ONLINE | TMS
PUBLICATIONS | SITE
An Article from the October 2003 JOM: A Hypertext-Enhanced Article
|Jonathan E. Spowart is with UES Incorporated in Dayton, Ohio; Herbert E. Mullens is with Wright State University in Dayton, Ohio; and Brian T. Puchala is with the University of Michigan in Detroit, Michigan.||
Exploring traditional, innovative, and revolutionary issues in the minerals, metals, and materials fields.
|OUR LATEST ISSUE|
TABLES OF CONTENTS
JOM TECHNICAL DIRECTORY
TMS WEBCAST HOME
ABSTRACT SUBMISSION FORM
RESERVE A CLASSIFIED
SINGLE ISSUE PURCHASES
LETTER TO EDITOR
Overview: Modeling and Characterization
Collecting and Analyzing Microstructures in Three Dimensions: A Fully Automated Approach
Figure 1. A macrograph of a “freckle chain” on the surface of a single-crystal superalloy casting. The solidification direction is <100>, which is horizontal in the figure.
Recent advances in computing power
have enabled the development of 3-D
microstructural models on all length
scales from atomistic simulations to
dislocation-dislocation interactions, 3-D
crystal plasticity models for deformation,
and 3-D fracture mechanics for
Serial sectioning is a well-established technique for obtaining 3-D microstructural data. In its simplest form, the technique involves the careful removal of a layer of material, followed by imaging of the freshly created surface. This is repeated many times in order to build up a series of two-dimensional (2-D) images (slices) which is then reconstructed (i.e., stacked) to form a data volume.
In the past, layer removal has been done by hand, using standard metallographic polishing techniques. This is a very delicate and time-consuming operation. In addition, the minimum slice thickness that can be repeatedly obtained in practice is 5–10 µm. Since a fundamental limitation of the serial sectioning technique is that features smaller than the minimum slice thickness will be missed, this places serious limitations on resolution. Furthermore, the repeated removal of a fixed depth of material by hand is challenging in a practical sense, and the accuracy of the final 3-D data volume depends entirely on the well-controlled removal of material in each slice. Add to this the time needed to carefully align and assemble the individual 2-D images and the prospect of obtaining a data volume comprising a few hundred slices becomes a daunting one.
Freckle Defects in Single-Crystal Ni-Superalloys
Recently, the Air Force Research
Laboratory’s Materials and Manufacturing
Directorate and UES, Incorporated demonstrated the capabilities of the
machine by using automated serial-sectioning
to extract the 3-D microstructural
features of freckle defects in an
experimental nickel-based superalloy
casting. Freckles are casting defects that
result in separate grains or sub-grains
on the surface of a single crystal or
directionally solidified casting. The
surface features often occur in “freckle
chains” extending along the solidification
direction, as shown in Figure 1.
Misoriented regions on the surface of the casting indicated the presence of complex sub-surface features that can extend deep into the interior of the crystal. After automated serial sectioning (130 slices, with a slice thickness of 2.7 ± 0.1 µm), the main body of the freckle is shown to be much larger than apparent on the surface (Figure 2, which is also available for viewing on-line as a QuickTime movie). The freckle region appears to be separated into smaller sub-domains, each with a slightly different crystallographic orientation. Nickel-based superalloys have been well documented1 as both elastically and plastically anisotropic. It is therefore likely that the effect of the spatial arrangement of these sub-domains coupled with their individual crystallographic orientations will strongly influence the stress state within the freckle. The 3-D information gathered in this study will therefore form part of a modeling effort to identify the combined effects of morphology and orientation on the criticality of freckle defects under specific loading conditions.
Figure 2. A 3-D rendering showing an 80 µm thick central region of a freckle defect in an experimental superalloy casting. The figure shows the spatial arrangement of different crystallographic sub-domains within the main freckle region as different gray levels. The largest sub-domain shows remnants of a dendrite structure, suggesting its origin as a dendrite tip from earlier in the casting process. The broken line shows the surface of the cylindrical casting.
Figure 3. A surface rendering of extruded DRA 2009/SiC/15p microstructure. The extrusion direction is parallel to the z axis.
Figure 4. A surface rendering of 3-D models of an individual SiC particle, comprising 35 serial section slices. Spacing between slices = 0.16 ± 0.01 µm.
|Click Here to view this three-dimensional figure as a movie (.mov) using QuickTime (~800 kb).||Click Here to view this figure as a 3-D movie as a .mov file using QuickTime (~15 Mb).||Click Here to view this figure as a 3-D movie as a .mov file using QuickTime (~15 Mb).|
dmax > 1.5dmin, dmax> 1.5dmid
dmax> 1.5dmin, dmax< 1.5dmid,
and dmid> 1.5dmin
and dmid< 1.5dmin
* Based on ratios of measured caliper diameters.
Figure 5. A histogram showing statistics of particle alignment, obtained from 3-D morphological data from a sample population of 100 SiC particles.
3-D Metallography of Discontinuously Reinforced Aluminum
Discontinuously reinforced aluminum (DRA) is a material system with a broad range of applications in ground transportation, thermal management, and both military and commercial aerospace, due in part to improvements in process control leading to well-characterized materials with improved mechanical and physical properties. In this context, the spatial arrangement (spacing and orientation) of reinforcement phases is of particular interest. It has been established through experimentation that the spatial distribution and/or morphology of the reinforcement has a strong influence on the mechanical properties of the final material.2,3 However, the influence of particle orientation on the anisotropy of mechanical properties is less tractable beccause it is experimentally difficult to measure.
Robo-Met.3D was used to automatically serial-section the 2009/SiC/15p DRA material using a slice thickness of 0.16 ± 0.01 µm. The total volume of material sectioned was 280 µm × 210 µm × 20.5 µm (1.2 µm × 106 µm3), with the sectioning done along the extrusion direction. It is possible to obtain large fields of view such as this by using an image montage technique to form a single, large image that has both high resolution and high spatial coverage. Figure 3 (which is also available for viewing on-line as a 3-D movie) shows a typical sub-volume (~3 µm × 104 µm3) of the DRA data set obtained via automated serial sectioning. In this rendering, the aluminum-alloy matrix phase is made transparent so that the SiC particles are clearly visible, with the extrusion direction parallel to the z axis.
The ability to capture a large field
of view at a high resolution is key to
providing a reasonably sized population
of microstructural features for statistical
analysis. A sample population of 100
particles was identified. The individual
particle sections were then carefully
cropped out of the 2-D slices and
reconstructed as individual 3-D models
(Figure 4, which is also available for viewing on-line as a 3-D movie).
In the analysis that follows, a and b are the caliper diameters parallel to the x and y axes and c is the measured caliper diameter parallel to the z axis. Typically the three measured caliper diameters can be ranked according to size, as dmax, dmid, and dmin. However, in some instances, dmid and dmin are measured to be the same within the resolution of the technique. In order to ascertain the influence of particle morphology on particle rotation during processing, a scheme was adopted for classifying the particle morphologies according to the ratios between their measured caliper diameters. For example, particles were classified as “rods” if the ratios between dmax and each of the other two dimensions (dmid and dmin) were calculated to be greater than a critical ratio of 1.5 (Table I). The particles were further classified as being either “well aligned” or “badly aligned” depending on whether dmax was parallel to the extrusion axis or not. Figure 5 is a histogram showing the percentages of well-aligned and badly aligned particles as a function of their morphology.
The presence of well-aligned particles in the extruded product (especially the rods and plates) suggests substantial particle rotation occurs during extrusion processing and the extent of rotation is a function of the morphology of the particles themselves. This information is valuable for conducting process modeling of these materials and is unobtainable by using standard statistically based 2-D stereological methods.
The Case for Automation
From the previous discussion, it is clear that the drive for automating the layer-removal
step is already quite strong; however, Robo-Met.3D was also designed to fully automate
the three-dimensional (3-D) data-volume generation process, from specimen preparation
and polishing to digital image capture and 3-D reconstruction. At the heart of the machine
is a high-end personal computer (PC) station running custom-written code that controls
a robotic arm used to translate a specimen between the metallographic polishing unit
and a fully automated optical metallograph. The PC also runs the image capture and 3-D
reconstruction software. Chemical etching is carried out automatically, increasing the
number of material systems that can be investigated (e.g., nickel-superalloy specimens
are routinely etched in this manner). The application of advanced automation techniques
represents a significant advance in serial sectioning, reducing the time to acquire data
volumes by around two orders of magnitude compared with manual techniques. The higher
data acquisition rates of Robo-Met.3D enable the systematic study of microstructural
evolution and trends so that the influence of such factors as heat treatment, deformation
processing, and damage evolution can be investigated. Rather than being limited to academic
research, 3-D microstructural analysis is now also a feasible technique for manufacturing
quality control, real-time failure analysis, and a host of other functions.
The current and projected capabilities of the Robo-Met.3D system are shown in Table A. Among the material systems that have been investigated, two systems with very different length scales stand out; one is an experimental single-crystal cast nickel superalloy, and the other is a commercially available 2009/SiC/15p discontinuously reinforced aluminum (DRA) composite material comprised of 15 vol.% SiC particles in a 2009 aluminum-alloy matrix. Each of these systems presents different and specific challenges to serial sectioning. The Robo-Met.3D system, which uses metallographic polishing to obtain the serial sections, offers greater flexibility than other techniques such as micro-milling, which tend to be limited in terms of the material systems that can be sectioned. Robo-Met.3D can rapidly produce the series of 2-D images needed for 3-D reconstruction of the data volume for any single polished surface that can be produced using standard metallographic polishing techniques.
This work was supported in part by the Air Force Office of Scientific Research under Task 01ML05-COR (Craig S. Hartley, program manager). In addition, the authors thank the following individuals for technical discussions and support during this research: Daniel B. Miracle, Michael D. Uchic, Clayton A. Smith, and Tresa M. Pollock, who supplied the Ni-6.8Al-6.2Ta-0.14Hf- 2.4W-4.6Re-1.5Mo-7.0Cr-7.5Co alloy used in this study.
1. C.T. Sims, N.S. Stoloff, and W.C. Hagel, eds.
Superalloys II (New York: Wiley, 1987).
2. J.E. Spowart, Z.-Y. Ma, and R.S. Mishra, “The Effect of Friction Stir Processing (FSP) on the Spatial Heterogeneity of Discontinuously Reinforced Aluminum (DRA) Microstructures,” Friction Stir Welding and Processing, ed. K.V. Jata, M. Mahoney, and R.S. Mishra (Warrendale, PA: TMS, 2003), pp. 243–252.
3. J.E. Spowart and D.B. Miracle, “The Influence of Reinforcement Morphology on the Tensile Response of 6061/SiC/25p Discontinuously Reinforced Aluminum,” Mater. Sci. Eng., A357 (2003), pp. 111–123.
For more information, contact J.E. Spowart, UES Incorporated, AFRL/MLLM Bldg. 655, 2230 Tenth Street, Suite 1, Wright-Patterson AFB, Ohio 45433; (937) 255-1340; fax (937) 255-3007; e-mail Jonathan.Spowart@wpafb.af.mil.
Direct questions about this or any other JOM page to firstname.lastname@example.org.
|Search||TMS Document Center||Subscriptions||Other Hypertext Articles||JOM||TMS OnLine|