A pinboard by
Matthew McMahon

Graduate Research Assistant, University of Virginia


Environmental cracking is problematic in Al-Mg alloys, potentially resolved by metal-rich coatings.

High strength, lightweight Al-Mg alloys are used to replace heavy steel components in a variety of industries today, but these alloys deal with corrosion-induced cracking problems that can lead to unexpected material failure. Previous work had proven that these corrosion reactions form significant concentrations of hydrogen ions, which in turn cause hydrogen embrittlement in these Al-Mg alloys that leads to rapid crack formation. My research has further validated why this cracking occurs, and in so doing has shown that minimizing these corrosion reactions effectively suppresses the corrosion-induced cracking by reducing hydrogen formation. I am now investigating economic solutions to solve this corrosion-induced material failure by studying the efficacy of metal-rich protective coatings. Such coatings have been used successfully to stop corrosion on a range of alloys in service, and they are designed with a multitude of different capabilities, but few have been studied to determine if they can mitigate cracking processes as well. Therefore, I aim to determine the metal-rich coating properties that best enable these coatings to mitigate environmental cracking in Al-Mg alloys, and in doing so I hope to inform future coating development. Al-Mg alloys are becoming increasing important to the transportation, defense, and general engineering sectors, and once the environmental cracking dilemma is resolved these new lightweight materials can be used in even wider reaching roles.


Metallurgical factors in stress corrosion cracking (SCC) and hydrogen-induced cracking (HIC)

Abstract: Nonmetallic inclusions can affect resistance of steels to both general and localized corrosion, including pitting corrosion, stress corrosion cracking (SCC), and hydrogen-induced cracking (HIC). Because stress corrosion cracks frequently initiate at pits, and pits nucleate at sulfides, the presence of sulfides is likely to affect the SCC process. Nonmetallic inclusions increase susceptibility of steel to HIC, which occurs by the formation of internal hydrogen blisters or blister-like cracks at internal delaminations or at nonmetallic inclusions in low strength materials. HIC occurs when H atoms diffusing through a linepipe steel become trapped and form H2 molecules at inhomogeneities in the steel. A planar, gas-filled defect is created, which grows parallel to the pipe surface as it continues to trap more diffusing H atoms. If the defect grows sufficiently large, it may develop into a blister. HIC failure occurs if a mechanism exists for linkage of defects or blisters with the internal and external surfaces. The H atom source is normally the cathodic reaction of an acid corrosion mechanism occurring at the internal linepipe surface, i.e., the reduction of hydrogen ions, H+:\( \begin{gathered} {\text{Anodic reaction}}:{\text{ Fe }} \to {\text{ Fe}}^{{2 + }} + {\text{ 2e}}^{ - } \hfill \\ {\text{Cathodic reaction}}:{\text{ 2H}}^{ + } ~ + {\text{ 2e}}^{ - } ~ \to {\text{ 2H}}_{\text{ads}} \hfill \\ \end{gathered} \)

Pub.: 25 Mar '09, Pinned: 28 Aug '17

The Role of grain boundary misorientation in intergranular cracking of Ni-16Cr-9Fe in 360 °C argon and high-Purity water

Abstract: The effect of grain boundary misorientation on the intergranular cracking behavior of pure Ni-16Cr-9Fe was assessed by determining if low-angle boundaries (LABs) or coincident site lattice boundaries (CSLBs) are more crack resistant than general high-angle boundaries (GHABs) in argon and high-purity water. Cracking susceptibility of boundary types was determined using constant extension rate tensile tests (CERTs) in 360 °C argon and in deaerated, high-purity water. Annealed samples contained 12 to 20 pct CSLBs, while CSLB-enhanced samples contained 27 to 44 pct CSLBs; GHAB proportions varied accordingly. Cracked boundary fractions for CSLB-enhanced samples tested in either environment ranged from 0.01 to 0.08, while those for annealed samples ranged from 0.07 to 0.10, indicating that samples with increased proportions of CSLBs are more crack resistant. No LABs cracked in either environment. In annealed samples, the proportion of CSLBs that cracked in water was 6.7 pct compared to 1.5 pct in argon; the proportion of GHABs that cracked in water was 9.3 pct compared to 6.6 pct for argon. Thus, CSLBs are more crack resistant than GHABs in either environment, and both are more crack resistant in argon than in water. The higher amounts of cracking and the higher CSLB cracking susceptibility in high-purity water indicate the presence of an environmental effect on cracking behavior. The beneficial effect of LABs and CSLBs is likely due to the ability of these boundaries to induce slip in neighboring grains by either transmitting or absorbing and re-emitting lattice dislocations, thereby reducing grain boundary stresses and the propensity for crack initiation. The results indicate that control of grain boundary proportions can improve the intergranular stress corrosion cracking susceptibility of pure Ni-16Cr-9Fe.

Pub.: 03 Dec '13, Pinned: 28 Aug '17

The EIS-based Kohonen neural network for high strength steel coating degradation assessment

Abstract: Electrochemical impedance spectroscopy (EIS) method is used for a long-term and in-depth study on the failure analysis of polymer coatings. With the assistance of neural networks, a deeper insight into the changing states of corrosion during certain exposure circumstances has been investigated by applying specific Kohonen intelligent learning networks. The Kohonen artificial network has been trained by using 4 sets of samples from sample 1# to sample 4# with unsupervised competitive learning methods. Each sample includes up to 14 cycles of EIS data. The trained network has been tested using sample 0# impedance data at 0.1 Hz. All the sample data were collected during exposure to accelerated corrosion environments, and it took the changing rate of impedance of each cycle as an input training sample. Compared with traditional classification, Kohonen artificial network method classifies corrosion process into 5 subprocesses, which is refinement of 3 typical corrosion processes. The 2 newly defined subprocesses of corrosion, namely, premiddle stage and postmiddle stage were introduced. The EIS data and macro-morphology for both subprocesses were analyzed through accelerated experiments that considered general atmospheric environmental factors such as UV radiation, thermal shock, and salt fog. The classification results of Kohonen artificial network are highly consistent with the predictions based on impedance magnitude at low frequency, which illustrates that the Kohonen network classification is an effective method to predict the failure cycles of polymer coatings.

Pub.: 12 Jul '17, Pinned: 28 Aug '17