Search NASA⌕ Search

SEARCH · Search NASA

Results for “alloy oxidation”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2

First-Principles study of interface capture of Ni during high-temperature oxidation of NiCr alloys

The formation of precipitated phases of less reactive metals within an oxide scale during alloy oxidation can disrupt its structural integrity, significantly compromising the protective function of the oxide. To better understand this phenomenon, it is crucial to investigate the atomic-level diffusion mechanisms that drive precipitate formation. In this study, we employ first-principles calculations to examine the diffusion and aggregation of Ni atoms across the NiCr/Cr 2 O 3 interface during the high-temperature oxidation of NiCr alloys. Our results reveal that, in the absence of Cr vacancies, Ni atoms predominantly remain within the NiCr substrate, with minimal migration toward the Cr 2 O 3 layer. However, when Cr vacancies are present at both the NiCr/Cr 2 O 3 interface and within the Cr 2 O 3 bulk, Ni atoms exhibit a strong propensity to migrate from the NiCr substrate into the Cr 2 O 3 bulk, where they aggregate into Ni-rich regions with a corundum structure. This study provides valuable atomic-level insights into the diffusion and aggregation of less-reactive metals at the alloy/oxide interface, enhancing our understanding of solute capture and its contribution to the degradation of oxidation resistance in alloys.

Chen, Jianmin [Xiangtan University (China)] (ORCID↗

Uncovering electronic and geometric descriptors of chemical activity for metal alloys and oxides using unsupervised machine learning

Here, we show that unsupervised machine learning (ML) using principal component analysis (PCA) provides a straightforward pathway for developing accurate and interpretable electronic-structure descriptors of the chemical and catalytic properties of materials. We demonstrate the approach by finding chemisorption descriptors for metal alloys and surface oxygens on metals and metal oxides. In both cases, the principal component (PC) descriptors yield ML models that predict the material’s chemical properties with competitive accuracy compared to ML models built using established descriptors. Importantly, interpreting the electronic-structure patterns captured by each PC descriptor via signal reconstruction suggests potential design motifs for future electronic-structure descriptor design and allows us to identify links between a material’s geometric and catalytic properties. Ultimately, we show that the unsupervised ML approach provides a route to find electronic-structure descriptors of the catalytic properties of materials that readily connect to geometric structure and composition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Lessons Learned in Employing Data Analytics to Predict Oxidation Kinetics and Spallation Behavior of High-Temperature NiCr-Based Alloys

Machine learning (ML) can offer many advantages in predicting material properties over traditional materials development methods based solely on limited experimental investigations or physical-based simulations with the capability to reduce development cost, risk, and time. However, so far, limited efforts have been made to predict alloy oxidation kinetics and spallation behavior via ML due to the lack of consistently measured and sufficient experimental data and the inherent complexity in oxidation behavior of multicomponent high-temperature alloys. A previous study reported the ability of ML to predict oxidation kinetics of NiCr-based alloys as a function of alloy composition and operating conditions. Here, the performance of a ML model in predicting rate constants and spallation probability was evaluated in light of the roles of the data distribution of the experimental dataset (data analytics), the alloy composition, the exposure environment and the chosen oxidation approach to extracting kinetic values from the measured mass changes (but using either a simple parabolic law or a statistical cyclic oxidation model). Potential strategies to improve the predictions and enhance the extrapolative capability of the previously trained model will be discussed.

36 MATERIALS SCIENCE↗

Role of nitrogen in the high-temperature oxidation of titanium alloys

Here, we characterized the oxidation of pure Ti, Ti-0.8Si, and Ti-2Nb at 800 °C in N 2 -20% O 2 and in sequential isotopically labeled N 2 -20% O 2 atmospheres to clarify how nitrogen influences the high-temperature oxidation mechanisms of titanium alloys. The alloys always exhibited a nitride layer beneath a compact oxide scale with localized nitrogen concentrations in the underlying metal. Nitrogen is found to limit the oxygen concentrations in the metal. The synergy between alloying and nitrogen helps maintain compact oxide scales, preventing the formation of the lamellar scales observed during oxidation in nitrogen-free atmosphere and the oxidation of pure Ti regardless of the atmosphere.

36 MATERIALS SCIENCE↗

High temperature oxidation of corrosion resistant alloys from machine learning

Parabolic rate constants, k p , were collected from published reports and calculated from corrosion product data (sample mass gain or corrosion product thickness) and tabulated for 75 alloys exposed to temperatures between ~800 and 2000 K (~500–1700 °C; 900–3000°F). Data were collected for environments including lab air, ambient and supercritical carbon dioxide, supercritical water, and steam. Materials studied include low- and high-Cr ferritic and austenitic steels, nickel superalloys, and aluminide materials. A combination of Arrhenius analysis, simple linear regression, supervised and unsupervised machine learning methods were used to investigate the relations between composition and oxidation kinetics. The supervised machine learning techniques produced the lowest mean standard errors. The most significant elements controlling oxidation kinetics were Ni, Cr, Al, and Fe, with Mo and Co composition also found to be significant features. The activation energies produced from the machine learning analysis were in the correct distributions for the diffusion constants for the oxide scales expected to dominate in each class.

Materials Science↗

Environmental Compatibility Issues for Ni-Based Alloys in Direct-Fired Supercritical CO2 Power Cycles

Direct-fired supercritical CO2 (sCO2) power cycles offer potential for high-efficiency power generation from natural gas and other fossil fuels with built-in carbon capture. Ni-based superalloys are the leading candidates for the hottest portions of these systems, where they must endure long-term exposure to high-temperature, high-pressure, high-velocity, impure CO2-rich environments. Herein we describe results of various experimental testing campaigns conduced at NETL showing that under such conditions, several simultaneously occurring degradation modes may be active including surface oxidation, alloy carburization, and oxide volatilization. It will be shown that the rates of degradation can be strongly affected by the alloy composition, impurities in the CO2, manufacturing method (wrought vs additive), and other factors. The influence of these factors in controlling alloy degradation are discussed in the context of potential compatibility issues for components in real sCO2 systems, such as compact heat exchangers. Finally, as a potential remedial measure, ongoing work involving protective coatings suitable for complex geometries is presented.

alloy oxidation↗

Developing an oxidation materials ontology for data-driven materials design

Materials data is complex, and managing and storing materials data for use and reuse is a common challenge. An ontology-based data management framework can address these challenges through encoding data attributes and relationships in a flexible way. This presentation discusses the creation of an ontology for alloy oxidation test data and reviews the logic, structure and interoperability of the ontology.

advanced alloy development↗

Effect of water vapor on high-temperature oxidation of NiAl alloy

The high-temperature oxidation of NiAl is studied with dry oxygen and water vapor. The oxidation in H 2 O results in a thicker Al 2 O 3 oxide scale than that in O 2 . The oxide scale formed initially is a single layer of γ-Al 2 O 3 that subsequently transforms into a α-Al 2 O 3 /γ-Al 2 O 3 bilayer structure, in which the inner α-Al2O3 layer formed in H2O has a higher porosity than that in O 2 . Finally, further density functional theory calculations show that H protons derived from H 2 O molecules penetrate into the oxide lattice and boost the formation of lattice vacancies in both α-Al 2 O 3 and γ-Al 2 O 3 , thus enhancing the oxide scale growth.

36 MATERIALS SCIENCE↗

Chromium segregation-induced oxide evolution in Ni-10Cr alloys during high-temperature oxidation

The oxidation behavior of a Ni-10(wt%)Cr alloy under high-temperature O 2 conditions is investigated using transmission electron microscopy and first-principles calculations. Results reveal that chromium segregation plays a central role in driving the evolution of complex oxide phase structures during oxidation. At low Cr concentrations, Cr preferentially segregates to NiO grain boundaries or internal pores, substituting for Ni atoms and forming Ni(Cr)O solid solutions. As Cr content increases, enhanced diffusion promotes Cr penetration into the NiO lattice, leading to the formation of multiphase oxide structures. First-principles modeling corroborates these findings: at low Cr concentrations, Cr atoms favor surface and grain-boundary segregation, while higher concentrations lead to Cr aggregation within the NiO bulk. Furthermore, the integrated experimental-theoretical approach provides atomistic insights into Cr-mediated mass transport mechanisms during alloy oxidation and offers valuable guidance for controlling oxide growth kinetics and phase stability in Ni-Cr alloys, with implications for improving oxidation resistance in high-temperature structural applications.

36 MATERIALS SCIENCE↗

Mesoporous nickel-iron-manganese-alloy based metal/metal oxide composite thick film catalysts

Selective alloy corrosion is used to synthesize a robust and ultrafine mesoporous NiFeMn-based metal/metal oxide oxygen evolving catalyst with ligament and pore sizes in the range of 10 nm and a BET surface area of 43 m2/g. As an oxygen evolving catalyst, the mesoporous catalyst exhibits high stability (>264 hours) at a high current density (500 mA/cm2) with a low overpotential (360 mV) using a moderate electrolyte concentration (1 M KOH). The catalyst is made from non-precious metals and its fabrication is straight forward and directly applicable to large-scale synthesis.

36 MATERIALS SCIENCE↗

Understanding oxidation of Fe-Cr-Al alloys through explainable artificial intelligence

Abstract The oxidation resistance of FeCrAl based on alloying composition and oxidizing conditions is predicted using a combinatorial experimental and artificial intelligence approach. A neural network (NN) classification model was trained on the experimental FeCrAl dataset produced at GE Research. Furthermore, using the SHapley Additive exPlanations (SHAP) explainable artificial intelligence (XAI) tool, we explore how the NN can showcase further material insights that are unavailable directly from a black-box model. We report that high Al and Cr content forms protective oxide layer, while Mo in FeCrAl creates thick unprotective oxide scale that is vulnerable to spallation due to thermal expansion. Graphical abstract

Materials Science↗

Enhanced Mechanical Properties and Wear Resistance of FeCrAl Alloys at ~ 300°C and Higher Temperatures

Abstract Worldwide, light water reactors (LWRs) have been using zirconium (Zr)-based alloys for the cladding of the uranium dioxide fuel for more than 6 decades. Zr alloys oxidize rapidly in the presence of water and steam at temperatures > 450°C; therefore, they do not respond well to scenarios of loss of coolant accidents. There is a global effort by nuclear materials technologists to find more robust or stronger cladding materials for LWRs. One option is to use an iron-chromium-aluminum (FeCrAl) alloy since they have excellent resistance to high temperature oxidation and superior mechanical properties at LWR operation temperatures. Results show that (1) FeCrAl alloys have better mechanical properties than Zr alloy and are orders of magnitude more resistant to creep at temperatures higher than LWR normal operation conditions. (2) FeCrAl alloys have better resistance to fretting wear than Zr alloys at the normal operation conditions of LWRs.

Materials Science↗