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Uniform Corrosion and General Dissolution of Aluminum Alloys

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Uniform Corrosion and General Dissolution of Aluminum Alloys Uniform Corrosion and General Dissolution of Aluminum Alloys 2024-T3, 6061-T6, and 7075-T6 DISSERTATION Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University By I-Wen Huang Graduate Program in Materials Science and Engineering The Ohio State University 2016 Dissertation Committee: Prof. Rudolph G. Buchheit, Advisor Prof. Gerald S. Frankel Prof. Jenifer S. Locke Prof. Christopher Taylor Copyright by I-Wen Huang 2016 Abstract Uniform corrosion and general dissolution of aluminum alloys was not as well-studied in the past, although it was known for causing significant amount of weight loss. This work comprises four chapters to understand uniform corrosion of aluminum alloys 2024-T3, 6061-T6, and 7075-T6. A preliminary weight loss experiment was performed for distinguishing corrosion induced weight loss attributed to uniform corrosion and pitting corrosion. The result suggested that uniform corrosion generated a greater mass loss than pitting corrosion. First, to understand uniform corrosion mechanism and kinetics in different environments, a series of static immersion tests in NaCl solutions were performed to provide quantitative measurement of uniform corrosion. Thereafter, uniform corrosion development as a function of temperature, pH, Cl−, and time was investigated to understand the influence of environmental factors. Faster uniform corrosion rate has been found at lower temperature (20 and 40°C) than at higher temperature (60 and 80°C) due to accelerated corrosion product formation at high temperatures inhibiting corrosion reactions. Electrochemical tests including along with scanning electron microscopy (SEM) were utilized to study the temperature effect. Second, in order to further understand the uniform corrosion influence on pit growth kinetics, a long term exposures for 180 days in both immersion and ASTM-B117 test were performed. Uniform corrosion induced surface recession was found to have limited impact on pit geometry regardless of exposure methods. It was also found that the competition for limited cathodic current from uniform corrosion the primary rate limiting ii factor for pit growth. Very large pits were found after uniform corrosion growth reached a plateau due to corrosion product coverage. Also, optical microscopy and focused ion beam (FIB) imaging has provided more insights of distinctive pitting geometry and subsurface damages found from immersion samples and B117 samples. Although uniform corrosion was studied in various electrolytes, the pH impact was still difficult to discern due to ongoing cathodic reactions that changed electrolyte pH with time. Therefore, buffered pH electrolytes with pH values of 3, 5, 8, and 10 were prepared static immersion tests. Electrochemical experiments were performed in each buffered pH conditions for understanding corrosion mechanisms. Uniform corrosion was found exhibiting higher corrosion rate in buffered acidic and alkaline electrolytes due to pH- and temperature-dependent corrosion product precipitation. Observations were supported by electrochemical, SEM, and EDS observations. Due to the complexity of corrosion data, a reliable corrosion prediction based on empirical observations could be challenging. Artificial neural network (ANN) modeling was used for corrosion data pattern recognition by mimicking human neural network systems. Predictive models were developed based on corrosion data acquired in this study. The model was adaptable through iteratively update its prediction by error minimization during the training phase. Trained ANN model can predict uniform corrosion successfully. In addition to ANN, fuzzy curve analysis was utilized to rank the influence of each input (temperature, pH, Cl−, and time). For example, temperature and pH were found to be the most influential parameters to uniform corrosion. This information can provide feedback for ANN improvement, also known as “data pruning”. iii Dedication This document is dedicated to my beloved family and Erin. iv Acknowledgments I am immensely benefited being part of Fontana Corrosion Center (FCC). First of all, I would like to thank my advisor Dr. Rudy Buchheit for this kind financial support and patient guidance throught the course of my Ph.D. His encouragement and openness has provided me motivation and time to pursue this degree in corrosion. I would also like to express my gratitude toward Dr. Jerry Frankel, the best teacher in the field of corrosion, for granting me this opportunity as a part of FCC. I would also like to acknowledge Dr. Jenifer Locke and Dr. Christopher Taylor for being my examination committee and for the time and advices have kindly provided. I would like to thank Dr. Belinda Hurley for her helpful discussion and effort on turning my work into scientific publications. I wish to thank the Department of Defense (DoD) Technical Corrosion Collaboration (TCC) and the DoD Corrosion Policy and Oversight Office for the financial support. During the course of my Ph.D., I received immense help form the member of FCC. In particular I would like to thank Dr. Yuehlien Lee, Dr. Liu Cao, Dr. Xiaoji Li, Dr. Zhicao Feng, Dr. Jichao Li, Dr. Xiaolei Guo, Dr. Shanshan Wang, Dr. Guangyi Liu, Dr. Omar Lopez-Garrity, Dr. Meng Lopez-Garrity, Dr. Brendy R. Troconis, Dr. Jinwook Seong, Dr. Santiago Fajardo, Dr. Ju Kang, Chris Putnam, Sara Cantonwine, Jiheon Jun, Weijie Mai, Angie Huggins, Xi Wang, Aline D avila Gabbardo, Kerrie Holguin, Benjamin Hanna, Jermain Onye, Dadi Zhang, Anup M. Panindre, Kuo-Hsiang Chang and all past and present FCC members for advice and assistance in this work. v Vita B.S. Materials Science and Engineering, 2007 National Cheng Kung University, Taiwan M.S. Materials Science and Engineering, 2010 Stony Brook University, Stony Brook, NY Ph.D. Materials Science and Engineering 2011 to present The Ohio State University, Columbus, OH Publications 1. I.-W. Huang, R. Buchheit, ECS Trans. 66 97-107 (2015). 2. I.-W. Huang, B. L. Hurley, F. Yang, and R. Buchheit, Electrochim. Acta. 199 242-253 (2016). 3. S.-S. Wang, I.-W. Huang, L. Yang, J.-T. Jiang, J.-F. Chen, S.-L. Dai, D. N. Seidman, G. S. Frankel, and L. Zhen, J. Electrochem. Soc. 162 (4) C150-C160, (2015). vi Fields of Study Major Field: Materials Science and Engineering vii Table of Contents Abstract .............................................................................................................................. ii Dedication ......................................................................................................................... iv Acknowledgments ............................................................................................................. v Vita .................................................................................................................................... vi Publications ...................................................................................................................... vi Fields of Study ................................................................................................................. vii Table of Contents ........................................................................................................... viii List of Tables .................................................................................................................. xiii List of Figures .................................................................................................................. xv Introduction ......................................................................................................................... 1 1.1 References ............................................................................................................ 4 Chapter 2 Literature Review.......................................................................................... 5 2.1 Introduction .......................................................................................................... 5 2.2 Uniform and Localized Corrosion of Aluminum Alloys ..................................... 5 2.2.1 Pitting Corrosion of Aluminum Alloys......................................................... 7 2.2.2 Uniform Corrosion of Aluminum Alloys ................................................... 10 2.3 Pitting Corrosion and Pit Morphology of Aluminum Alloys Under the Influence of Uniform Corrosion .................................................................................................... 19 viii 2.4 Corrosion Data Assessment Using Artificial Neural Network and Fuzzy Curve Analysis ......................................................................................................................... 20 2.5 Unresolved issues ............................................................................................... 22 2.6 References .......................................................................................................... 33 Chapter 3 Dependence on Temperature, pH, and Cl− in the Uniform Corrosion of Aluminum Alloys 2024-T3, 6061-T6, and 7075-T6 ........................................................ 40 3.1 Introduction ........................................................................................................ 40 3.2 Experimental ...................................................................................................... 42 3.2.1 Sample preparation ....................................................................................
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