Impurities in lead alloys affect the production yield and grid quality of lead-acid batteries. In addition to contamination limits, battery manufacturers often specify the maximum level of dross that can be produced when melting a given alloy. This study presents, for the first time, an example of a method for determining the percentage of dross formed after melting an alloy. In addition, the effect of three different lead pyrorefining methods—traditional refining, traditional refining with the double addition of NaOH and NaNO3 and an alternative method using metallic aluminum—on the percentage of dross produced during the melting of the PbSnCa alloy was evaluated. Industrial-scale experiments have revealed significant differences in the amount of melt dross formed, confirming the influence of the refining method on this parameter. The aluminum refining method gave a lower dross content than the traditional approach and showed the highest process stability. Microstructural and phase analysis indicated that the resulting dross consisted mainly of metallic lead mixed with oxide phases. The results highlight the potential of lead refining using aluminum and provide valuable insights into optimizing lead recycling practices, as well as being a valuable knowledge base for lead-acid battery manufacturers.

Bulk Metallic Glasses (BMGs) are becoming prevalent as specialty components in aerospace, energy, and medical technologies, and hold long-term potential as consumer good components. When manufacturing BMG components by solidification and thermoplastic forming, however, even small deviations from optimal processing conditions can alter the structural glass state, promote crystallization, and introduce geometric flaws. Established techniques to evaluate the integrity of BMG components are often expensive, time-consuming, and destructive in nature. In this study, we employ Resonance Ultrasound Spectroscopy (RUS) as an inexpensive, fast, and non-destructive alternative to accurately measure the elastic properties of BMG components and thus estimate their fictive temperature. Further, RUS can detect crystallinity and geometric flaws. These capabilities are demonstrated even for complex component geometries, based on a BMG planet gear here.

High temperature creep strengths of Nb-based alloys have been limited by the lack of coherent precipitates that exist at temperatures above 1200Image 1. In this investigation, a series of BCC Nb-based alloys with coherent HfRu- and ZrRu-B2 precipitates were investigated to determine the dependence of phase stability, misfit, and solvus temperatures on composition. Sequential anneals from 1000-1500Image 1 were used to determine the B2 solvus temperature (Ts,B2) of each alloy and solvus lines were constructed for each system. HfRu-B2 is found to be more thermally stable than ZrRu, with HfRu-containing alloys demonstrating higher Ts,B2 at equivalent Ru concentrations. For alloys with Ts,B2 above 1200Image 1, additional anneals at 1000 and 1200Image 1 provide insight into B2 volume fraction variations with temperature. Additional Hf- and Zr-rich tertiary phases also formed on the grain boundaries of the selected compositions at intermediate to high temperatures. Through transmission electron microscopy, the lattice misfits for the B2 precipitates were found to be ≈ 0.5% at 1000Image 1 and the grain boundary phases were identified as C14 Laves, L10, β-Hf, and topologically close-packed P phases. Implications for the design of Nb-based alloys strengthened by Ru-B2 precipitates, including strategies to mitigate deleterious phase formation, are discussed throughout.

Refractory alloys can be difficult to fabricate by laser-based manufacturing methods due to their high melting temperatures, high interstitial solubility, and propensity for low temperature brittleness. Laser-based processes, such as welding and additive manufacturing (AM), yield similar populations of defects, including microsegregation and solidification and solid-state cracking. Given the extreme challenges and cost associated with the production of refractory powders, this research aimed to develop a rapid screening methodology that combines predictive defect formation metrics with single track melting experiments. A flexible single laser track melting platform was designed to perform screening experiments on conventional and multi-principal element refractory alloys across a wide range of laser energy inputs. The platform was employed to investigate laser melting on solid substrates, or on a substrate with a single layer of powder feedstock, and is demonstrated with the highly fabricable Nb-base alloy C103. Preliminary investigations are performed on refractory multi-principal element alloys in the Hf-Mo-Nb-Ta-Ti family, and significant differences in cracking resistance and solidification morphology are observed. Implications for future alloy design and processing strategies for defect-resistant refractory alloys for AM are discussed.

Additive manufacturingAdditive manufacturing enables the fabrication of complex part geometries, and is attractive for advanced aerospace components. Laser powder bed fusion (LPBF)Laser Powder Bed Fusion (LPBF), specifically, is being assessed for manufacturing structural components of gas-turbine engines made from high- ^' volume fraction superalloys. However, the formation of crack defects during LPBFLaser Powder Bed Fusion (LPBF) of nearly all superalloys within this class has undercut their mechanical performance greatly. This study builds on prior work examining the cracking susceptibility of high- ^' volume fraction superalloys during LPBF by simplifying the LPBF process down to single track laser meltingLaser melting scans. The CoNi-base alloy GammaPrint-700 is utilized in this study, as the cracking resistance of the alloy can be controlled through the boronBoron content. A means of improving the cracking resistance of the alloy through homogenization treatments prior to laser meltingLaser melting was identified. Characterization of the single tracks reveals a possible mechanism of crack initiationCrack initiation via liquation cracking of grain boundariesGrain boundary in the substrate material, and propagation via solidification crackingSolidification cracking along grain boundariesGrain boundary in the melt pool. Additionally, a protocol for assessing the cracking resistance while developing new high- ^' volume fraction superalloys for additive manufacturingAdditive manufacturing is discussed.

Laser powder bed fusion (LPBF)Laser Powder Bed Fusion (LPBF) printing defects are investigated through multimodal 3D serial sectioningSerial sectioning data on a model CoNi alloy. Defect segmentation across three different LPBF prints with different scan strategies, in which interlayer rotation and the presence of a contour scan is varied, reveal fully dense microstructuresMicrostructure (>99.8 m, beyond the resolution capabilities of most industrial non-destructive evaluation techniques. A comparison between 3D and 2D defects measurements is included, revealing significant variability between 2D measurements and the ground truth 3D data. A state-of-the-art machine learningMachine learning framework, U-Net, is implemented for defect segmentation within three TriBeam tomography datasets containing backscattered electron images with variable contrast conditions. U-Net results indicate high-fidelity defect segmentation within all three datasets where recall and precision are >85

A newly developed CoNi-based superalloy is demonstrated to be tolerant of a wide range of laser powder bed fusion print conditions, with limited defect content and high relative densities. These promising traits motivated investigation of the structural uniformity in samples printed at the upper end of the scan velocity processing window (>1000 mm/s). A new misorientation metric, starting reference orientation deviation (SROD), was calculated from mm(3)-scale 3D microstructure information to examine structure evolution during epitaxial growth of columnar grains. Misorientations of >20(degrees) were observed within the large columnar grains that grew through multiple build layers. The SROD observations highlight the CoNi superalloy's ability to plastically deform to high levels, as evidenced by misorientation gradients, across the range of temperatures experienced in laser additive manufacturing. Misorientation gradients within the columnar grain structure are high relative to Ni base superalloys, allowing for strengthening with high volume fractions of L1(2) precipitates.

The dynamics of laser spot melting and metallic alloy solidification are investigated through synchrotron x-ray radiography, 3D electron backscatter diffraction data, and computational fluid dynamics (CFD) simulations on a model NiMoAl alloy. Solidification velocities are measured from in-situ images to validate a CFD model of the spot melt. TriBeam tomography is used to reconstruct the melt pool in 3D, characterize the microstructure, and validate the CFD model melt pool dimensions. 3D geometrically necessary dislocation (GND) density calculations reveal extensive deformation at the sample surface. GND calculations integrated with the CFD model reveal that the halo of small, equiaxed grains adjacent to the fusion line is a result of recrystallization that occurred in the heat affected zone. By combining in-situ and ex-situ data modalities across a variety of temporal and spatial length scales, the microstructure formation mechanisms and their relationship to melt pool solidification are quantified.

This study investigates the role of geometrically necessary dislocations (GNDs) and microstructure on void nucleation and growth in wrought and additively manufactured (AM) tantalum subjected to high-strain rate loading. Multi-modal 3D data was collected using TriBeam tomography to calculate GND densities and their spatial relationship to voids. A microstructural comparison between the wrought and AM samples identified distinct void shapes and locations, with intragranular voids and more spherical voids frequently observed in the AM dataset. Results indicate that voids preferentially form at both high-angle grain boundaries and low-angle subgrain boundaries, the latter of which are frequently observed in the AM material. Through a radial distribution analysis of all voids in the datasets, significant GND localization to near-void-surface regions was observed in both samples. 3D crystal plasticity simulations were employed to extend the experimental observations, revealing higher void growth rates in [111] oriented grains when compared to [001] grains. The simulations also suggest that GNDs can be generated as part of the void growth process, with more GND accumulation for growth in a [111] grain than a [001] grain. These findings provide valuable insights into the links between nanoscale void nucleation, mesoscale void growth, and microstructural effects in dynamically loaded tantalum.

Geometrically necessary dislocation (GND) content is measured from mm3-scaled Ti7Al three-dimensional (3D) microstructural data using a theory extended for hexagonal close packed crystals, which accounts for basal, prismatic and pyramidal < c+a > type dislocation content. The Ti7Al samples have been mechanically pre-strained to two different strain levels, and will then be strained along the same axis in uniaxial tension during simulation. Both inter- and intragranular GNDs across the microstructures have been characterized, with a large contribution of pyramidal < c+a > GNDs, consistent with the relative slip activity involved in pre-straining. The spatially resolved crystallographic GND distributions within the 3D microstructures are used to instantiate a microstructure model for forward modeling deformation simulations by a dislocation density hardening elasto-viscoplastic fast Fourier transform framework. Coarsening the voxel resolution during the initial microstructure construction procedure is shown to strongly impact both the magnitude and spatial distribution of the GNDs and in turn the forward deformation response of the pre-strained material. This study indicates that the voxel resolution desired when transferring from measured to model microstructures need not only be proportionally scaled with the microstructure but also sufficiently fine to capture the subgranular orientation gradients that may already be present in the material.

Intermetallics with crystals derived from body-centered cubic structures are promising materials to enhance the performance and high temperature capability of high-strength alloys both as matrix materials and as strengthening precipitates. Given the ordered nature of these materials, the defect structures that ultimately mediate plasticity can be complex and strongly dependent on processing vis-à-vis the extent of disorder inherited from high temperature phases. Here, we elucidate the elementary characteristics of the defect structures in the Heusler (L21) intermetallic MnCu2Al as investigated by the orientation-dependent strength and compressive plasticity measured from in situ micro-compression experiments and post-mortem transmission electron microscopy. Our experiments reveal single crystal compressive yield strengths as high as 1.2 GPa and a capacity for stable plastic deformation, accompanied by slip characteristics reminiscent of bcc-derived crystals. We study the equilibrium dissociation mechanisms and critical stresses of 〈111〉{110}-type dislocations in the Heusler intermetallic using an ab initio informed phase field dislocation dynamics model. The calculations suggest that the dislocation dissociates into multiple distinct partials, which depend on the character of the dislocation, and are closely spaced to a degree that intervening faults are undetectable using conventional transmission electron microscopy. Critical stresses to initiate glide of these defect structures quantitatively agree with measured yield strengths. Our work details the interplay between the significant degree of elastic anisotropy, stacking fault energies, and glissile defect structures governing mechanical properties and motivates an increased awareness of the role that complex defect structures play for alloy design involving bcc-derived intermetallics.

Journal Article Merging Machine Learning and TriBeam Tomography for 3D Defect Detection in an AM CoNi-Based Superalloy Get access James Lamb, James Lamb University of California Santa Barbara, Materials Department, Santa Barbara, CA, United States Corresponding author: jlamb@ucsb.edu Search for other works by this author on: Oxford Academic Google Scholar McLean Echlin, McLean Echlin University of California Santa Barbara, Materials Department, Santa Barbara, CA, United States Search for other works by this author on: Oxford Academic Google Scholar Andrew Polonsky, Andrew Polonsky Sandia National Laboratories, Materials Mechanics & Tribology, Albuquerque, NM, United States Search for other works by this author on: Oxford Academic Google Scholar Remco Geurts, Remco Geurts Thermo Fisher Scientific, Eindhoven, Netherlands Search for other works by this author on: Oxford Academic Google Scholar Kira Pusch, Kira Pusch University of California Santa Barbara, Materials Department, Santa Barbara, CA, United States Search for other works by this author on: Oxford Academic Google Scholar Evan Raeker, Evan Raeker University of California Santa Barbara, Materials Department, Santa Barbara, CA, United States Search for other works by this author on: Oxford Academic Google Scholar Aurelien Botman, Aurelien Botman Thermo Fisher Scientific, Hillsboro, OR, United States Search for other works by this author on: Oxford Academic Google Scholar Chris Torbet, Chris Torbet University of California Santa Barbara, Materials Department, Santa Barbara, CA, United States Search for other works by this author on: Oxford Academic Google Scholar Tresa Pollock Tresa Pollock University of California Santa Barbara, Materials Department, Santa Barbara, CA, United States Search for other works by this author on: Oxford Academic Google Scholar Microscopy and Microanalysis, Volume 28, Issue S1, 1 August 2022, Pages 862–863, https://doi.org/10.1017/S1431927622003828 Published: 01 August 2022

Streams of multimodal three-dimensional (3D) and four-dimensional (4D) data are revolutionizing our ability to design and predict the behavior of a broad array of advanced materials systems. Over the last 10 years, a new 3D imaging platform consisting of a femtosecond (fs) pulsed laser coupled with a focused ion beam scanning electron microscope (FIB SEM) has been developed by UC Santa Barbara in collaboration with Thermo Fisher Scientific (formerly FEI). The femtosecond-laser-enabled FIB SEM, called the TriBeam, has become one of the only 3D serial sectioning methods available that can gather millimeter-scaled multimodal datasets at sub- $$\mu $$ m voxel resolutions; these length scales are critical for many materials problems. Multimodal chemical, crystallographic, and morphological information can be gathered rapidly on a layer-by-layer basis and reconstructed in 3D. Large (gigabyte to terabyte scale) 3D datasets have been generated for a broad array of materials systems, including metallic alloys, ceramics, biomaterials, polymer- and ceramic-matrix composites, and semiconductors. The research tasks performed have resulted in a completely new design, operating with a dual-wavelength femtosecond-pulsed laser on a plasma focused ion beam (PFIB) platform.