Prediction of Corrosion of Advanced Materials and Fabricated Components

Anderko, Andrzej; Engelhardt, George R.; Łencka, Małgorzata M.; Jakab, M. A.; Tormoen, Garth W.; Sridhar, Narasi

doi:10.2172/916966

Cited by 13 publications

(31 citation statements)

References 98 publications

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“…Since the details of this model were described previously, 19,24 only its essential features are summarised here. The model was derived by considering the dissolution of a metal in a localised corrosion environment in the limit of repassivation.…”

Section: Extension Of Model To Mo Depletionmentioning

confidence: 99%

“…Most importantly, for the study of thermally aged alloys, the parameters of the model have been generalised in terms of alloy composition for Fe-Ni-Cr-Mo-W-N alloys. 24 This generalisation was based on experimental E rp data for 13 base (typically mill-annealed) stainless steels and nickel-based alloys, supplemented by those for Fe and Ni. The Appendix summarises the final working equations for the E rp model, defines the model parameters and provides the equations for calculating the parameters as functions of alloy composition.…”

Section: Extension Of Model To Mo Depletionmentioning

confidence: 99%

“…23 The repassivation potential model can be used as a predictive tool for alloys in multicomponent industrial environments because its parameters are expressed as functions of aqueous solution chemistry. Moreover, the E rp model parameters have been correlated with the composition of Fe-Ni-Cr-Mo-W-N alloys, 24 thus making it possible to predict the effect of compositional variations in an alloy on E rp .…”

Section: Introductionmentioning

confidence: 99%

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Localised corrosion of heat-treated alloys Part II – Predicting grain boundary microchemistry and its effect on repassivation potential

Anderko¹,

Sridhar

Tormoen

2010

Corrosion Engineering, Science and Technology

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A methodology has been developed for predicting the effect of thermal aging on the repassivation potential of austenitic alloys. The methodology combines two models, a grain boundary microchemistry model for calculating the chromium and molybdenum depletion profiles in the vicinity of grain boundaries and an electrochemical model that relates the repassivation potential to the microchemistry and environmental conditions, including temperature and solution chemistry. The grain boundary microchemistry model incorporates a thermodynamic paraequilibrium treatment of the formation of carbides and a kinetic treatment of the diffusion of Cr and Mo. With this model, experimental Cr and Mo depletion profiles can be reproduced for sensitised alloys 600, 825 and 316L. The repassivation potential model accounts for the effects of solution chemistry and temperature by considering competitive dissolution, adsorption and oxide formation processes at the interface between the metal and the occluded site solution. Using a previously developed relationship between the repassivation potential and bulk alloy composition, a procedure has been established for calculating the observable repassivation potential of thermally aged alloys by integrating the local E rp values that correspond to the alloy microchemistry in the depletion zone. The predicted repassivation potentials agree with experimental data for thermally aged alloys 600 and 825 in chloride solutions. Additionally, the model has been applied to estimate the repassivation potential of welded samples in which segregation of alloying elements is observed.

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Section: Extension Of Model To Mo Depletionmentioning

confidence: 99%

Section: Extension Of Model To Mo Depletionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Localised corrosion of heat-treated alloys Part II – Predicting grain boundary microchemistry and its effect on repassivation potential

Anderko¹,

Sridhar

Tormoen

2010

Corrosion Engineering, Science and Technology

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“…As dilution increases, more Fe and Cr from base metal will mix with weld metal, which in turn increases the breakdown potential and decreases the repassivation potential [13]. The lower repassivation potential is a more conservative parameter in designing to prevent localized corrosion since localized corrosion is highly unlikely below the repassivation potential [2,[20][21][22]. Stainless steel is more susceptible to crevice corrosion than Ni-Cu alloys in general since stainless steel usually has a relatively lower repassivation potential [8].…”

Section: Experimental Techniquesmentioning

confidence: 99%

A corrosion study of nickel–copper and nickel–copper–palladium welding filler metals

Liang¹,

Sowards²,

Frankel³

et al. 2010

Materials & Corrosion

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In an effort to reduce the release of fumes containing carcinogenic Cr 6þ during arc welding of stainless steel, Cr-free filler metals for welding of SS304 have been developed. Corrosion studies were carried out on 304L stainless steel samples welded with these Cr-free consumables. The corrosion properties of gas tungsten arc (GTA) and shielded metal arc (SMA) welds fabricated with Ni-Cu and Ni-Cu-Pd consumables were found to be comparable to those of welds fabricated with SS308L, the standard filler metal used with SS304. Although the breakdown potentials of the welds made using both welding processes were lower than that of the SS308L GTA weld, the repassivation potentials of these welds were much higher. Generally, the repassivation potential is a more conservative measure of susceptibility to localized corrosion. Accordingly, the Ni-Cu and Ni-Cu-Pd welds were more resistant to crevice corrosion than SS308L welds. The addition of a small amount of Pd improved the corrosion resistance relative to Ni-Cu welds, which is consistent with previous studies from specially-prepared button samples and bead-on-plate samples. Other corrosion studies such as creviced and uncreviced long time immersion, atmospheric exposure, and slow strain rate testing suggest that Ni-Cu-Pd filler metal can be a potential replacement for the conventional SS308L filler metal for joining SS304.

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“…The general repassivation model developed by Anderko and coworkers [52][53][54][55][56] was founded upon this view. However, the authors assumed the surface condition at repassivation to be at or near saturation.…”

mentioning

confidence: 99%

Evaluating the Critical Chemistry for Repassivation at the Corroding Surface Using Mass Transport Model-Based Artificial Pit Experiments

Srinivasan

Kelly

2016

J. Electrochem. Soc.

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One-dimensional mass transport model calculations were utilized to design experiments with stainless steel artificial pit electrodes to determine the critical concentration of cations at the corroding surface representing the transition between stable pitting and repassivation. Rapid polarization scans following salt film precipitation and consequent open circuit dilution to different surface concentrations permitted the evaluation of kinetics at various degrees of saturation. These experiments showed a distinct change in kinetics as the surface concentration decreased, thus identifying the critical pit chemistry for the onset of repassivation. Chemical modeling of oxide precipitation from solution permitted the investigation of oxide nucleation across varying surface concentration as a function of pH as the cause of repassivation. This analysis enabled the estimation of the pH at which the first oxide would precipitate in the critical pit solution chemistry, which when combined with cation hydrolysis calculations, resulted in the evaluation of the critical pH at the transition between pit stability and repassivation. A mixed potential theory-based analysis of these results was utilized to provide mechanistic support to the quantitative framework describing critical factors for pitting stability and repassivation.

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Prediction of Corrosion of Advanced Materials and Fabricated Components

Cited by 13 publications

References 98 publications

Localised corrosion of heat-treated alloys Part II – Predicting grain boundary microchemistry and its effect on repassivation potential

Localised corrosion of heat-treated alloys Part II – Predicting grain boundary microchemistry and its effect on repassivation potential

A corrosion study of nickel–copper and nickel–copper–palladium welding filler metals

Evaluating the Critical Chemistry for Repassivation at the Corroding Surface Using Mass Transport Model-Based Artificial Pit Experiments

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