Oxidation of Metals最新文献

The transformation of wüstite (FeO) in the oxide layer formed during high temperature oxidation (600 °C and 700 °C) on hot-worked tool steel was investigated. Wüstite plays an important role in the oxide layer of these steels used for hot working. However, understanding its transformation behavior during cooling is crucial for controlling the final oxide layer structure. Slow cooling rates have a significant influence on the final wüstite content, resulting in inaccurate representations of the composition of the oxide layer at temperatures above 570 °C. The aim of this study was to determine the influence of cooling rate on the wüstite content in the oxide layer after high temperature oxidation. It was found that for hot-worked steel samples oxidized at 700 °C or higher, a cooling rate of more than 1000 °C min⁻¹ is required to suppress the eutectoid transformation and maintain the realistic wüstite content. At lower temperatures (570 °C–600 °C), a cooling rate of more than 100 °C min⁻¹ is required to achieve the wüstite content observed at oxidation temperatures in the oxide layer. Overall, the hematite and magnetite contents also vart with the cooling rate, which is associated with changes in the wüstite content.

Analysis of scanning electron microscope (SEM) images is crucial for characterising aluminide diffusion coatings deposited via the slurry route on steels, yet challenging due to various factors like imaging artefacts, noise, and overlapping features such as resin, precipitates, cracks, and pores. This study focuses on determining the thicknesses of the coating layers Fe₂Al₅ and, if present, FeAl, pore characteristics, and chromium precipitate fractions after the heat treatment that forms the diffusion coating. A deep learning SEM image segmentation model utilising U-Net architecture is proposed. Ground truth data were generated using the trainable Weka segmentation plugin in ImageJ, manually refined for accuracy, and supplemented with synthetic data from Blender 3D software for data augmentation of a limited number of SEM label images. The deep learning model trained on a combination of synthetic and real SEM data achieved mean dice scores of 98.7% ± 0.2 for the Fe₂Al₅ layer, 82.6% ± 8.1 for pores, and 81.48% ± 3.6 for precipitates when evaluated on manually labelled SEM data. The deep learning procedure was applied to evaluate a series of SEM images of diffusion coatings obtained with three different slurry compositions. The evaluation revealed that using a slurry without a rheology modifier may lead to a thicker partial Fe₂Al₅ layer that is formed by inward diffusion. The relation between the outward and inward diffusion Fe₂Al₅ layers was not affected by the coating thickness. The thinner diffusion coating presents lower pores and chromium precipitate fractions independently of the slurry selected.

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.