A Proposal for the Application of Failure Assessment Diagrams to Subcritical Hydrogen Induced Cracking Propagation Processes

In this work, an optimization proposal for a model based on the definition of regions for crack propagation by means of the micromechanical comparison by SEM images and its application to failure assessment diagrams (FADs) is presented. It consists in three approaches. (1) The definition of the crack propagation initiation in the elastic‐plastic range. (2) A slight modification of the zones in which the FAD is divided for hydrogen induced cracking (HIC) conditions. (3) The introduction of a simple correction for the definition of the Kr coordinate of the FAD to take into account the fracture toughness reduction caused by an aggressive environment, instead of using a fracture parameter obtained from a test in air. For the experimental work, four medium and high strength steels exposed to a cathodic charge and cathodic protection environments were employed, studying two different loading rates in each case, and testing C(T) samples under slow rates in the environment. The study was completed with a subsequent fractographic analysis by SEM. A good degree of fulfilment was appreciated in both materials and environmental conditions, showing the validity of the predictions supplied by the FAD optimization model proposal, which constitutes an advance in the accuracy of the FAD predictive model.This research was funded by CECA, grant number 7210‐PE/110, by The Spanish Ministry of Economy and Competitivity, grant number MAT2014‐58738‐C3‐3‐R, and by the post‐doctoral contracts program of the University of Cantabria, budgetary application 62.0000.64251

Passive Behavior and Passivity Breakdown of AISI 304 in LiBr Solutions through Scanning Electrochemical Microscopy

The passive behavior and passivity breakdown of AISI 304 stainless steel in LiBr solutions has been investigated by means of scanning electrochemical microscopy (SECM). The sample generation - tip collection (SG-TC) mode was used to operate the SECM and the tip potential was biased to detect the electroactive species. The evolution of the current at the ultramicroelectrode tip with the applied potential within the passive range was followed at different LiBr concentrations. Results show that the absolute value of the current at the tip increases with the applied potential. Additionally, SECM was also used to detect stable pits formed on the stainless steel surface in a 0.2 M LiBr solution. The results show clear evidence of the presence of high amounts of other reducible species (metal cations) apart from oxygen. Also, the dish-shape morphology of the pits observed using Confocal Laser Scanning Microscopy will be discussed in relation to the kinetics of the reactions observed using SECM. (c) 2014 The Electrochemical Society. All rights reserved.The authors would like to express their gratitude to the Generalitat Valenciana for its help in the SECM acquisition (PPC/2011/013) and in the CLSM acquisition (MY08/ISIRM/S/100) and to Dr. Asuncion Jaime for her translation assistance.Fernández Domene, RM.; Sánchez Tovar, R.; García Antón, J. (2014). Passive Behavior and Passivity Breakdown of AISI 304 in LiBr Solutions through Scanning Electrochemical Microscopy. Journal of The Electrochemical Society. 161(12):565-572. https://doi.org/10.1149/2.1051412jesS56557216112Cobb Harold M. (Ed.), Steel Products Manual: Stainless Steels, Iron & Steel Society, 1999.Schweitzer P. A. , Corrosion Engineering Handbook: Fundamentals of Metallic Corrosion, CRC Press, Boca Ratón, FL., 2007.Hakiki, N. 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Characterization of pitting corrosion of stainless steel using artificial neural networks

In this work, different classification models were proposed to predict the pitting corrosion status of AISI 316L stainless steel according to the environmental conditions and the breakdown potential values. In order to study the pitting corrosion status of this material, polarization tests were undertaken in different environmental conditions: varying chloride ion concentration, pH and temperature. Two different techniques were presented: k nearest neighbor (KNN) and Artificial Neural Networks (ANNs). The parameters for the classifiers were set based on a compromise between recall and precision using bootstrap as validation technique. The ROC space was presented to compare the classification performance of the different models. In this frame, Bayesian regularized neural network model proved to be the most promising technique to determine the pitting corrosion status of 316L stainless steel without resorting to optical metallographic studies

Effect of alloying elements on the electronic properties of thin passive films formed on carbon steel, ferritic and austenitic stainless steels in a highly concentrated LiBr solution

The influence of alloying elements on the electrochemical and semiconducting properties of thin passive films formed on several steels (carbon steel, ferritic and austenitic stainless steels) has been studied in a highly concentrated lithium bromide (LiBr) solution at 25 °C, by means of potentiodynamic tests and Mott-Schottky analysis. The addition of Cr to carbon steel promoted the formation of a p-type semiconducting region in the passive film. A high Ni content modified the electronic behaviour of highly alloyed austenitic stainless steels. Mo did not modify the electronic structure of the passive films, but reduced the concentration of defects