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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 109 records · Page 6

Impact of Irradiation on Corrosion Performance of Hybrid Organic/Inorganic Coatings on Austenitic Stainless Steel

The effects of gamma radiation on the performance of two corrosion-resistant coatings applied to stainless-steel 304L (SS304L) surfaces are presented. Specifically, the ability of the coatings to mitigate corrosion of SS304L surfaces as a function of the dose received (0–1300 Mrad) and dose rate (176 compared to 1054 rad/s) is evaluated using electrochemical methods, spectroscopy, and microscopy. Coating A, an organic/inorganic hybrid coating consisting of a two-part silica ceramic component and a polymer linker was evaluated in comparison to Coating B, which utilized Coating A as a topcoat for a commercial, off-the-shelf, Zn-rich primer. Post irradiation, Coating A demonstrated some corrosion protection following exposure to low levels of gamma radiation, but coating degradation occurred with an increased exposure dose and resulted in isolated regions of corrosion initiation. For Coating B, greater corrosion resistance was observed compared to Coating A due to the sacrificial nature of the Zn at elevated doses of gamma radiation. No effect of the dose rate (for the single dose examined) was observed for either coating. It is proposed for Coating B that as the polymer coating thermally degrades above 250 °C (bond scission of the polymer occurs), the remaining Zinc layer adhered to the SS304L post-irradiation enables enhanced corrosion resistance as compared to Coating A, which displays solely polymer degradation. The results presented herein establish an understanding of coating behavior with radiation exposure, specifically the relationship between corrosion coating performance and radiation dose, and can inform ageing and lifetime management for various applications.

degradation↗

The evolution of pit morphology and growth kinetics in aluminum during atmospheric corrosion

Abstract Assessing the lifetimes of alloys in humid, corrosive environments requires growth kinetic information regarding individual instances of damage, e.g. pit growth rates. Corrosion rates measured at the continuum scale using mass change convolute the rate of pit nucleation and growth, providing limited information on local kinetics. The current study used in-situ X-ray computed tomography to measure growth rates of individual pits in aluminum over 100 h of exposure in a humid, chloride environment. While pits grew at relatively constant rates over the first hours after nucleation, significant growth-rate nonlinearities subsequently occurred. These were linked to both droplet spreading, which altered the cathode size, and changes in the mode of pit growth. Pit morphology appeared to influence the dominant growth mode and the duration of pit growth. Post-mortem serial sectioning revealed pits preferentially attacked grain-boundary triple junctions and dislocation boundaries.

Noell, Philip J. (ORCID:0000000346998999)↗

Lessons Learned Using in-situ TEM Liquid Corrosion of Al Alloys

Al and Al alloys are of interest in energy applications due to their strength and low weight [1] in addition to their electrochemical properties for aluminum-air batteries for energy storage [2]. However, Al alloys also are susceptible to corrosion in a variety of environments including liquid electrolytes and in solar panels [3], which has led to a great deal of research to understand and improve corrosion resistance in these materials. Al metal forms a native, passivating oxide layer in the presence of ambient air, which slows corrosion initiation. However, pitting still occurs as this protective layer breaks down in the presence of electrolytes. Thin metal Al films were used in these experiments to observe initiation and growth of pitting, which can be used as an approximation of corrosion initiation behavior in bulk samples.

alluminum alloys↗

A Multiscale Inelastic Internal State Variable Corrosion Model

We present a corrosion internal state variable (ISV) damage model based upon the integrated computational materials engineering (ICME) hierarchical multiscale paradigm. Structure–property experiments for magnesium alloys were used where the only inputs were the volume fractions of each element of the periodic table. This macroscale ISV corrosion model finds its basis in Horstemeyer’s mechanical damage model, which includes three separate ISVs for damage nucleation, growth, and coalescence, as well as Walton’s inclusion of corrosion, which introduces five new ISVs for pit nucleation, growth, and coalescence, along with general corrosion and intergranular corrosion. While Walton’s corrosion ISVs are phenomenological in nature, herein we develop a multiscale physical basis for the corrosion ISVs. The parameters for the macroscale corrosion ISVs were garnered from the mesoscale Butler–Volmer equations. Pure magnesium with differing amounts of aluminum were used in corrosion tests to exemplify the different pitting, general corrosion, and intergranular corrosion rates, and the macroscale ISV model was calibrated with said data, in which the only inputs to the model are the volume percentages of the elements magnesium and aluminum. Although magnesium alloys were used to motivate and calibrate the model, the model is abstract enough to possibly capture other material systems as well.

Chemistry↗

Probing corrosion using a simple and versatile in situ multimodal corrosion measurement system

In this work, we have developed a unique in situ multimodal corrosion system that is capable of acquiring electrochemical data, sample imaging/visualization and hydrogen collection, simultaneously. Each of these modalities yield valuable information pertaining to the ongoing corrosion process. Combining them can yield holistic information on the role of microstructure, processing history, presence of coatings, etc., on the sequence of steps occurring during the corrosion process, and how they correlate with the acquired electrochemical data. Four materials systems, namely AA6061-T6 aluminum alloy, AZ91 magnesium alloy, galvanized DP590 steel, and pure Zn, were investigated under open circuit potential and under potentiodynamic polarization. The multimodal corrosion system was utilized to observe processes such as surface passivation and dissolution, pit and filiform corrosion initiation and propagation, and was correlated with location and magnitude of hydrogen evolution. This approach is shown to yield a truly multimodal understanding of the ongoing corrosion processes.

36 MATERIALS SCIENCE↗

Corrosion characteristics of Mo and TZM alloy for plasma facing components in molten lithium at 623 K

Here, in this study, the corrosion behaviours of molybdenum (Mo) and a Mo-based alloy (TZM) were investigated using a static immersion corrosion technique. Weight loss, surface microstructure, and corrosion depth of Mo and the TZM alloy were correlated with elements. The compatibility of Mo and the TZM alloy in static liquid Li was suitable. Mo demonstrated uniform corrosion with a homogenous dissolution of free C and Mo, and TZM alloy exhibited a nonuniform corrosion behaviour with a preferential grain boundary attack caused by the selective dissolution of free C, Ti, and Zr. When the surface oxidation layer of the samples was consumed, free C from Mo and TZM diffused into molten Li to form Li 2 C 2 and then was captured by Zr, Ti, and Mo to form thermodynamically stable carbides, which resulted in the enrichment of the C layer near the sample surfaces. In addition, Ti and Zr acted as N-trappers in liquid Li; the formation of Zr and Ti nitrides resulted in the enrichment of N, Ti, and Zr elements on the surface and led to TZM corrosion increase. Thus, Zr and Ti depletion, pitting, and grain boundary corrosion were problematic for TZM under long-term exposure to liquid Li. Reducing the content of free C and nonmetallic N and increasing the amount of Ti and Zr carbides on the surface of and inside the raw TZM alloy helped improve the corrosion resistance of TZM in liquid Li.

36 MATERIALS SCIENCE↗

Time-Dependent Corrosion Behavior of Aluminum Using Advanced Electrochemical and Characterization Techniques

The time-dependent corrosion behavior of pure aluminum (Al) in a chloride-containing environment was investigated using various electrochemical and characterization techniques for up to 336 h. Transmission electron microscopic and secondary ion mass spectroscopic analysis revealed the continuous dissolution of the surface film over the immersion time. In the meantime, the increasing passive oxide thickness resulted in the surface film resistance enhancement over the immersion time, as indicated by the electrochemical impedance spectroscopic analysis. The electrochemical noise measurements showed an increase in the corrosion kinetics with immersion time until 60 h because of the accelerated localized corrosion in the early stage of immersion. However, an inhibition in corrosion kinetics occurred after longer immersion times due to corrosion product deposition inside the pit.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Uranium hydride corrosion. II Modeling spatially random growth using reaction and nucleation kinetics

A uranium hydride (UH 3 ) corrosion kinetics model has been developed, based on dimensionally restricted nucleation kinetics, which combines heretofore separate reaction and nucleation kinetics models into a single predictive construct. This theoretical framework accounts for the superficial and random pitting behaviour of UH 3 corrosion. The model can be used to generate the net corrosion surface area and volume fractions for a uranium specimen, generally accounting for its geometric form factor through the surface-to-volume ratio. Furthermore, the combined corrosion kinetics model enables the generation of quantities which may be directly compared to those obtained by non-destructive, non-contact evaluation methods.

36 MATERIALS SCIENCE↗

Nuclear Canister Corrosion Detection

The software titled "nccd" is used for running residual neural networks (ResNets) on images of nuclear canisters. The software provides only the code for the implementation (based on the fastai library), but it does not share the image data. The compute code allows the use of residual nets (and more generally of other deep learning models) for classifying images from nuclear canisters as corroded. or intact. An image is considered to be corroded if it contains pitting or stress corrosion cracks. The code trains ResNets on image tiles extracted from original images from nuclear canisters, and then implements a classification rule, which can be applied to a validation set to decide if each original image is corroded or intact. The software automates the process of using images taken from nuclear canisters to detect corrosion. It provides also scope for future research directions on the basis of the existing research and code.

Papamarkou, Theodore↗

STATISTICAL ANALYSIS OF IN-SERVICE ULTRASONIC INSPECTION DATA OF WASTE TANKS AT THE SAVANNAH RIVER Site-25021

CONCLUSIONS AND RECOMMENDATIONS •“There is no evidence of pit depth growth over the last 15-years demonstrating the effectiveness of the corrosion control program. •“Incipient pits” are not growing and are likely pre-service pits. • No need to continue measuring these tiny pits. However, due to the random nature of pit initiation and the potentially accelerated growth of a pit, periodic monitoring for pit growth is prudent. 1. No reportable pits were identified. All identified pits are far less than the reportable depth of 25% of the nominal wall thickness. 2. No cracking was identified. 3. There is no evidence that active, systemic corrosion has occurred in Tank 29 during its 38-year service history as of 2009.

Harris, Stephen P. [Savannah River National Labora↗

Pit Stability Predictions of Additively Manufactured SS316 Surfaces Using Finite Element Analysis

Stainless steels are susceptible to localized forms of corrosion attack, such as pitting. The size and lifetime of a nucleated pit can vary, depending on a critical potential or current density criterion, which determines if the pit repassivates or continues growing. This work uses finite element method (FEM) modeling to compare the critical pit radii predicted by thermodynamic and kinetic repassivation criteria. Experimental electrochemical boundary conditions are used to capture the active pit kinetics. Geometric and environmental parameters, such as the pit shape and size (analogous to additively manufactured lack-of-fusion pores), solution concentration, and water layer thickness were considered to assess their impact on the pit repassivation criterion. The critical pit radius (the transition point from stable growth to repassivation) predicted for a hemispherical pit was larger when using the repassivation potential (E rp ) criteria, as opposed to the current density criteria (pit stability product). Including both the pit stability product and E rp into its calculations, the analytical maximum pit model predicted a critical radius two times more conservative than the FEA approach, under the conditions studied herein. The complex pits representing lack-of-fusion pores were shown to have minimal impact on the critical radius in atmospheric conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Electrochemical metrics for corrosion resistant alloys

Abstract Corrosion is an electrochemical phenomenon. It can occur via different modes of attack, each having its own mechanisms, and therefore there are multiple metrics for evaluating corrosion resistance. In corrosion resistant alloys (CRAs), the rate of localized corrosion can exceed that of uniform corrosion by orders of magnitude. Therefore, instead of uniform corrosion rate, more complex electrochemical parameters are required to capture the salient features of corrosion phenomena. Here, we collect a database with an emphasis on metrics related to localized corrosion. The six sections of the database include data on various metal alloys with measurements of (1) pitting potential, E pit , (2) repassivation potential, E rp , (3) crevice corrosion potential, E crev , (4) pitting temperature, T pit , (5) crevice corrosion temperature, T crev , and (6) corrosion potential, E corr , corrosion current density, i corr , passivation current density, i pass , and corrosion rate. The experimental data were collected from 85 publications and include Al- and Fe-based alloys, high entropy alloys (HEAs), and a Ni-Cr-Mo ternary system. This dataset could be used in the design of highly corrosion resistant alloys.

36 MATERIALS SCIENCE↗

Corrosion and repassivation of Super 13Cr stainless steel in artificial 1D pit electrodes at elevated temperature

Repassivation behavior of Super 13Cr martensitic stainless steel was investigated using a one-dimensional artificial pit electrode in deaerated NaCl solutions at 85 °C. Critical potentials for pit repassivation (E crit ) were measured by downward potential scans. E crit and the final current density (i f ) at the end of the scan can be correlated to the pit repassivation, showing that repassivation is more probable with smaller i f and higher E crit . Pit repassivation at a constant potential was correlated with if and average current density (i avg ). A combination of lower i f and i avg suggests a higher probability for pit repassivation.

36 MATERIALS SCIENCE↗

Observations of Atmospheric Corrosion Testing on Heated Austenitic Stainless Steel Surfaces: Exploring the Role of Inert Dust Particulates and Seawater

Relevant atmospheric corrosion laboratory testing environments were developed to explore the influence of inert dust and seawater on the corrosion susceptibility of stainless steel in spent nuclear fuel dry storage conditions. Measurements from dust collected on in-service dry storage canisters were applied to develop exposure conditions. Three atmospheric exposure conditions, two static and one cyclic, were examined with three different surface coverages: co-deposited large dust and seawater, co-deposited small dust and seawater, and solely seawater. Stainless steel coupons representative of spent nuclear fuel dry storage canister material were subjected to the various corrosion environments, with the results from exposures up to 1 year presented here. Post exposure, corrosion damage was analyzed using optical microscopy, scanning electron microscopy, and energy dispersive X-ray spectroscopy. Initial observations are presented herein, and potential implications with respect to the influence of inert dust particles on corrosion susceptibility are summarized. In general, the co-deposition of dust and salt resulted in larger pits and exhibited mixed modes of corrosion that were not observed in the no-dust conditions (i.e., crevicing, filiform, and pits within pits). The presence of the inert dust may influence brine spreading and/or act as crevice formers, leading to enhanced corrosion. This study highlights the significance of incorporating dust particulate(s) beyond the deliquescent chemistries to fully evaluate atmospheric corrosion severity.

Sea salt↗

Unsupervised learning-enabled pulsed infrared thermographic microscopy of subsurface defects in stainless steel

Metallic structures produced with laser powder bed fusion (LPBF) additive manufacturing method (AM) frequently contain microscopic porosity defects, with typical approximate size distribution from one to 100 microns. Presence of such defects could lead to premature failure of the structure. In principle, structural integrity assessment of LPBF metals can be accomplished with nondestructive evaluation (NDE). Pulsed infrared thermography (PIT) is a non-contact, one-sided NDE method that allows for imaging of internal defects in arbitrary size and shape metallic structures using heat transfer. PIT imaging is performed using compact instrumentation consisting of a flash lamp for deposition of a heat pulse, and a fast frame infrared (IR) camera for measuring surface temperature transients. However, limitations of imaging resolution with PIT include blurring due to heat diffusion, sensitivity limit of the IR camera. We demonstrate enhancement of PIT imaging capability with unsupervised learning (UL), which enables PIT microscopy of subsurface defects in high strength corrosion resistant stainless steel 316 alloy. PIT images were processed with UL spatial–temporal separation-based clustering segmentation (STSCS) algorithm, refined by morphology image processing methods to enhance visibility of defects. The STSCS algorithm starts with wavelet decomposition to spatially de-noise thermograms, followed by UL principal component analysis (PCA), fine-tuning optimization, and neural learning-based independent component analysis (ICA) algorithms to temporally compress de-noised thermograms. The compressed thermograms were further processed with UL-based graph thresholding K-means clustering algorithm for defects segmentation. The STSCS algorithm also includes online learning feature for efficient re-training of the model with new data. For this study, metallic specimens with calibrated microscopic flat bottom hole defects, with diameters in the range from 203 to 76 µm, were produced using electro discharge machining (EDM) drilling. While the raw thermograms do not show any material defects, using STSCS algorithm to process PIT images reveals defects as small as 101 µm in diameter. To the best of our knowledge, this is the smallest reported size of a sub-surface defect in a metal imaged with PIT, which demonstrates the PIT capability of detecting defects in the size range relevant to quality control requirements of LPBF-printed high-strength metals.

36 MATERIALS SCIENCE↗