Stable isotope analysis of iron and oxygen isotopes in magnetite of Kiruna-type from Sweden and Chile have been conducted to further the understanding of the formation, and advance the analysis methods of these deposits. For this, data from SIMS (secondary ion mass spectroscopy), EBSD (electron backscatter diffraction) and triple oxygen analysis (by laser fluorination) are used. Some researchers have found that crystal orientation can affect the oxygen and iron isotope ratios when analysing magnetite by SIMS, complicating the process. EBSD analysis therefore aided by finding the orientations of the crystals prior to SIMS analysis. Magnetite from Kiruna have been tested for use as SIMS reference material, but it did not prove to be suitable at present time. Further homoegeneity tests can be useful before declaring the sample as unsuitable. Preliminary iron isotope results from SIMS on magnetite from Kiirunavaara indicate an internal variation of δ 56 Fe between -0.72-0.70 per mil, with an uncertainty of 0.38 per mil (1σ). The variations could not be determined to match crystal orientations. Triple oxygen analyses show very low ∆'17 O on Kiruna samples, -357 to -171 ‰, indicating a strong MIF-O (mass-independently fractionated oxygen isotope composition) component. The MIF-O signal is also present in ∆'17 O records in evaporites from similar ages (1.7 - 1.9 Ga) (Crockford et al. 2019), which are known to partly contain oxygen derived from atmospheric O 2 . The MIF-O signal was not present in the Chilean magnetite samples, however, they are within the ∆'17 range of evaporites (Crockford et al.2019) from a similiar age (0 Ma vs 2 Ma). It is proposed that magmatic fluids interacted with evaporites, exchanging oxygen isotopes, before forming magnetite of Kiruna-type, thereby allowing the magnetite to contain part of the atmospheric isotopic record.

Extended plasticity mechanisms (EPM) allow a metal to undergo extended plastic deformation without failure. These mechanisms are responsible for the extended plastic deformation characteristic of hot working processes. In this thesis it is shown that electron backscatter diffraction (EBSD) is capable of detecting EPM artifacts in the final microstructure of AISI 304L stainless steel (304L). Results also indicate that dislocation cells form in hot worked AISI 304L stainless steel. Additionally, in this study EBSD data collection and analysis is used with a design of experiments approach to model the presence of EPM artifacts in the final microstructure of friction stir welded 304L. Texture analysis of the welded material reveals a dominant shear deformation texture and a lack of the rotated cube texture. The shear deformation texture is characteristic of dynamic recovery (DRV) and continuous dynamic recrystallization (CDRX), while the rotated cube texture is characteristic of discontinuous dynamic recrystallization (DDRX). The texture analysis results indicate that dynamic recovery (DRV) and continuous dynamic recrystallization (CDRX) play a role in the final microstructure of the welded material, while DDRX does not. Design of experiments was used to find the relationships between the fraction of cell boundaries and spindle speed, travel speed, location in the stir zone, and tool temperature. The regression analyses reported that predicted fraction of cell boundaries were relatively high (approximately 0.70 or more) and changed by less that 20% in the stir zone and 10% in the TMAZ. The relatively high predictions indicate that in FSW 304L DRV dominates and limited CDRX occurs. The small changes in predictions across the experimental space indicate that the effects, while statistically significant, are not practically significant. Finally, an alternate tool temperature basis was developed, which provides a valid method for selecting welds which should have constant tool temperature.

Cross-correlation based analysis of electron backscatter diffraction (EBSD) patterns and the use of simulated reference patterns has opened up entirely new avenues of insight into local lattice properties within EBSD scans. The benefits of accessing new levels of orientation resolution and multiple types of previously inaccessible data measures are accompanied with new challenges in characterizing microscope geometry and other error previously ignored in EBSD systems. The foremost of these challenges, when using simulated patterns in high resolution EBSD (HR-EBSD), is the determination of pattern center (the location on the sample from which the EBSD pattern originated) with sufficient accuracy to avoid the introduction of phantom lattice rotations and elastic strain into these highly sensitive measures. This dissertation demonstrates how to greatly improve pattern center determination. It also presents a method for the extraction of grain boundary plane information from single two-dimensional surface scans. These are accomplished through the use of previously un-accessed detail within EBSD images, coupled with physical models of the backscattering phenomena. A software algorithm is detailed and applied for the determination of pattern center with an accuracy of ~0.03% of the phosphor screen width, or ~10µm. This resolution makes it possible to apply a simulated pattern method (developed at BYU) in HR-EBSD, with several important benefits over the original HR-EBSD approach developed by Angus Wilkinson. Experimental work is done on epitaxially-grown silicon and germanium in order to gauge the precision of HR-EBSD with simulated reference patterns using the new pattern center calibration approach. It is found that strain resolution with a calibrated pattern center and simulated reference patterns can be as low as 7x10-4. Finally, Monte Carlo-based models of the electron interaction volume are used in conjunction with pattern-mixing-strength curves of line scans crossing grain boundaries in order to recover 3D grain boundary plane information. Validation of the approach is done using 3D serial scan data and coherent twin boundaries in tantalum and copper. The proposed method for recovery of grain boundary plane orientation exhibits an average error of 3 degrees.

The application of high resolution electron backscatter diffraction (HR-EBSD) techniques has been used in order to study the evolution of geometrically necessary dislocation (GND). The tested materials were taken from AZ31 magnesium sheet which had strong basal texture. Because of low symmetry of the magnesium crystal lattice, the von Mises criteria cannot be satisfied by the three independent, easily activated, basal slips. The strain along the c-axis of the crystal must be accommodated by either twinning and/or slip systems. HR-EBSD data was taken in order to investigate these phenomena. The HR-EBSD results were post processed in order to resolve total GND density onto the observed possible slip systems. The first chapter of the investigation focused on the correlation between resolved GNDs with tensile twin nucleation, and the subsequent propagation path in the microstructure. For this purpose, 2.5 % strain was applied in a uniaxial compression test along the transverse direction (TD). Several fine scan were done at the boundaries where twin formed. The results show that in order for a twin to nucleate spontaneously at the grain boundaries, two criteria should generally be met: high angle grain boundaries (35-45°) and pile ups of basal slip system in neighboring grain at the other side of the boundary. Furthermore, once nucleation has initiated, twin propagation can occur through low angle grain boundaries (15-25°); if a twin reaches a high angle boundary, it will generally terminate at the boundary at low strain levels. A twin may pass through high angle boundaries with further deformation. In the second chapter, deformation of the AZ31 magnesium alloy was study for different strain paths. For this purpose, compression and tension in-situ tests were done and the texture and GND evolutions were investigated. The results show that the load paths, compression and tension, evolve the microstructure in different ways. Massive twin fractions were formed in compression, and higher GND contents were observed in tension tests. It was observed that at higher strain levels GND contents are roughly independent of the initial texture but the activation of slip systems at low strain strongly depends on initial structure. If the samples were loaded along RD, GND density increased sharply at low strain. In contrast, for the samples loaded along TD, GND increased moderately. A small amount of repetition is apparent in the two parts of the thesis due to them being formatted for individual publication as journal papers.

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Metal additive manufacturing (AM) provides a platform for microstructure optimization via process control, the ability to model the evolution of microstructures from changes in processing condition or even predict the microstructures from given processing condition would greatly reduce the time frame and the cost of the optimization process. In 1, we present a deep learning framework to quantitatively analyze the microstructural variations of metals fabricated by AM under different processing conditions. We also demonstrate the capability of predicting new microstructures from the representation with deep learning and we can explore the physical insights of the implicitly expressed microstructure representations. We validate our framework using samples fabricated by a solid-state AM technology, additive friction stir deposition, which typically results in equiaxed microstructures. In 2, we further improve and generalize the generating framework, a set of metrics is used to quantitatively analyze the effectiveness of the generation by comparing the microstructure characteristics between the generated samples and the originals. We also take advantage of image processing techniques to aid the calculation of metrics that require grain segmentation. / Master of Science / Different from the traditional manufacturing technique which removes material to form the desired shape, additive manufacturing (AM) adds material together to form the shapes usually layer by layer. AM which is sometimes also referred to as 3-D printing enables the optimization of material property through changing the processing conditions. The microstructure is structures formed by materials on a microscopic scale. Crystals like metal usually form a crystalline structure composed of grains where atoms have the same orientation. Especially for metal AM, changes in the processing condition will usually result in changes in microstructures and material properties. To better optimize for the desired material properties, in 1 we present a microstructure representation method that allows projection of microstructure onto the representation space and prediction from an arbitrary point from the representation space. This representation method allows us to better analyze the changes in microstructure in relation to the changes in processing conditions. In 2, we validate the representation and prediction using EBSD data collected from copper samples manufactured with AM under different processing conditions.

Particle accelerators are a leading tool for frontier science. Pushing that frontier further demands more machines with higher performance, and more of a very expensive technology: superconducting radio-frequency (SRF) acceleration. From a materials perspective this means reducing residual surface resistance or raising the operating temperature (currently ~2 K) of SRF cavities. Both are pursued by materials modification: nitrogen doping/infusion in the first instance and coating with Nb3Sn in the second. Materials characterization is key to achieving understanding and directing RandD. However, very little has been done. This present work aims to fill the knowledge gap and to provide needed, validated tools to the accelerator science community. In this connection, SIMS, XPS and EBSD have proven especially valuable and represent the majority of discussion in this dissertation. / Doctor of Philosophy / Particle accelerators are a powerful tool that helps us expand our knowledge of science and how the universe works. Pushing that knowledge further requires us to use more and more powerful particle accelerators. Particle accelerators are based on a very expensive technology: superconducting radio-frequency (SRF) cavities. These cavities are hollow tubes made from niobium and shaped in such a way as to cause electromagnetic waves to form. These waves are what are used to accelerate particles. The energy input and loss of energy as heat are massive resulting in millions of dollars a year in electric bills at particle accelerator facilities. In order to build bigger and more powerful particle accelerates they most be more efficient or they become prohibitively expensive. In this dissertation I look at several next generation materials used in building particle accelerators. In particular I describe and go into detail about how to characterize these materials. In other words, how we determine the materials properties and how those properties affect the performance.