][3][4] Compared to the production and use of pure surfactants, surfactant mixtures are well known due to the superior physicochemical properties and capabilities in efficient solubilization, adsorption, suspension, and transportation. [5][6][7][8] The solutions of surfactant mixtures can often be conveniently tuned to achieve desired properties by adjusting the mixed surfactant types and molar ratios. More surface-active and expensive surfactants are often mixed with less surface-active and cheaper surfactants to reduce cost.9,10 Natural mixtures of surfactants are sometimes used to avoid the investment in separation processes. However, further studies are required in order to optimize inhibition efficiency of surfactant mixtures and minimize environmental impact.Surfactant molecules have hydrophilic and hydrophobic sections, 7,11,12 which are critical to the adsorption on metal surface and associated corrosion inhibition.2-4 The hydrophilic functional group of surfactant molecules strongly prefers interaction with polar entities such as metals, which is helpful in corrosion inhibition. The hydroph...

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Electrochemical measurement, modeling, and prediction of corrosion inhibition efficiency of ternary mixtures of homologous surfactants in salt solution

Cited by 67 publications

References 53 publications

Mixed-surfactant aggregation, adsorption, and associated steel corrosion inhibition in salt solution

Mixed-surfactant aggregation, adsorption, and associated steel corrosion inhibition in salt solution

Effects of Surfactant Aggregation and Adsorption on Steel Corrosion Inhibition in Salt Solution

Experimental Investigation and Modeling of the Performance of Pure and Mixed Surfactant Inhibitors: Partitioning and Distribution in Water-Oil Environments

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