Oxidation of Metals最新文献

The diffusion properties of polycrystalline materials depend on their grain shape and size, which determine the spatial distribution of grain boundaries. These morphological characteristics are of interest when evaluating an alloy ability to form a protective oxide scale by selective oxidation at high temperature. The composition changes induced by selective oxidation in 2D polycrystals were studied by finite element simulations. We examined the effect of the grain boundary orientation in lamellar polycrystals, and the effects of the grain size distribution in random equiaxed polycrystals. Fine-grained polycrystals were found to behave as uniform media. The effective diffusivity of fine lamellar polycrystals depends on the grain boundary orientation and is bounded by the upper and lower composite diffusivities, while the effective diffusivity of fine equiaxed polycrystals can be estimated by a modified Hart equation. The behavior of coarser equiaxed polycrystal was shown to vary according to the local grain size: the concentration at the alloy-scale interface is fully determined by the local grain size in larger grains, while it is affected by the surrounding grains in finer grains. Increasing the grain size dispersion led to a more scattered response and shifted the minimum interface concentrations toward lower values, which is expected to have a detrimental effect on the oxidation resistance.

Heat treatments and oxidation tests were performed on systems composed of a single-crystal AM3 superalloy with a NiCoCrAlYTa+Pt coating to investigate the effect of Pt on Ta and Ti diffusion at high temperature. Experimental results were compared to an AM3 superalloy directly coated with Pt. For all the studied systems, the effect of Pt on elemental activities was evaluated through thermodynamic calculations. Pt diffusion was found to be faster in the NiCoCrAlYTa coating than in AM3. High Ta contents were measured in the Pt-rich γ′ phase below the surface and significant Al and Cr transport toward the surface was observed, in agreement with thermodynamic calculations which predicted an important decrease in their activities in the presence of Pt. An outward diffusion of Ti was also noticed, whereas calculations did not show a decrease in Ti activity due to Pt. Other discrepancies between experiments and thermodynamic calculations were noted and are discussed in this work.

High entropy alloys (HEAs) challenge conventional alloy design by incorporating five or more principal elements in near-equal atomic proportions, forming random solid solutions with simple phases. HEAs exhibit exceptional properties such as high phase stability, mechanical strength, corrosion, oxidation, wear, fatigue resistance, and notable thermal stability. While traditional methods like arc melting and casting are often used for HEA preparation, they pose limitations due to cost and processing challenges. Additive manufacturing has emerged as a transformative technique, enabling the cost-effective fabrication of complex structures with customized properties. Here, we summarized the following “state-of-the-art” additively manufactured alloy systems: AlCrCoNiX (X = Fe, Si, Ti, etc.) HEAs, CoCrFeMnNi HEAs, and refractory HEAs. This review focused on elucidating their oxidation properties, emphasizing key findings, challenges, and opportunities. It also discussed the potential strategies for enhancing oxidation resistance. Additionally, it highlighted research gaps and underscored the urgent need for further exploration to meet the demands for high-temperature applications.

The addition of Si is known to improve the oxidation resistance of pure titanium and titanium alloys. However, most past studies concern the influence of relatively large Si contents (0.35–8 wt%), which is often incompatible with a good ductility because of the presence of Ti₅Si₃ precipitates. This study focuses on the influence of the Si content on the high-temperature resistance of near-alpha alloys from the family of Ti6244 alloy (6% Al, 2% Sn, 4% Zr 4% Mo–wt%) with small proportions of Si. The silicon addition was found to improve the high-temperature oxidation resistance of near-alpha Ti-Al-Sn-Zr-Mo family alloys by decreasing the oxidation rate and the oxide scale thickness, as well by producing a denser oxide scale. Rutile and alumina were detected within the oxide scale by XRD and Raman spectrometry. The presence of Si is associated with the presence of larger quantities of N at the oxide/metal interface.

The influence of cobalt and cobalt–manganese oxide coating thickness on its ability to be a good diffusion barrier against Cr outward diffusion was investigated for stainless steel interconnects (AISI 441) of a solid oxide cell (SOC). The coatings were all synthesized using a DLI-MOCVD (Direct Liquid Injection-Metal Oxide Chemical Vapor Deposition) hot wall reactor. The study shows that a minimum cobalt oxide thickness of 300 nm was needed to be a good diffusion barrier against Cr for the 500-h exposure test. This observation was linked to the Mn concentration reached in the cobalt spinel during exposure. Indeed, during exposure at high temperature, Mn diffused from the substrate into the cobalt coating and transformed cobalt spinel into Co-Mn spinel. Whereas pure cobalt spinel was a good Cr diffusion barrier, cobalt-manganese spinel, Co_3-xMn_xO₄, was not when x > 2. The thickness of the cobalt coatings must be chosen so that the Mn quantity coming into it from diffusion from the substrate does not degrade the protectiveness of the coating.

Degradation of coatings and structural materials due to high temperature corrosion in the presence of molten salt environment is a major concern for critical infrastructure applications to meet its commercial viability. The choice of high value coatings and structural (construction parts) materials comes with challenges, and therefore data centric approach may accelerate change in discovery and data practices. This research aims to use machine learning (ML) approach to estimate corrosion rates of materials when operated at high temperatures conditions (e.g., nuclear, geothermal, oxidation (dry/wet), solar applications) but geared towards nuclear thermochemical cycles. Published data related to materials (structural and coatings materials), their composition and manufacturing, including corrosion environment were gathered and analysed. Analysis demonstrated that random forest regression model is highly precise compared to other models. Assessment indicates that very limited sets of materials are likely to survive high temperature corrosive environment for extended period of exposure. While a higher quality and larger dataset are required to accurately predict the corrosion rate, the findings demonstrated the value of ML’s regression and data mining capabilities for corrosion data analysis. With the research gap in material selection strategies, proposed research will be critical to advancing data analytics approach exploiting their properties for high temperature corrosion applications.

Graphical Abstract

Aluminide coatings were prepared by chemical vapor deposition (CVD) method on Ni-based superalloy Mar-M247 to improve the corrosion resistance. The Na₂SO₄-induced hot corrosion behavior of Mar-M247 with and without aluminide coating was investigated at varying temperatures. The results revealed that the substrate underwent relatively mild corrosion attack at temperatures below the Na₂SO₄ melting point, but extremely severe corrosion attack above it. The aluminide coating significantly improved the corrosion resistance of the substrate, with the formation of Al₂O₃ scale during corrosion. The effects of both solid and molten Na₂SO₄ on hot corrosion resistance of Mar-M247 alloy and its aluminide coating was discussed, as well as the detrimental effect of tungsten on the substrate in ‘type I’ hot corrosion.