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3D microstructural characterization of nickel superalloys via serial-sectioning using a dual beam FIB-SEM
Scripta Materialia 55 (2006) 23–28 www.actamat-journals.com
Viewpoint Paper
3D microstructural characterization of nickel superalloys via serial-sectioning using a dual beam FIB-SEM Michael D. Uchic,a,* Michael A. Groeber,b Dennis M. Dimiduka and J.P. Simmonsa a
Air Force Research Laboratory, Materials and Manufacturing Directorate, Wright-Patterson AFB, OH 45433, United States b The Ohio State University, Department of Materials Science and Engineering, Columbus, OH 43210, United States Received 7 November 2005; revised 8 February 2006; accepted 13 February 2006 Available online 27 March 2006
Abstract—Dual beam focused ion beam-scanning electron microscopes are well suited for characterizing micron and sub-micron size microstructural features in three dimensions via serial-sectioning procedures. Importantly, these commercially-available instruments can be used to collect morphological, crystallographic, and chemical information throughout a serial-sectioning experiment. Selected examples are shown to demonstrate these capabilities. 2006 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved. Keywords: Microstructure; Focused ion beam (FIB) microscopy
1. Introduction The study of microstructure in three dimensions (3D) is currently undergoing a revolutionary change in terms of the development and commercial availability of dedicated characterization systems, visualization software, and analysis methodologies. While scientists have been able to readily characterize some microstructural features in two dimensions (2D) using standard microscopy instrumentation and stereological procedures, there are many microstructural features that can only be measured in 3D, such as the number of features per volume, the true size and shape of microstructural features, and the connectivity between features [1]. The need to more accurately and quantitatively characterize microstructure has in large part stimulated the steady development of a suite of automated or nearly-autonomous instruments and methodologies that can characterize in 3D the local structure, chemistry, and/or crystallography of materials from the atomic scale extending all the way up to millimeter-size volumes. This includes devices and methods that are particularly suited for characterizing metals such as the 3D atom probe and local-electron atom probe [2,3], tomographic transmission electron microscopy [4,5], focused ion beam (FIB)
* Corresponding author. Tel.: +1 937 255 4784; fax: +1 937 255 3007; e-mail: [email protected]
serial-sectioning [6–10], synchrotron-based X-Ray diffraction [11,12], and mechanical polishing or micromilling serial-sectioning devices [13,14]. The continued refinement and application of these sophisticated instruments and methodologies will certainly advance the field of materials characterization. Of primary interest for modern mechanical property prediction programs is the ability to quantitatively characterize grain and precipitate-level microstructural features, in order to supply modeling and simulation efforts with high fidelity descriptions of microstructure [15]. These descriptions might consist of either direct or synthetic representations of microstructures in 3D, or statistical functions that describe microstructural feature distributions. In order to apply serial-sectioning methods to characterization of a particular feature class, a general rule of thumb is that one would like a minimum of 10–20 sections per feature to accurately represent its size and shape. Many engineering alloys have grains and precipitates that have dimensions on the order of a couple hundred nanometers to a few microns. The study of these features is ideally suited for FIB microscopes, as these systems are capable of focusing the ion beam to spot sizes smaller than 20 nm, and are able to control the position of the beam with nm-level accuracy. Single beam FIB microscopes have been previously demonstrated to be very capable systems for performing serial-sectioning experiments at the microscale, where
1359-6462/$ - see front matter 2006 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved. doi:10.1016/j.scriptamat.2006.02.039
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M. D. Uchic et al. / Scripta Materialia 55 (2006) 23–28
the FIB is used as a ‘‘nano-knife’’ to prepare a series of cross-sectional surfaces [6–10]. After cross-section milling the surface-of-interest is repositioned so that the FIB column can acquire a scanning ion microscope (SIM) image or collect a secondary ion mass spectroscopy map, and repeating this process multiple times forms the basis of a serial-sectioning experiment. With the advent of dual beam focused ion beam-scanning electron microscopes (DB FIB-SEMs), the incorporation of an electron column and associated analytical capabilities into the FIB microscope transforms this device into a much more capable serial-sectioning instrument. In this article we discuss the application of DB FIB-SEM microscopes to study microstructures in 3D, identify current limitations, and suggest areas for future development.
2. Dual beam FIB-SEM serial-sectioning methodology This section will briefly describe the DB FIB-SEM serial-sectioning methodology employed by the authors to study aerospace materials. All of the experimental work has been performed on a FEI Strata DB 235 microscope outfitted with a TSL orientation imaging microscopy system and EDAX electron dispersive spectroscopy system. Although details such as the microscope control scripts are specific to this instrumentation set, it is likely that the general techniques are applicable to other FIB-SEM instruments. A schematic of the geometry of the FIB and SEM columns and typical sample orientation for the serialsectioning experiment is shown in Figure 1(A), and an image of the typical sample geometry used in our laboratory is shown in Figure 1(B). The sample has been FIB micromachined prior to the serial-sectioning experiment into a cantilevered beam configuration [16]. This sample geometry is not required, as the serial-sectioning experiments can be performed at the surface of a bulk sample with only a small amount of pre-experiment micromachining (for example, see Refs. [9,10]). The advantages of the cantilever beam geometry include minimizing the redeposition of milled material onto the surface-ofinterest, eliminating the possibility of shielding the detectors for crystallographic or chemical analysis while mapping the entire surface-of-interest, and clearly defin-
ing the boundaries of the volume interrogated during the experiment (useful for post-experiment alignment of the serial-sectioning images). The standard serial-sectioning procedure for the DB FIB-SEM begins with cross-section FIB milling to remove a small slice of material as shown in Figure 1(A). Normal incidence milling in a scanning mode is generally not used for serial-sectioning experiments, as milling rates are dependent on a number of factors, including chemistry, crystal orientation, and surface topology [17]. Most serial-sectioning experiments rely on the ability to consistently remove a known thickness of material per cycle while keeping the surface-of-interest flat. Since many engineering materials have a microstructure that is both polyphase and polycrystalline, repeated normal incidence milling is not generally useful for serial-sectioning, although there are situations for single crystal superalloys (where the matrix and precipitates have similar milling rates) in which this methodology has been successfully applied [18]. By comparison, the geometry of cross-section milling allows one to prepare a flat surface even when the microconstituents have vastly different milling rates. Also, ion milling is a relatively gentle and damage-free process as compared to conventional mechanical grinding or polishing methods, so features such as porosity or comparatively-soft phases are preserved. After cross-section milling, the surface-of-interest is analyzed. If SEM imaging is sufficient to characterize the material microstructure, one can collect an image from the freshly-milled surface without moving the sample, and the cycle can be repeated until the desired volume of material has been interrogated. This procedure has been automated for the FEI Strata DB 235 microscope using FEI’s Auto Slice and View software. Automation software for this application is essential, as it ensures that the serial-section removal rate is nominally consistent (as compared to manual definition of the milling patterns), and this eliminates the need for human supervision and interaction, so that the experiment can run for long periods of time and can contain potentially hundreds of serial sections. However, using only this approach severely underutilizes the analytical capabilities of the DB FIB-SEM. Importantly, for the standard port configuration of the DB 235 microscope the only information that can be
Figure 1. (A) Schematic of the sample geometry relative to the FIB and SEM columns for serial-sectioning via cross-section milling. (B) Representative cantilever beam sample geometry used for serial-sectioning. The arrows indicate fiducial markers used for the pattern recognition software. The two circles are used for rotation alignment, while the cross is used for both lateral alignment and positioning of the milling pattern.
M. D. Uchic et al. / Scripta Materialia 55 (2006) 23–28
acquired synchronously with cross-section milling are SEM images or EDS maps [19]. One cannot access either SIM imaging or electron back-scatter diffraction (EBSD) mapping, because the sample needs to be repositioned—which can include a tilt, rotation and translation—in order to expose the cross-section face to the desired source and detector. In addition, there can be practical problems when stopping and restarting Auto Slice and View experiments that are associated with the positional accuracy of the initial milling pattern, which must be determined manually. In order to take advantage of all of the analytical capabilities of DB 235, we have developed a microscope control script that allows for the autonomous collection of any combination of SEM images, SIM images, EBSD maps and EDS maps throughout a serial-sectioning experiment [16]. The control script is written in the FEI RunScript language. An important feature of the script is the usage of the built-in pattern recognition capabilities of the DB 235, which ensures both precise repositioning of sample after moving between serial-sectioning or analysis steps, and exact placement of the milling beam prior to cross-section milling. There are other benefits to using pattern recognition technology. This process also allows one to stop and restart an experiment without error, which is important for long-term data collection runs as incorporating EBSD or EDS analysis can significantly lengthen the time needed to perform a given experiment. From a user perspective, the electron and ion optics are extremely stable for this platform, but having the ability to stop the experiment and fine-tune the instrument performance (or recover gracefully from experimental problems) has significantly improved the success rate of these experiments, which have lasted up to six consecutive days. Using this custom microscope control script, the user is able to define a serial-sectioning experiment that can contain image, crystallographic, and chemical data. In the following section, we show two examples of using the DB FIB-SEM and custom microscope control script to characterize the structure and crystallography of finegrained Ni superalloys. The first example demonstrates the ability of the DB FIB-SEM to characterize relatively ‘‘large’’ volumes of material where the grain structure and crystallography are of interest. The second example highlights the fine sectioning fidelity of the DB FIBSEM, which is used to characterize the 3D morphology of c 0 (Ni3Al) precipitates within a superalloy. 3. Example 1: characterization of the grain structure of nickel base superalloys As mentioned above, this first example illustrates the use of the DB FIB-SEM to characterize the 3D grain structure and crystallography of a fine-grained polycrystalline nickel-base superalloy, IN100. The majority of the grains in this material range in size from 1 to 5 lm in diameter, therefore a removal rate of 100–300 nm per section is sufficient to characterize the grain morphology. Note that this sectioning depth is accessible by traditional mechanical polishing methods; however, there are no known instruments which have integrated
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mechanical polishing and electron optics-based analysis for automated data acquisition. In order to acquire morphological information, we determined that SIM imaging using the secondary electron detector produced images having the best contrast for segmentation of the grain structure (conventional electron backscatter detectors are not readily available for the DB 235). By segmentation, we mean the process of extracting various microstructural features such as grains, grain boundaries or carbide precipitates using image processing programs [20], and this process has to be completed prior to visualizing or analyzing these features in 3D. High contrast images are desired as this generally aids computer-based segmentation algorithms. The procedure for a typical serial-sectioning experiment is as follows, and the values reported here correspond to the experimental results shown in Figure 2. Cross-section milling was performed using a 3000 pA aperture and a filled box milling pattern of dimensions 57 · 0.125 lm for a time of approximately 450 s. The box pattern was slightly-oversized relative to the desired sectioning thickness (100 nm) to minimize the impact of any error in positioning of the milling pattern. After cross-section milling, the sample was rotated 180 and repositioned for SIM imaging. Scanning Ion Microscope images were acquired using a 100 pA aperture and a pixel dwell time of 50 ls. The experiment acquired a total of 247 sections, and examined a volume of material having dimensions of 48 · 47 · 24.7 lm. In Figure 2(A), we show a series of four ion images taken from a single section, where there is a 6 change in specimen tilt between consecutive images. The large change in contrast between grains of different orientation is due to ion channeling [17]. The motivation for acquiring multiple images is that ion channeling contrast has an angular dependency, and having multiple images improves the likelihood that adjacent grains will have large differences in intensity for at least one imaging angle. One current research effort aims to develop robust and automated software that will accurately combine the entire series of SIM images, and to use this information to automatically segment the entire grain boundary network. For selected cases where a single grain has strong channeling contrast relative to neighboring grains, we have been able to apply simple image processing methods to segment these features and reconstruct these grains in 3D, as shown in Figure 2(B). In addition to image data, EBDS and/or EDS maps can also be collected for each section. This typically occurs after collection of the ion images, where the sample is repositioned for optimal beam- specimen-detector geometry, a map is collected, and the sample is moved back to the cross-sectioning milling position for removal of the next section. Note that while the mechanical damage from FIB milling is often at a low enough level to allow for generation of EBSD patterns from 30 kV Ga+ ion-milled surfaces, this condition is material specific and some materials may require more stringent surface-preparation procedures. One significant drawback to collecting crystallographic or chemical maps during the serial-sectioning experiment is the time required for data collection. In
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Figure 2. (A) A series of four SIM images collected from a single section of a serial-sectioning experiment. There is a 6 change in specimen tilt between consecutive images, which results in changing contrast levels due to ion channeling effects [17]. (B) Two different perspective views of a 3D reconstruction of a grain contained within the areas indicated by the black boxes in (A). The frame around the grain measures 6.4 lm · 4.4 lm · 5.0 lm, with the direction indicated by the dotted lines measuring 5.0 lm. The 3D reconstructions were performed using the software program IMOD [23].
a nearly identical experiment to the one described above, EBSD patterns were collected throughout a serial-sectioning experiment [16]. The time required to collect a 50 · 47 lm EBSD map with a 0.25 lm pixel size at an acquisition rate of 58 points per second was approximately 11 min. By comparison, the other individual steps in the serial-sectioning experiment did not take as much time: cross-section milling (8 min), sample stage repositioning via pattern matching (6 min), and collection of four SIM images of the same area with a 50 nm pixel size (5 min). The time needed for the EBSD data collection was approximately 36% of the cycle time, even though the pixel resolution of the EBSD data was only 1/5th the resolution of the image data. Acquisition of chemical spectra with reasonable statistics will likely require an order of magnitude longer collection times as compared to EBSD maps. Although the acquisition of the EBSD or EDS data does significantly lengthen the time needed to complete an experiment, this information can be readily used for automated segmentation of grain structures. A recent study by Groeber et al. has developed software to perform both automated segmentation and quantitative 2D analysis using EBSD data for every section of serialsectioning experiment [16]. This analysis includes both morphological and crystallographic parameters such as grain area, grain perimeter length, number of neighbors, and grain boundary misorientation. Current research in this area is focused on performing segmentation, optimized surface meshing, and quantitative analysis of this data in a full 3D environment [21]. 4. Example 2: characterization of c 0 precipitate morphology The second example highlights the capability of the DB FIB-SEM to perform extremely fine serial-section-
ing. The material examined in this study was a polycrystalline nickel-base superalloy (Rene´ 88 DT), which had been given an experimental heat treatment in order to produce a coarsened Ni3Al (c 0 ) precipitate morphology. In comparison to the previous example, the serialsectioning sample encompassed only two grains, as this study focused on characterizing the morphology of the c 0 precipitates within a single grain. Scanning ion imaging (using the secondary electron detector) provided the largest contrast difference between the c 0 phase and the matrix. In order to characterize the size and shape of the c 0 precipitates, the serial-sectioning thickness was selected to be 25 nm, which would be extremely difficult to achieve with mechanical polishing methods. Like the previous example, this experiment required rotating, translating, and tilting the sample between the cross-section milling position and the ion imaging position. It was our experience that a serial-sectioning thickness of 25 nm is near the practical limit of the DB 235 when incorporating stage movements into the serial-sectioning script, due to the rather long time (20 min) needed to minimize stage drift to a level which would not affect the sectioning process. The experimental conditions are as follows. Serialsectioning was performed using a 100 pA beam aperture, with the milling box consisting of dimensions 15 lm · 0.062 lm (oversized relative to sectioning thickness of 25 nm) for 290 s. For SIM imaging, a 100 pA aperture was used with a pixel dwell time of 20 ls. In Figure 3, a series of four images from the experiment are shown, which are spaced apart in depth at intervals of approximately 250 nm. For the region indicated in the micrographs, there appears to be a number of clustered but discrete sub-micron c 0 precipitates and an occasional carbide particle. The connectivity between these features is impossible to discern without the aid of 3D reconstruction. Figure 4(A) shows a reconstruction of the c 0 phase and carbides within this volume, which
M. D. Uchic et al. / Scripta Materialia 55 (2006) 23–28
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Figure 3. A series of four SIM images from a serial-sectioning experiment. The light-colored phase is c 0 , the medium-gray matrix is c, and the dark particles are carbides. The change in depth between the images shown is approximately 250 nm. Three-dimensional reconstructions of the c 0 phase and carbides contained within the areas indicated by the white boxes are shown in Figure 4.
Figure 4. (A) A 3D reconstruction of the c 0 phase and carbide particles from the areas indicated in Fig. 3. The frame around the precipitate measures 2.1 lm · 2.1 lm · 1.5 lm, with the direction indicated by the dotted lines measuring 1.5 lm. The 3D reconstruction clearly shows that all of the c 0 phase in the outlined volume is connected and forms one large precipitate. (B) An additional 3D reconstruction, where the matrix has been made semi-transparent in order to reveal the carbide particles that are distributed within the arms of the c 0 precipitate. The 3D reconstructions were performed using the software program IMOD [23].
demonstrates that all of the apparently discrete c 0 precipitates from the regions indicated in Figure 3 are actually interconnected and form a single precipitate. In Figure 4(B), one can also observe six carbide particles that are in contact with the c 0 precipitate. This study is a work in progress, and we have not completed a quantitative analysis of the distribution of size and morphology of the c 0 precipitates or any spatial correlations between the c 0 precipitates and carbide particles. However, this example clearly shows the ability of the FIB microscope to characterize microstructure at fine length scales and over volumes which are not accessible by any other instrument.
5. Comments on future developments and needs From the examples in the previous section, it is clear that the DB FIB-SEM is a potent instrument capable of automated characterization of the morphology, crystallography, and chemistry of micron and sub-micron size features in 3D. It is worth mentioning that this instrument is not optimized solely for 3D microscopy, as other primary functions include the production of site-specific TEM lamellae and direct-write micromachining. Because these instruments are typically placed in multi-user
facilities and are not usually dedicated to 3D microscopy, there is a strong user need for faster data acquisition from the serial-sectioning experiments. As instrument manufactures improve the performance of various sub-systems (for example, FIB columns optimized for cross-section milling at high beam currents, low-drift optical-encoded stages, faster EBSD cameras, high count-rate EDS systems), these changes will naturally shorten the time needed to complete a serial-sectioning experiment (perhaps collectively) by an order of magnitude from the examples shown previously. Also, data collection is usually done in monotonic fashion, that is, the same suite of data is collected at regular intervals throughout the experiment and data analysis is started after the experiment is completed. In the future, it may be possible to significantly shorten the experiment by analyzing the serial-sectioning data in real time, giving feedback to the microscope as to the frequency and type of data that needs to be collected on the following section—i.e., ‘smart’ or ‘informed’ acquisition methodologies. Lastly, it has been our experience that the time needed to physically collect the serial-sectioning data is actually not the current rate-limiting step in characterizing microstructural features in 3D. Rather, it is the difficulty in performing robust segmentation that represents the real rate-limiting step in terms of performing 3D
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microstructural visualization and analysis, especially when the serial-sectioning experiment consists solely of image data. Analysis of crystallographic or chemical maps rather than image data can alleviate some of these difficulties [16,22], although continued development and transition of advanced signal processing methods to the materials science community will be extremely beneficial. Incorporation of multiple data sources (multi-spectral analysis) will likely allow for fully-autonomous data segmentation, and provide data which contains nearly all of the desired information about a particular microstructure. Once these methods become more widely available, we envisage that the quantitative study of microstructure in 3D at the microscale via the DB FIB-SEM will become a commonplace methodology. Acknowledgements The authors acknowledge support from the Materials and Manufacturing Directorate and the Air Force Office of Scientific Research. MAG acknowledges support through contract # F33615-01-2-5225. The authors thank Peter Sarosi and Michael Mills from The Ohio State University for supplying the Rene´ 88 DT superalloy sample, and Somnath Ghosh for valuable discussions. The authors would also like to thank Stuart Wright, Paul Scutts, Mike Tiner, and Damian Dingley, and Joe Ullmer of TSL for development of remote-capable OIM software, and Robert Kerns, Robert Wheeler and Frank Scheltens of the Microstructural Characterization Facility at AFRL/ML for their assistance in incorporating the TSL OIM system into the serial-sectioning scripting program. Lastly, the authors gratefully acknowledge the efforts of Hamish Fraser, who has consistently championed the development of dual beam microscopes. References [1] R.T. DeHoff, J. Microsc. 131 (1983) 259–263. [2] D. Blavette, A. Bostel, J.M. Sarrau, B. Deconihout, A. Menand, Nature 363 (1993) 432–435.
[3] S.S.A. Gerstl, D.N. Seidman, A.A. Gribb, T.F. Kelly, AM&P 10 (2004) 31–33. [4] J. Frank, Electron Tomography: Three-dimensional Imaging with the Transmission Electron Microscope, Plenum Press, New York, NY, 1992. [5] P.A. Midgley, M. Weyland, Ultramicroscopy 96 (2003) 413–431. [6] T. Sakamoto, Z. Cheng, M. Takahasi, M. Owari, Y. Nihei, Jpn. J. Appl. Phys. 37 (1998) 2051–2056. [7] D.N. Dunn, R. Hull, Appl. Phys. Lett. 75 (1999) 3414– 3416. [8] M.W. Phaneuf, J. Li, Proc. Microsc. Microanal. 6 (2000) 524–525. [9] B.J. Inkson, T. Steer, G. Mo¨bus, G.T. Wagner, J. Microscopy 201 (2001) 256–269. [10] B.J. Inkson, M. Mulvihill, G. Mo¨bus, Scripta Mater. 45 (2001) 753–758. [11] S. Schmidt, S.F. Nielsen, C. Gundlach, L. Margulies, X. Huang, D. Juul Jensen, Science 9 (2004) 229–232. [12] B.C. Larson, W. Yang, G.E. Ice, J.D. Budai, J.Z. Tischler, Nature 415 (2002) 887–890. [13] J.E. Spowart, H.M. Mullens, B.T. Puchala, JOM-J. Min. Met. Mater. S 37 (2003) 35–37. [14] J. Alkemper, P.W. Voorhees, J. Microsc. 201 (2001) 388– 394. [15] D.M. Dimiduk, T.A. Parthasarathy, S.I. Rao, Y.S. Choi, M.D. Uchic, in: S. Ghosh, J.M. Castro, J.K. Lee (Eds.), Materials Processing and Design: Modeling, Simulation, and Applications, NUMIFORM 2004, Springer-Verlag, New York, NY, 2004, pp. 1705–1710. [16] M.A. Groeber, B.K. Haley, M.D. Uchic, D.M. Dimiduk, S. Ghosh, Mater. Char., in press. [17] J. Orloff, M. Utlaut, L. Swanson, High Resolution Focused Ion Beams: FIB and Its Applications, Kluwer Academic/Plenum, New York, NY, 2003. [18] M.D. Uchic, M.G. De Graef, R. Wheeler, D.M. Dimiduk, submitted for publication. [19] P.G. Kotula, M.R. Keenan, J.R. Michael, Proc. Microsc. Microanal. 9 (Suppl. 2) (2003) 1004–1005. [20] J.C. Russ, The Image Processing Handbook, 3rd ed., CRC Press, Boca Raton, FL, 1999. [21] M.G. Groeber, Y. Bhandari, D.M. Dimiduk, M.D. Uchic, S. Ghosh, unpublished research. [22] P.G. Kotula, M.R. Keenan, J.R. Michael, Microsc. Microanal. 9 (2003) 1–17. [23] J.R. Kremer, D.N. Mastronarde, J.R. McIntosh, J. Struct. Biol. 116 (1996) 71–76.
Viewpoint Paper
3D microstructural characterization of nickel superalloys via serial-sectioning using a dual beam FIB-SEM Michael D. Uchic,a,* Michael A. Groeber,b Dennis M. Dimiduka and J.P. Simmonsa a
Air Force Research Laboratory, Materials and Manufacturing Directorate, Wright-Patterson AFB, OH 45433, United States b The Ohio State University, Department of Materials Science and Engineering, Columbus, OH 43210, United States Received 7 November 2005; revised 8 February 2006; accepted 13 February 2006 Available online 27 March 2006
Abstract—Dual beam focused ion beam-scanning electron microscopes are well suited for characterizing micron and sub-micron size microstructural features in three dimensions via serial-sectioning procedures. Importantly, these commercially-available instruments can be used to collect morphological, crystallographic, and chemical information throughout a serial-sectioning experiment. Selected examples are shown to demonstrate these capabilities. 2006 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved. Keywords: Microstructure; Focused ion beam (FIB) microscopy
1. Introduction The study of microstructure in three dimensions (3D) is currently undergoing a revolutionary change in terms of the development and commercial availability of dedicated characterization systems, visualization software, and analysis methodologies. While scientists have been able to readily characterize some microstructural features in two dimensions (2D) using standard microscopy instrumentation and stereological procedures, there are many microstructural features that can only be measured in 3D, such as the number of features per volume, the true size and shape of microstructural features, and the connectivity between features [1]. The need to more accurately and quantitatively characterize microstructure has in large part stimulated the steady development of a suite of automated or nearly-autonomous instruments and methodologies that can characterize in 3D the local structure, chemistry, and/or crystallography of materials from the atomic scale extending all the way up to millimeter-size volumes. This includes devices and methods that are particularly suited for characterizing metals such as the 3D atom probe and local-electron atom probe [2,3], tomographic transmission electron microscopy [4,5], focused ion beam (FIB)
* Corresponding author. Tel.: +1 937 255 4784; fax: +1 937 255 3007; e-mail: [email protected]
serial-sectioning [6–10], synchrotron-based X-Ray diffraction [11,12], and mechanical polishing or micromilling serial-sectioning devices [13,14]. The continued refinement and application of these sophisticated instruments and methodologies will certainly advance the field of materials characterization. Of primary interest for modern mechanical property prediction programs is the ability to quantitatively characterize grain and precipitate-level microstructural features, in order to supply modeling and simulation efforts with high fidelity descriptions of microstructure [15]. These descriptions might consist of either direct or synthetic representations of microstructures in 3D, or statistical functions that describe microstructural feature distributions. In order to apply serial-sectioning methods to characterization of a particular feature class, a general rule of thumb is that one would like a minimum of 10–20 sections per feature to accurately represent its size and shape. Many engineering alloys have grains and precipitates that have dimensions on the order of a couple hundred nanometers to a few microns. The study of these features is ideally suited for FIB microscopes, as these systems are capable of focusing the ion beam to spot sizes smaller than 20 nm, and are able to control the position of the beam with nm-level accuracy. Single beam FIB microscopes have been previously demonstrated to be very capable systems for performing serial-sectioning experiments at the microscale, where
1359-6462/$ - see front matter 2006 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved. doi:10.1016/j.scriptamat.2006.02.039
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M. D. Uchic et al. / Scripta Materialia 55 (2006) 23–28
the FIB is used as a ‘‘nano-knife’’ to prepare a series of cross-sectional surfaces [6–10]. After cross-section milling the surface-of-interest is repositioned so that the FIB column can acquire a scanning ion microscope (SIM) image or collect a secondary ion mass spectroscopy map, and repeating this process multiple times forms the basis of a serial-sectioning experiment. With the advent of dual beam focused ion beam-scanning electron microscopes (DB FIB-SEMs), the incorporation of an electron column and associated analytical capabilities into the FIB microscope transforms this device into a much more capable serial-sectioning instrument. In this article we discuss the application of DB FIB-SEM microscopes to study microstructures in 3D, identify current limitations, and suggest areas for future development.
2. Dual beam FIB-SEM serial-sectioning methodology This section will briefly describe the DB FIB-SEM serial-sectioning methodology employed by the authors to study aerospace materials. All of the experimental work has been performed on a FEI Strata DB 235 microscope outfitted with a TSL orientation imaging microscopy system and EDAX electron dispersive spectroscopy system. Although details such as the microscope control scripts are specific to this instrumentation set, it is likely that the general techniques are applicable to other FIB-SEM instruments. A schematic of the geometry of the FIB and SEM columns and typical sample orientation for the serialsectioning experiment is shown in Figure 1(A), and an image of the typical sample geometry used in our laboratory is shown in Figure 1(B). The sample has been FIB micromachined prior to the serial-sectioning experiment into a cantilevered beam configuration [16]. This sample geometry is not required, as the serial-sectioning experiments can be performed at the surface of a bulk sample with only a small amount of pre-experiment micromachining (for example, see Refs. [9,10]). The advantages of the cantilever beam geometry include minimizing the redeposition of milled material onto the surface-ofinterest, eliminating the possibility of shielding the detectors for crystallographic or chemical analysis while mapping the entire surface-of-interest, and clearly defin-
ing the boundaries of the volume interrogated during the experiment (useful for post-experiment alignment of the serial-sectioning images). The standard serial-sectioning procedure for the DB FIB-SEM begins with cross-section FIB milling to remove a small slice of material as shown in Figure 1(A). Normal incidence milling in a scanning mode is generally not used for serial-sectioning experiments, as milling rates are dependent on a number of factors, including chemistry, crystal orientation, and surface topology [17]. Most serial-sectioning experiments rely on the ability to consistently remove a known thickness of material per cycle while keeping the surface-of-interest flat. Since many engineering materials have a microstructure that is both polyphase and polycrystalline, repeated normal incidence milling is not generally useful for serial-sectioning, although there are situations for single crystal superalloys (where the matrix and precipitates have similar milling rates) in which this methodology has been successfully applied [18]. By comparison, the geometry of cross-section milling allows one to prepare a flat surface even when the microconstituents have vastly different milling rates. Also, ion milling is a relatively gentle and damage-free process as compared to conventional mechanical grinding or polishing methods, so features such as porosity or comparatively-soft phases are preserved. After cross-section milling, the surface-of-interest is analyzed. If SEM imaging is sufficient to characterize the material microstructure, one can collect an image from the freshly-milled surface without moving the sample, and the cycle can be repeated until the desired volume of material has been interrogated. This procedure has been automated for the FEI Strata DB 235 microscope using FEI’s Auto Slice and View software. Automation software for this application is essential, as it ensures that the serial-section removal rate is nominally consistent (as compared to manual definition of the milling patterns), and this eliminates the need for human supervision and interaction, so that the experiment can run for long periods of time and can contain potentially hundreds of serial sections. However, using only this approach severely underutilizes the analytical capabilities of the DB FIB-SEM. Importantly, for the standard port configuration of the DB 235 microscope the only information that can be
Figure 1. (A) Schematic of the sample geometry relative to the FIB and SEM columns for serial-sectioning via cross-section milling. (B) Representative cantilever beam sample geometry used for serial-sectioning. The arrows indicate fiducial markers used for the pattern recognition software. The two circles are used for rotation alignment, while the cross is used for both lateral alignment and positioning of the milling pattern.
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acquired synchronously with cross-section milling are SEM images or EDS maps [19]. One cannot access either SIM imaging or electron back-scatter diffraction (EBSD) mapping, because the sample needs to be repositioned—which can include a tilt, rotation and translation—in order to expose the cross-section face to the desired source and detector. In addition, there can be practical problems when stopping and restarting Auto Slice and View experiments that are associated with the positional accuracy of the initial milling pattern, which must be determined manually. In order to take advantage of all of the analytical capabilities of DB 235, we have developed a microscope control script that allows for the autonomous collection of any combination of SEM images, SIM images, EBSD maps and EDS maps throughout a serial-sectioning experiment [16]. The control script is written in the FEI RunScript language. An important feature of the script is the usage of the built-in pattern recognition capabilities of the DB 235, which ensures both precise repositioning of sample after moving between serial-sectioning or analysis steps, and exact placement of the milling beam prior to cross-section milling. There are other benefits to using pattern recognition technology. This process also allows one to stop and restart an experiment without error, which is important for long-term data collection runs as incorporating EBSD or EDS analysis can significantly lengthen the time needed to perform a given experiment. From a user perspective, the electron and ion optics are extremely stable for this platform, but having the ability to stop the experiment and fine-tune the instrument performance (or recover gracefully from experimental problems) has significantly improved the success rate of these experiments, which have lasted up to six consecutive days. Using this custom microscope control script, the user is able to define a serial-sectioning experiment that can contain image, crystallographic, and chemical data. In the following section, we show two examples of using the DB FIB-SEM and custom microscope control script to characterize the structure and crystallography of finegrained Ni superalloys. The first example demonstrates the ability of the DB FIB-SEM to characterize relatively ‘‘large’’ volumes of material where the grain structure and crystallography are of interest. The second example highlights the fine sectioning fidelity of the DB FIBSEM, which is used to characterize the 3D morphology of c 0 (Ni3Al) precipitates within a superalloy. 3. Example 1: characterization of the grain structure of nickel base superalloys As mentioned above, this first example illustrates the use of the DB FIB-SEM to characterize the 3D grain structure and crystallography of a fine-grained polycrystalline nickel-base superalloy, IN100. The majority of the grains in this material range in size from 1 to 5 lm in diameter, therefore a removal rate of 100–300 nm per section is sufficient to characterize the grain morphology. Note that this sectioning depth is accessible by traditional mechanical polishing methods; however, there are no known instruments which have integrated
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mechanical polishing and electron optics-based analysis for automated data acquisition. In order to acquire morphological information, we determined that SIM imaging using the secondary electron detector produced images having the best contrast for segmentation of the grain structure (conventional electron backscatter detectors are not readily available for the DB 235). By segmentation, we mean the process of extracting various microstructural features such as grains, grain boundaries or carbide precipitates using image processing programs [20], and this process has to be completed prior to visualizing or analyzing these features in 3D. High contrast images are desired as this generally aids computer-based segmentation algorithms. The procedure for a typical serial-sectioning experiment is as follows, and the values reported here correspond to the experimental results shown in Figure 2. Cross-section milling was performed using a 3000 pA aperture and a filled box milling pattern of dimensions 57 · 0.125 lm for a time of approximately 450 s. The box pattern was slightly-oversized relative to the desired sectioning thickness (100 nm) to minimize the impact of any error in positioning of the milling pattern. After cross-section milling, the sample was rotated 180 and repositioned for SIM imaging. Scanning Ion Microscope images were acquired using a 100 pA aperture and a pixel dwell time of 50 ls. The experiment acquired a total of 247 sections, and examined a volume of material having dimensions of 48 · 47 · 24.7 lm. In Figure 2(A), we show a series of four ion images taken from a single section, where there is a 6 change in specimen tilt between consecutive images. The large change in contrast between grains of different orientation is due to ion channeling [17]. The motivation for acquiring multiple images is that ion channeling contrast has an angular dependency, and having multiple images improves the likelihood that adjacent grains will have large differences in intensity for at least one imaging angle. One current research effort aims to develop robust and automated software that will accurately combine the entire series of SIM images, and to use this information to automatically segment the entire grain boundary network. For selected cases where a single grain has strong channeling contrast relative to neighboring grains, we have been able to apply simple image processing methods to segment these features and reconstruct these grains in 3D, as shown in Figure 2(B). In addition to image data, EBDS and/or EDS maps can also be collected for each section. This typically occurs after collection of the ion images, where the sample is repositioned for optimal beam- specimen-detector geometry, a map is collected, and the sample is moved back to the cross-sectioning milling position for removal of the next section. Note that while the mechanical damage from FIB milling is often at a low enough level to allow for generation of EBSD patterns from 30 kV Ga+ ion-milled surfaces, this condition is material specific and some materials may require more stringent surface-preparation procedures. One significant drawback to collecting crystallographic or chemical maps during the serial-sectioning experiment is the time required for data collection. In
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Figure 2. (A) A series of four SIM images collected from a single section of a serial-sectioning experiment. There is a 6 change in specimen tilt between consecutive images, which results in changing contrast levels due to ion channeling effects [17]. (B) Two different perspective views of a 3D reconstruction of a grain contained within the areas indicated by the black boxes in (A). The frame around the grain measures 6.4 lm · 4.4 lm · 5.0 lm, with the direction indicated by the dotted lines measuring 5.0 lm. The 3D reconstructions were performed using the software program IMOD [23].
a nearly identical experiment to the one described above, EBSD patterns were collected throughout a serial-sectioning experiment [16]. The time required to collect a 50 · 47 lm EBSD map with a 0.25 lm pixel size at an acquisition rate of 58 points per second was approximately 11 min. By comparison, the other individual steps in the serial-sectioning experiment did not take as much time: cross-section milling (8 min), sample stage repositioning via pattern matching (6 min), and collection of four SIM images of the same area with a 50 nm pixel size (5 min). The time needed for the EBSD data collection was approximately 36% of the cycle time, even though the pixel resolution of the EBSD data was only 1/5th the resolution of the image data. Acquisition of chemical spectra with reasonable statistics will likely require an order of magnitude longer collection times as compared to EBSD maps. Although the acquisition of the EBSD or EDS data does significantly lengthen the time needed to complete an experiment, this information can be readily used for automated segmentation of grain structures. A recent study by Groeber et al. has developed software to perform both automated segmentation and quantitative 2D analysis using EBSD data for every section of serialsectioning experiment [16]. This analysis includes both morphological and crystallographic parameters such as grain area, grain perimeter length, number of neighbors, and grain boundary misorientation. Current research in this area is focused on performing segmentation, optimized surface meshing, and quantitative analysis of this data in a full 3D environment [21]. 4. Example 2: characterization of c 0 precipitate morphology The second example highlights the capability of the DB FIB-SEM to perform extremely fine serial-section-
ing. The material examined in this study was a polycrystalline nickel-base superalloy (Rene´ 88 DT), which had been given an experimental heat treatment in order to produce a coarsened Ni3Al (c 0 ) precipitate morphology. In comparison to the previous example, the serialsectioning sample encompassed only two grains, as this study focused on characterizing the morphology of the c 0 precipitates within a single grain. Scanning ion imaging (using the secondary electron detector) provided the largest contrast difference between the c 0 phase and the matrix. In order to characterize the size and shape of the c 0 precipitates, the serial-sectioning thickness was selected to be 25 nm, which would be extremely difficult to achieve with mechanical polishing methods. Like the previous example, this experiment required rotating, translating, and tilting the sample between the cross-section milling position and the ion imaging position. It was our experience that a serial-sectioning thickness of 25 nm is near the practical limit of the DB 235 when incorporating stage movements into the serial-sectioning script, due to the rather long time (20 min) needed to minimize stage drift to a level which would not affect the sectioning process. The experimental conditions are as follows. Serialsectioning was performed using a 100 pA beam aperture, with the milling box consisting of dimensions 15 lm · 0.062 lm (oversized relative to sectioning thickness of 25 nm) for 290 s. For SIM imaging, a 100 pA aperture was used with a pixel dwell time of 20 ls. In Figure 3, a series of four images from the experiment are shown, which are spaced apart in depth at intervals of approximately 250 nm. For the region indicated in the micrographs, there appears to be a number of clustered but discrete sub-micron c 0 precipitates and an occasional carbide particle. The connectivity between these features is impossible to discern without the aid of 3D reconstruction. Figure 4(A) shows a reconstruction of the c 0 phase and carbides within this volume, which
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Figure 3. A series of four SIM images from a serial-sectioning experiment. The light-colored phase is c 0 , the medium-gray matrix is c, and the dark particles are carbides. The change in depth between the images shown is approximately 250 nm. Three-dimensional reconstructions of the c 0 phase and carbides contained within the areas indicated by the white boxes are shown in Figure 4.
Figure 4. (A) A 3D reconstruction of the c 0 phase and carbide particles from the areas indicated in Fig. 3. The frame around the precipitate measures 2.1 lm · 2.1 lm · 1.5 lm, with the direction indicated by the dotted lines measuring 1.5 lm. The 3D reconstruction clearly shows that all of the c 0 phase in the outlined volume is connected and forms one large precipitate. (B) An additional 3D reconstruction, where the matrix has been made semi-transparent in order to reveal the carbide particles that are distributed within the arms of the c 0 precipitate. The 3D reconstructions were performed using the software program IMOD [23].
demonstrates that all of the apparently discrete c 0 precipitates from the regions indicated in Figure 3 are actually interconnected and form a single precipitate. In Figure 4(B), one can also observe six carbide particles that are in contact with the c 0 precipitate. This study is a work in progress, and we have not completed a quantitative analysis of the distribution of size and morphology of the c 0 precipitates or any spatial correlations between the c 0 precipitates and carbide particles. However, this example clearly shows the ability of the FIB microscope to characterize microstructure at fine length scales and over volumes which are not accessible by any other instrument.
5. Comments on future developments and needs From the examples in the previous section, it is clear that the DB FIB-SEM is a potent instrument capable of automated characterization of the morphology, crystallography, and chemistry of micron and sub-micron size features in 3D. It is worth mentioning that this instrument is not optimized solely for 3D microscopy, as other primary functions include the production of site-specific TEM lamellae and direct-write micromachining. Because these instruments are typically placed in multi-user
facilities and are not usually dedicated to 3D microscopy, there is a strong user need for faster data acquisition from the serial-sectioning experiments. As instrument manufactures improve the performance of various sub-systems (for example, FIB columns optimized for cross-section milling at high beam currents, low-drift optical-encoded stages, faster EBSD cameras, high count-rate EDS systems), these changes will naturally shorten the time needed to complete a serial-sectioning experiment (perhaps collectively) by an order of magnitude from the examples shown previously. Also, data collection is usually done in monotonic fashion, that is, the same suite of data is collected at regular intervals throughout the experiment and data analysis is started after the experiment is completed. In the future, it may be possible to significantly shorten the experiment by analyzing the serial-sectioning data in real time, giving feedback to the microscope as to the frequency and type of data that needs to be collected on the following section—i.e., ‘smart’ or ‘informed’ acquisition methodologies. Lastly, it has been our experience that the time needed to physically collect the serial-sectioning data is actually not the current rate-limiting step in characterizing microstructural features in 3D. Rather, it is the difficulty in performing robust segmentation that represents the real rate-limiting step in terms of performing 3D
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microstructural visualization and analysis, especially when the serial-sectioning experiment consists solely of image data. Analysis of crystallographic or chemical maps rather than image data can alleviate some of these difficulties [16,22], although continued development and transition of advanced signal processing methods to the materials science community will be extremely beneficial. Incorporation of multiple data sources (multi-spectral analysis) will likely allow for fully-autonomous data segmentation, and provide data which contains nearly all of the desired information about a particular microstructure. Once these methods become more widely available, we envisage that the quantitative study of microstructure in 3D at the microscale via the DB FIB-SEM will become a commonplace methodology. Acknowledgements The authors acknowledge support from the Materials and Manufacturing Directorate and the Air Force Office of Scientific Research. MAG acknowledges support through contract # F33615-01-2-5225. The authors thank Peter Sarosi and Michael Mills from The Ohio State University for supplying the Rene´ 88 DT superalloy sample, and Somnath Ghosh for valuable discussions. The authors would also like to thank Stuart Wright, Paul Scutts, Mike Tiner, and Damian Dingley, and Joe Ullmer of TSL for development of remote-capable OIM software, and Robert Kerns, Robert Wheeler and Frank Scheltens of the Microstructural Characterization Facility at AFRL/ML for their assistance in incorporating the TSL OIM system into the serial-sectioning scripting program. Lastly, the authors gratefully acknowledge the efforts of Hamish Fraser, who has consistently championed the development of dual beam microscopes. References [1] R.T. DeHoff, J. Microsc. 131 (1983) 259–263. [2] D. Blavette, A. Bostel, J.M. Sarrau, B. Deconihout, A. Menand, Nature 363 (1993) 432–435.
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