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This paper examines the consistency between experiments and thermodynamic predictions of the modification of non-metallic inclusions by dissolved Ca in liquid Fe-Al alloys. Current thermodynamic predictions made with FactSage (version 7.2) were found to overestimate the amount of dissolved Ca and the Ca in non-metallic inclusions. This was demonstrated in two ways. First, Al-deoxidized Fe was held in CaO-3 pct ZrO2 crucibles for 100-136 minutes at 1873 K (1600 °C) and then reoxidized to precipitate dissolved Ca as oxide inclusions. The amount of Ca in the inclusions after reoxidation was quantified and considered equal to the dissolved Ca in the liquid Fe prior to reoxidation. Although experimental data were limited, the results suggested that the dissolved Ca was low and that the thermodynamic behavior of Ca could be best described by excluding Ca-O interaction. The assumption of no Ca-O interaction was compared with the associate solution model employed in FactSage by simulating the evolution of inclusion compositions in Fe—2, 1, 0.5, 0.1 wt pct Al alloys exposed to CaO (sat.)-MgO (sat.)-Al2O3 slags. The assumption of no Ca-O interaction led to predictions that were much closer to experimental results. More work is needed to ensure dissolved Ca behavior is accurately described and to ensure the sources for Ca modification of inclusions in industrial samples are properly identified.

The high melting temperature of tungsten (W) makes it an attractive candidate for energy generation applications; however, its use is limited by its poor ductility at low temperatures. This limitation affects even melt-based additive manufacturing (AM) processes such as laser powder bed fusion (PBF-LB), with as-fabricated pure W exhibiting both longitudinal and transverse cracks. Metallurgical and processing factors that affect these cracks are still being explored. This work utilizes powderless single-tracks on pure W plates made over a range of power and velocity combinations in three unique PBF-LB setups: one with flowing argon, one with continuous vacuum, and an in situ high-speed synchrotron X-ray radiography setup. Each had different oxygen activities in their build environments. Longitudinal cracks with oxides appearing to exude from the crack were found for tracks deposited in a build environment with argon shield gas, while no such cracks were observed for builds conducted in vacuum. A calculation showed that direct oxygen ingress into the melt pool from the build environment is negligible when argon shield gas is present. Thus, incorporation of spatter is a likely mechanism for oxygen ingress into the melt pool. Radiography showed extensive keyholing, spatter generation, and crack formation at keyhole porosity. A heat transfer calculation showed the crack formation time was consistent with cooling below its ductile-to-brittle transition (DBT) temperature. This work identifies solidification cracking as a feasible mechanism in pure W beyond the well-known DBT related cracking.

This study documents laboratory-scale observations of reactions between Fe-Al alloys (0.1 to 2 wt pct Al) with slags and refractories. Al in steels is known to reduce oxide components in slag and refractory. With continued development of Al-containing Advanced High-Strength Steel (AHSS) grade, the effects of higher Al must be examined because reduction of components such as CaO and MgO could lead to uncontrolled modification of non-metallic inclusions. This may lead to castability or in-service performance problems. In this work, Fe-Al alloys and CaO-MgO-Al2O3 slags were melted in an MgO crucible and samples were taken at various times up to 60 minutes. Inclusions from these samples were characterized using an automated scanning electron microscope equipped with energy dispersive x-ray analysis (SEM/EDS). Initially Al2O3 inclusions were modified to MgAl2O4, then MgO, then MgO + CaO-Al2O3-MgO liquid inclusions. Modification of the inclusions was faster at higher Al levels. Very little Ca modification was observed except at 2 wt pct Al level. The thermodynamic feasibility of inclusion modification and some of the mass transfer considerations that may have led to the differences in the Mg and Ca modification behavior were discussed.

In this work, we operate on a small dataset available from the technical literature to predict the oxidation-induced mass change at 1000 °C of thousands of new alloy compositions using “Tree-based Pipeline Optimization Tool” , an automated machine learning (ML) method. The ML pipeline we develop is trained on the log10 of the mass change per unit area. This yields a mean absolute error of 0.34 on the test set’s values, which span 3.5 decades. With additional insights from thermodynamic simulations, a set of seven alloys is selected, manufactured, and characterized. Of these, the oxidation behavior of five alloys is well-predicted by the ML-based model, while results for two alloys show orders of magnitude deviations from predictions. The results show that ML-based methods can be useful for predicting composition-dependent oxidation behavior, despite its many complexities.

This study focuses on the initial stages of iron surface oxidation, studied by confocal scanning laser microscopy. Pure iron cubes were prepared and polished for in situ observation. Samples were oxidized for 2–60 s by dry air at 1150 °C. A dynamic oxidation process was observed, with two reaction fronts that moved from the sample edge to the center at around 20–30- and around 40–50-s oxidation, respectively. Scanning electron microscopy (SEM) was used to characterize the iron oxide surface morphology. Pyramidal features appeared first on the surface, and then the surface became flatter with time. X-ray diffraction was used to characterize the phases of the outermost oxide layer. Overall, the content of wüstite decreased and hematite content increased with oxidation time. SEM with a backscattered electron detector was used to measure the oxide layer thicknesses, and it was found that the oxide thickness increased parabolically with time. The different oxide layers within the scale were identified by an optical microscope with a polarized light source. Even after 2-s oxidation, an obvious magnetite layer was found on the wüstite layer, and after 10-s oxidation, an obvious hematite layer was observed on the magnetite layer. A thicker hematite layer was observed at the sample edge. The reasons for the morphology changes are discussed.

The nitrogen isotope exchange reaction was applied to measure the interfacial reaction rate constant of nitrogen with liquid cobalt at 1823 K, 1873 K, and 1923 K. Measured values increased with increasing temperature, with average values of 1.3×10−7 mol cm−2 s−1 atm−1 at 1823 K, 3.3×10−7 mol cm−2 s−1 atm−1 at 1873 K, and 6.2×10−7 mol cm−2 s−1 atm−1 at 1923 K. Compared with liquid iron, the rate on cobalt is more than an order of magnitude smaller.

The nature of MgO and Al 2 O 3 dissolution in metallurgical slags may affect production cost, efficiency, and product quality. However, the rate-limiting dissolution mechanism, chemical reaction or boundary layer diffusion, is not well understood. In the present report, the dissolution mechanism of MgO and Al 2 O 3 in metallurgical slag was evaluated based on available literature data. The mass balance between the dissolving particle and the flux equation through the boundary layer was applied to predict the dissolution curve. The influence of fluid flow was taken into account to calculate the mass transfer rate at the oxide/slag interface. It was found that the rate-limiting step of MgO and Al 2 O 3 dissolution is the same: mass transfer through the boundary layer. Depending on the slag composition and experimental temperature, the effective diffusion coefficient for MgO and Al 2 O 3 dissolution falls in the range of 10 −12 to 10 −9  m 2 /s.

This study showed that MgO inclusions can be stable in liquid iron with elevated Al and it illustrated an important role of vaporization in the evolution of inclusions. Previous studies have shown that dissolved Al reduces MgO from slags and refractories, leading to spinel (MgAl 2 O 4 ) inclusions. The elevated Al content of newer steels raises the possibility that MgO inclusions can be stable. In this work, MgO inclusions were produced and observed in an Fe-Al alloy. The inclusions in the liquid alloy at 1873 K (1600 °C) were observed in situ with a Confocal Laser Scanning Microscope (CLSM). Two types of experiments were performed: one where only a metal sample was melted and the other where the sample was in contact with a liquid, MgO-saturated slag. When no slag was present, the MgO inclusions shrank and disappeared at 1873 K (1600 °C). No inclusions were observed in situ during cooling or in post-CLSM analysis. When the MgO-saturated slag was present, the inclusion sizes were essentially constant and MgO was observed on the surface of post-CLSM samples. Analysis of the results showed that MgO can be stable in 1873 K (1600 °C), but that its presence depends on the rate of removal of Mg due to vaporization and the supply of Mg due to slag/metal or refractory/metal reactions.

Titanium nitride precipitation on a primary inclusion particle during solidification of bearing steel has been tracked by varying temperature in a confocal scanning violet laser microscope. Upon precipitation, an obvious growth of titanium nitride on a primary inclusion particle was observed due to the rapid solute diffusion in liquid steel. The onset of titanium nitride precipitation did not change with primary inclusion particle size, but the time of growth was greater for a smaller primary inclusion particle. Meanwhile, the particle size displayed little influence on the total precipitated amount of titanium nitride on it under the same conditions. At the later period of solidification, almost no change occurred in inclusion size, but the inclusion shape varied from circle to almost square in two-dimension, or cubic in three-dimension, to attain the equilibrium with steel.

This study presents a method to automatically identify inclusion clusters within a sample. Utilizing the output of scanning electron microscopy’s automated feature analysis along with Density-based Spatial Clustering of Application with Noise, an unsupervised machine learning algorithm, inclusion clusters are identified based on their spatial position. The analysis was initially conducted on two samples known by manual analysis to be clustered and non-clustered to evaluate the applicability of this technique. A serial-sectioning analysis was performed to obtain a 3D representation of the inclusion distribution. The 2D and 3D results were consistent. To evaluate the area effected by clusters, the convex hull area was utilized rather than the total inclusion area in a cluster. The analysis was then applied to a series of samples from three aluminum-alloyed heats to investigate cluster evolution throughout the secondary steelmaking process. Several distinct types of clusters were identified. Agglomerated globular alumina inclusion clusters were observed after tapping, which then evolved to non-globular inclusion clusters. The same types of clusters were also observed for spinel inclusions, but they were not as pervasive as alumina inclusions. In addition, clustering of small micro-inclusions around a large macro-inclusion was occasionally observed.