The influence of crystallographic orientation distribution on 316LVM stainless steel pitting behavior

Shahryari, Arash; Szpunar, Jerzy A.; Omanovic, Sasha

doi:10.1016/j.corsci.2008.12.019

Cited by 115 publications

(75 citation statements)

References 27 publications

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“…It is reasonable to suppose that the presence of the orientation <100> in the shear texture is at the origin of the improvement of the pitting resistance in ferritic steels which has higher atomic density intrinsic of the FCC systems (ferrite) 15,[32][33] . Previous studies 15,34 showed that the lower susceptibility to pits generation is related with increasing atomic density planes of the FCC system, this susceptibility decreasing in the following order: 110 > 100 > 111. The crystallographic planes with a high number of nearest neighbour atoms requires a higher total energy for the breaking of the bonds and the subsequent dissolution of atoms 35 .…”

Section: Influence Of the Crystallographic Texture On The Corrosion Rmentioning

confidence: 99%

“…The pitting potential increases at 3.6 mm and decreases at the centre of the sample (2 mm), i.e., the corrosion resistance is reduced at the centre. Figure 7 shows the influence of the crystallographic texture on the pitting potential, because the crystallographic texture changes throughout the thickness of steel in the same way as the pitting potential, and demonstrating that the pitting phenomenon has an slightly anisotropic behaviour [11][12][13][14][15] . This anisotropic behaviour occurs because carbon segregation 22 is more intense in the centre of the slab in non-stabilised steel.…”

Section: Influence Of the Crystallographic Texture On The Corrosion Rmentioning

confidence: 99%

“…Some early studies [11][12] analysed the influence of structural texture of carbon, low-alloyed and high alloyed steel rods in the anisotropy of corrosion resistance and showed a strong dependence by the orientation of metal fibres, and recent studies reinforce this fact: the influence of fibre orientations on corrosion 13,14 . More recently, it has been concluded that the orientations <111> and <110> show a better corrosion and pitting resistance because of their high atomic density, and conversely, one expects to find worse corrosion and pitting resistance associated with orientations showing a lower atomic density [10][11][12][13][14][15][16] . It was also concluded 17 that the crystallographic texture is the main cause of the anisotropy of electrochemical corrosion in hot rolled rods.…”

Section: Introductionmentioning

confidence: 99%

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The Influence of Crystallographic Texture and Niobium Stabilisation on the Corrosion Resistance of Ferritic Stainless Steel

2017

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The objective of this work is to investigate the influence of the crystallographic texture on the corrosion resistance of 16% Cr ferritic stainless steel. Samples of ASTM S43000 ferritic stainless steel, both niobium-stabilised and non-stabilised, were used. The samples were subjected to crystallographic characterisation (EBSD) and analysed using an inverse pole figure (IPF) and a crystalline orientation distribution function (CODF). The samples also underwent anodic potentiodynamic polarisation tests (deaeration by high-purity argon gas) in 3.56% NaCl and 1N H 2 SO 4 solutions, and the surface was examined by SEM after the tests. The results showed a clear influence of the crystallographic texture on the corrosion resistance. The niobium decreases the amount of the preferred orientation and thus the influence of the texture on the corrosion resistance, although the corrosion resistance of the stainless steel is increased as niobium carbides are formed.

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Section: Influence Of the Crystallographic Texture On The Corrosion Rmentioning

confidence: 99%

Section: Influence Of the Crystallographic Texture On The Corrosion Rmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The Influence of Crystallographic Texture and Niobium Stabilisation on the Corrosion Resistance of Ferritic Stainless Steel

2017

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“…Several studies suggested that crystallographic orientations greatly affect the propagation rates and morphology of the corroding pits. [55][56][57] This dependence is usually attributed to factors such as close packing of crystal planes, reaction rate variation along different plane orientations and density of crystalline defects on micro scale. Here, we demonstrate that this PF model can be a good tool to study this phenomenon in detail.…”

Section: D Pf Modelmentioning

confidence: 99%

Phase-field model of pitting corrosion kinetics in metallic materials

Ansari

Xiao

et al. 2018

npj Comput Mater

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Pitting corrosion is one of the most destructive forms of corrosion that can lead to catastrophic failure of structures. This study presents a thermodynamically consistent phase field model for the quantitative prediction of the pitting corrosion kinetics in metallic materials. An order parameter is introduced to represent the local physical state of the metal within a metal-electrolyte system. The free energy of the system is described in terms of its metal ion concentration and the order parameter. Both the ion transport in the electrolyte and the electrochemical reactions at the electrolyte/metal interface are explicitly taken into consideration. The temporal evolution of ion concentration profile and the order parameter field is driven by the reduction in the total free energy of the system and is obtained by numerically solving the governing equations. A calibration study is performed to couple the kinetic interface parameter with the corrosion current density to obtain a direct relationship between overpotential and the kinetic interface parameter. The phase field model is validated against the experimental results, and several examples are presented for applications of the phase-field model to understand the corrosion behavior of closely located pits, stressed material, ceramic particles-reinforced steel, and their crystallographic orientation dependence. INTRODUCTIONCorrosion is the gradual destruction of materials (usually metallic materials) via chemical and/or electrochemical reaction with their environment. It costs about 3.1% of the gross domestic product (GDP) in the United States, which is much more than the cost of all natural disasters combined. Localized corrosion, such as pitting corrosion, is one of the most destructive forms of corrosion; it leads to the catastrophic failure of structures and raises both human safety and financial concerns. 1-3 Pitting corrosion of stainless steel usually occurs in two different stages: (1) pit initiation from passive film breakage 4-6 and (2) pit growth. 2,3,[7][8][9][10][11][12] In this study, we focused on the development of a phase-field modeling capability to study pit growth by considering both anodic and cathodic reactions.In the past few decades, great efforts have been made to develop numerical models for pitting corrosion. The moving interface and the electrical double layer at the metal/electrolyte interface are the two challenging problems faced by most of these numerical models. These numerical models can be divided according to the method in which a moving interface is incorporated in their models. Several steady state 9,10,13-18 and transient state 19-28 models have been developed over the years that did not allow for changes in the shape and dimensions of the pits/crevices as corrosion proceeds.Recent advances in numerical techniques, such as the finite element method, the finite volume method, the arbitrary Lagrangian-Eulerian method, the mesh-free method, and the level set method have encouraged researchers to model the evolving morphology...

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“…It should be noted that crystallographic texture of steels can also affect their corrosion resistance. Particularly, it was shown that the pitting corrosion susceptibility of the grains of 316LVM stainless steel is dependent on the crystallographic planes [232]. The planar orientation {111} and {100} parallel to the surface had the highest resistance to pitting corrosion, and a lower pitting resistance was expected for the crystallographic planes with lower atomic density.…”

Section: Corrosion Resistancementioning

confidence: 99%

Multifunctional Properties of Bulk Nanostructured Metallic Materials

Sabirov

Enikeev

Murashkin

et al. 2015

Bulk Nanostructured Materials With Multifunctional Properties

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This chapter focuses on multifunctional properties of bulk nanostructured metallic materials and structure-properties relationship therein. The most important structural factors affecting mechanical, physical, and chemical properties of the nanomaterials are discussed, and the strategies to their further improvement are outlined. Special attention is paid to nanostructural design for simultaneous improvement of mutually exclusive properties. Superstrength and Enhanced Mechanical PropertiesAlthough the mechanical and functional properties of all polycrystalline metallic materials are determined by several factors, the grain size of the material generally plays the most significant and often a dominant role. Thus, the strength of different polycrystalline materials is related to the grain size, d, through the Hall-Petch equation which states that the yield stress, σ y , is given bywhere σ o is termed the friction stress and k y the Hall-Petch constant [1,2]. It follows from Eq. 3.1 that the strength increases with a reduction in the grain size and this has led to an ever-increasing interest in fabricating materials with extremely small grain sizes. The fabrication of bulk samples and billets using equal channel angular pressing (ECAP), high pressure torsion (HPT), and other severe plastic deformation (SPD) techniques was a crucial first step in initiating investigations into the properties of bulk nanomaterials because the use of SPD processing permitted, and subsequently fully supported, a series of systematic studies using various nanostructured metallic materials including commercial alloys [3][4][5][6][7][8]

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The influence of crystallographic orientation distribution on 316LVM stainless steel pitting behavior

Cited by 115 publications

References 27 publications

The Influence of Crystallographic Texture and Niobium Stabilisation on the Corrosion Resistance of Ferritic Stainless Steel

The Influence of Crystallographic Texture and Niobium Stabilisation on the Corrosion Resistance of Ferritic Stainless Steel

Phase-field model of pitting corrosion kinetics in metallic materials

Multifunctional Properties of Bulk Nanostructured Metallic Materials

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