Wootz steel project by electron backscatter diffraction

The data is from an electron backscatter diffraction (EBSD) study of the microstructure of high carbon ‘Wootz’ steel. The objective of the study is to infer an unknown thermomechanical history from observation and analysis of the final microstructure in various ancient artefacts (swords and tools), and then compare the findings with heat treatments of the ancient artefacts and modern attempts at duplication of the structure. Electron backscatter data reveals the orientation relationships between various phases in the material, particularly cementite and ferrite.

Electron backscatter diffraction (EBSD) map of AZ31 compressed to 1% strain at room temperature in a direction parallel to the extrusion direction

The collection contains an EBSD map of AZ31 compressed to 1% strain at room temperature in a direction parallel to the extrusion direction. The map was collected as part of an investigation into the role of twinning in the occurrence of a yield point elongation during deformation.

Evaluation of four supervised learning methods for benthic habitat mapping using backscatter from multi-beam sonar

An understanding of the distribution and extent of marine habitats is essential for the implementation of ecosystem-based management strategies. Historically this had been difficult in marine environments until the advancement of acoustic sensors. This study demonstrates the applicability of supervised learning techniques for benthic habitat characterization using angular backscatter response data. With the advancement of multibeam echo-sounder (MBES) technology, full coverage datasets of physical structure over vast regions of the seafloor are now achievable. Supervised learning methods typically applied to terrestrial remote sensing provide a cost-effective approach for habitat characterization in marine systems. However the comparison of the relative performance of different classifiers using acoustic data is limited. Characterization of acoustic backscatter data from MBES using four different supervised learning methods to generate benthic habitat maps is presented. Maximum Likelihood Classifier (MLC), Quick, Unbiased, Efficient Statistical Tree (QUEST), Random Forest (RF) and Support Vector Machine (SVM) were evaluated to classify angular backscatter response into habitat classes using training data acquired from underwater video observations. Results for biota classifications indicated that SVM and RF produced the highest accuracies, followed by QUEST and MLC, respectively. The most important backscatter data were from the moderate incidence angles between 30° and 50°. This study presents initial results for understanding how acoustic backscatter from MBES can be optimized for the characterization of marine benthic biological habitats. © 2012 by the authors.

Wootz steel project by electron backscatter diffraction

The data is from an electron backscatter diffraction (EBSD) study of the microstructure of high carbon ‘Wootz’ steel. The objective of the study is to infer an unknown thermomechanical history from observation and analysis of the final microstructure in various ancient artefacts (swords and tools), and then compare the findings with heat treatments of the ancient artefacts and modern attempts at duplication of the structure. Electron backscatter data reveals the orientation relationships between various phases in the material, particularly cementite and ferrite. The dataset is randomly structured and organised. The data is automatically generated by an electron backscattered diffraction system attached to a field emission scanning electron microscope. The dataset uses proprietary software (cannot be copied or distributed without complying with licensing agreements): Oxford HKL Channel 5. As the native formats are binary they cannot be read with standard software.

Grain boundary segregation in Fe-Mn-C twinning-induced plasticity steels studied by correlative electron backscatter diffraction and atom probe tomography

We report on the characterization of grain boundary (GB) segregation in an Fe-28Mn-0.3C (wt.%) twinning-induced plasticity (TWIP) steel. After recrystallization of this steel for 24 h at 700 °C, ∼50% general grain boundaries (GBs) and ∼35% Σ3 annealing twin boundaries were observed (others were high-order Σ and low-angle GBs). The segregation of B, C and P and traces of Si and Cu were detected at the general GB by atom probe tomography (APT) and quantified using ladder diagrams. In the case of the Σ3 coherent annealing twin, it was necessary to first locate the position of the boundary by density analysis of the atom probe data, then small amounts of B, Si and P segregation and, surprisingly, depletion of C were detected. The concentration of Mn was constant across the interface for both boundary types. The depletion of C at the annealing twin is explained by a local change in the stacking sequence at the boundary, creating a local hexagonal close-packed structure with low C solubility. This finding raises the question of whether segregation/depletion also occurs at Σ3 deformation twin boundaries in high-Mn TWIP steels. Consequently, a previously published APT dataset of the Fe-22Mn-0.6C alloy system, containing a high density of deformation twins due to 30% tensile deformation at room temperature, was reinvestigated using the same analysis routine as for the annealing twin. Although crystallographically identical to the annealing twin, no evidence of segregation or depletion was found at the deformation twins, owing to the lack of mobility of solutes during twin formation at room temperature.

Integrating multibeam backscatter angular response, mosaic and bathymetry data for benthic habitat mapping

Multibeam echosounders (MBES) are increasingly becoming the tool of choice for marine habitat mapping applications. In turn, the rapid expansion of habitat mapping studies has resulted in a need for automated classification techniques to efficiently map benthic habitats, assess confidence in model outputs, and evaluate the importance of variables driving the patterns observed. The benthic habitat characterisation process often involves the analysis of MBES bathymetry, backscatter mosaic or angular response with observation data providing ground truth. However, studies that make use of the full range of MBES outputs within a single classification process are limited. We present an approach that integrates backscatter angular response with MBES bathymetry, backscatter mosaic and their derivatives in a classification process using a Random Forests (RF) machine-learning algorithm to predict the distribution of benthic biological habitats. This approach includes a method of deriving statistical features from backscatter angular response curves created from MBES data collated within homogeneous regions of a backscatter mosaic. Using the RF algorithm we assess the relative importance of each variable in order to optimise the classification process and simplify models applied. The results showed that the inclusion of the angular response features in the classification process improved the accuracy of the final habitat maps from 88.5% to 93.6%. The RF algorithm identified bathymetry and the angular response mean as the two most important predictors. However, the highest classification rates were only obtained after incorporating additional features derived from bathymetry and the backscatter mosaic. The angular response features were found to be more important to the classification process compared to the backscatter mosaic features. This analysis indicates that integrating angular response information with bathymetry and the backscatter mosaic, along with their derivatives, constitutes an important improvement for studying the distribution of benthic habitats, which is necessary for effective marine spatial planning and resource management.

Recrystallization textures in course grained low carbon and interstitial free steels

The microstructures and textures of coarse grained cold rolled, partially recrystallized and fully recrystallized low carbon and interstitial free steel were examined by optical microscopy, scanning electron microscopy (SEM) and electron backscatter diffraction (EBSD). The recrystallization textures of the two grades are markedly different, with the low carbon steel having a predominantly Goss {11O}<OOl> texture and the interstitial free steel having a <1ll>/1ND texture with a strong {III }<112> component. One possible explanation for the texture difference is that less severe localization of flow during deformation of interstitial free steels causes less Goss nuclei to be generated. While some support for this view is provided by the results presented in this paper, the results suggest that another mechanism may be at least partially responsible. Examination of micro
shear bands on the surface of pre-polished samples showed that a higher proportion of micro shear bands remained active at high rolling reductions in the low carbon steel, compared with the interstitial free grade. Regions of Goss orientation within bands that have ceased to operate rotate to
near-{ III }<112> orientations with further deformation. Consequently, the recrystallization texture of coarse grained interstitial free steels can be rationalized by a reduction in the availability of Goss nuclei and an increase in the availability of {Ill }<112> nuclei due to a "Goss to {Ill }<112>" rotation within micro shear bands that have ceased to operate.

Fragmentation of orientation within grains of a cold-rolled interstitial-free steel

The formation of a favourable recrystallization texture in interstitial-free (IF) steels depends on the availability and activation of particular nucleation sites in the deformed microstructure. This paper presents a description of the deformed microstructure of a commercially cold-rolled IF steel, with particular emphasis on the microstructural inhomogeneities and short-range orientational variation that provide suitable nucleation sites during recrystallization. RD-fibre regions deform relatively homogeneously and exhibit little short-range orientational variation. ND-fibre regions are heavily banded and exhibit considerable short-range orientational variation associated with the bands. While the overall orientational spread of ND-fibre grains frequently is about the ND-axis, the short-range orientational variation often involves rotation about axes in the TD-ND plane that are nearer to the TD than the ND.

On the production of randomly-oriented recrystallization nuclei for selective growth experiments

The ideal starting condition for selective growth experiments is one having a layer of randomly-oriented nuclei adjacent to a matrix with negligible orientational variation but sufficient stored energy to promote growth. In practice, cutting or deformation processes are used in an attempt to approximate these ideal conditions, but the degree to which this is achieved has not been rigorously quantified. In this work, Fe-3wt%Si single crystals were cut or deformed using six different processes. The variation in texture with distance from the cut or deformed surface was measured using electron backscatter diffraction (EBSD) in a field emission gun scanning electron microscope (FEG-SEM) in order to assess the ability of each process to create conditions suitable for selective growth experiments. While grooving with a machine tool produced the best spread of orientations at the cut surface, the suitability of this process is diminished by the presence of a differently-textured deformed layer between the cut surface and the single crystal matrix. Grinding produced a less ideal distribution of orientations at the cut surface, but the presence of these orientations in a very thin layer adjacent to the matrix makes this process preferable for preparing crystals for selective growth experiments, provided the results are corrected for the deviation in the distribution of nuclei orientations from a random distribution.