Three-Dimensional Microstructure Reconstruction Using FIB-OIM

A new method for reconstructing a three-dimensional microstructure using the focused ion beam-orientation imaging microscopy (FIB-OIM) is introduced. The technique is important for the study of three-dimensional microstructures of materials because it can automatically align (register) a series of parallel sections with both topological information and orientation information at the sub-micrometer scale. Using voxel-based tessellation, a three-dimensional microstructure is reconstructed by registering each section. The application of the method to a cubic material is described and, based on the reconstruction, the grain shape and grain size distribution are characterized. Introduction Materials characterization is a crucial step in exploring microstructure-property relationships and, because of the opacity of most crystalline materials, it is conventionally based on data obtained from two-dimensional plane sections. Many problems related to the properties of materials such as corrosion, fatigue crack formation and fracture are three-dimensional in nature because most practical materials have a polycrystalline structure with tremendous complexity in the spatial arrangement of the microstructural units (grains, grain boundaries, orientations, particles and so on). Clearly, conventional two-dimensional characterization is not always sufficient to quantitatively describe the microstructure. Even though stereology can be used to deduce the three-dimensional microstructure from two-dimensional observations, its statistical approach inevitably requires various spatial and morphological assumptions about the defect structure [1]. Considerable effort has been made to reconstruct three-dimensional microstructures using serial sectioning in recent years [2-6]. Saylor et al. [2] have used serial sections to determine grain boundary energies over all five crystallographic parameters. Others have reconstructed microstructures while either automating the sectioning using the techniques based on the focused ion beam [4, 5] or using local orientation information obtained from a series of EBSD maps [6]. Recently, a new automated serial sectioning method for reconstructing three-dimensional microstructures using the focused ion beam-orientation imaging microscopy (FIB-OIM) was developed, giving a full description of both morphology and local orientation of the microstructures in three dimensions [7-10]. In this paper, we introduce an example of a reconstruction based on the registration of a set of electron back-scatter diffraction (EBSD) images acquired in a dual-beam instrument that combines ion beam milling with a scanning electron microscope. We then present selected characteristics of the reconstructed microstructure including grain morphology and grain size distribution. Reconstruction Procedure The figure below shows the EBSD maps of two adjacent layers from a series of cross-sections of a Ni-based alloy obtained through serial sectioning in a dual-beam system. The data was collected and provided by Air Force Research Laboratory (AFRL) using the FEI system. The number of serial sections was 96 and the area of each scanned section was about 50 μm. For both figures, the black and speckled regions represent the collection of scanned pixels where the EBSD system attempted to index a diffraction pattern but was not able to produce a solution. The central region with wellindexed points shows that a registration system based on orientation information must take into account the local quality of the data available. As illustrated in Fig. 1, the position of the region of reliable data did not remain constant from layer-to-layer. For the TSL system used in this instance, there are two indicators of quality, which are known as “confidence index” (CI) and “image quality” (IQ). CI varies between -1 (poor) and 1 (good) and experience suggests that values above about 0.1 are reliable. Examination of the IQ values for this specific example suggested that poorly indexed pixels had the IQ values smaller than 100. Fig 1. Inverse pole figure maps of two adjacent sections of a nickel-based alloy. The thick red lines illustrate the edges of the area with reliable data (left figure). Notice that the abrupt deviation of the area of reliable data in the next layer (right figure) from the thick red lines indicates how each layer drifts laterally during the milling and EBSD mapping. The registration was based on the assumption that the successive layers were sufficiently well aligned that the only adjustment required was the translation confined to integer valued shifts along x and y directions in each plane (i.e. the layers could be assumed to be parallel to one another, with no rotations between layers). We used the orientation information inherent in the EBSD maps to align the successive layers, which exhibited significant displacements relative to one another (See the figure above). The average disorientation (D) was calculated as shown in Eq. 1 as the average of the product of disorientation, ∆g, between each well-indexed pixel in the upper layer and its one or more neighboring pixels in the layer below and a weighting factor, w, that decreases the contribution to D from points in the layer below having a low confidence index and low image quality. The expectation is that good alignment will generate a small average disorientation between pixels in adjacent layers.