Ultramicroscopy 148 (2015) 123–131

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Ultramicroscopy journal homepage: www.elsevier.com/locate/ultramic

Dark-field imaging based on post-processed electron backscatter diffraction patterns of bulk crystalline materials in a scanning electron microscope Nicolas Brodusch n, Hendrix Demers, Raynald Gauvin McGill University, Mining and Materials Engineering Department, Montréal, Québec, Canada H3A 0C5

art ic l e i nf o

a b s t r a c t

Article history: Received 8 July 2014 Received in revised form 8 September 2014 Accepted 21 September 2014 Available online 22 October 2014

Dark-field (DF) images were acquired in the scanning electron microscope with an offline procedure based on electron backscatter diffraction (EBSD) patterns (EBSPs). These EBSD-DF images were generated by selecting a particular reflection on the electron backscatter diffraction pattern and by reporting the intensity of one or several pixels around this point at each pixel of the EBSD-DF image. Unlike previous studies, the diffraction information of the sample is the basis of the final image contrast with a pixel scale resolution at the EBSP providing DF imaging in the scanning electron microscope. The offline facility of this technique permits the selection of any diffraction condition available in the diffraction pattern and displaying the corresponding image. The high number of diffraction-based images available allows a better monitoring of deformation structures compared to electron channeling contrast imaging (ECCI) which is generally limited to a few images of the same area. This technique was applied to steel and iron specimens and showed its high capability in describing more rigorously the deformation structures around micro-hardness indents. Due to the offline relation between the reference EBSP and the EBSD-DF images, this new technique will undoubtedly greatly improve our knowledge of deformation mechanism and help to improve our understanding of the ECCI contrast mechanisms. & 2014 Elsevier B.V. All rights reserved.

Keywords: Dark-field (DF) Electron channeling contrast imaging (ECCI) Electron channeling pattern (ECP) Electron backscatter diffraction (EBSD) Deformation Scanning electron microscope (SEM)

1. Introduction In transmission electron microscopy, a dark-field (DF) image is obtained when a specific diffraction reflection is excited. This can be accomplished either in the conventional transmission electron microscope (CTEM) or the scanning transmission electron microscope (STEM) by collecting the signal from the diffracted beam corresponding to the selected reflection. Practically, this is performed by placing an aperture (CTEM) or selecting a particular collection angle (STEM) to collect electrons scattered through the Bragg angle corresponding to the specific lattice planes selected. In the scanning electron microscope (SEM), DF imaging can be achieved in STEM mode as in a dedicated STEM when thin specimens are used [1]. However, no DF imaging has been reported on bulk specimens. Only electron channeling contrast imaging (ECCI) provides a DF type contrast based on the electron channeling n Correspondence to: Mining and Materials Engineering Department, Wong Building, McGill University, 3610 University Street, Montréal, Québec, Canada H3A 0C5. Tel.: þ 1 514 398 7182; fax: þ 1 514 398 4492. E-mail address: [email protected] (N. Brodusch).

http://dx.doi.org/10.1016/j.ultramic.2014.09.005 0304-3991/& 2014 Elsevier B.V. All rights reserved.

pattern (ECP). This Kikuchi-like pattern is an angular distribution of the backscattered electron (BSE) yield obtained when the primary electron beam is scanned over a large specimen area or rocked around the optic axis of the microscope at a specific point of the specimen surface [2]. In fact, when the angle between the beam and the lattice planes is close to the Bragg angle, the BSE yield is proportional to the probability of the electron to be backscattered inside the matter in addition to the Z2 dependence of Rutherford scattering. This probability is based on the Bloch wave theory [3] and is the square of the coefficient of a Bloch wave contribution divided by the sum of all the square of each Bloch wave contribution. To simplify the calculations, only two Bloch waves are generally used to describe this probability. Bloch wave of type I has its maximum at the atom sites while type II has its maxima between the atom rows. At the exact Bragg angle the contribution of the two Bloch waves is equal. When the scan angle is small, typically at magnification higher than 100 times [4], the intensity at each pixel of the ECCI image is equal to that at the centre of the corresponding ECP at the same pixel position. This acts like a virtual aperture at the centre of the ECP. However, this virtual aperture, used to select the channeling pattern (ECP) area for the signal

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suspensions with etching steps (5% and 2% nitric acid in water) in between. The sample was then electro-polished in 20% perchloric acid and 80% ethanol for 5 min (30 s interval) at room temperature. A final polishing step was manually performed with a 50 nm colloidal silica suspension. Indentations were carried out using a Clark Microhardness Tester CM-1000AT (Sun-Tec Corporation, Novi, MI, USA), with a peak load of 50 g. The steel sample was a stress relief annealed nonoriented Si–Fe electrical steel (NOES) cut in a 1.5  1.5 cm2, ground with 800 and 1200 grit papers and polished with 3 and 1 mm diamond suspensions. Final polishing was performed with a 50 nm colloidal silica suspension for 1 h followed by Ar þ ion beam milling using a Hitachi IM3000 flat milling system (Hitachi High-Technologies, Rexdale, Canada). The accelerating voltage was 3 kV and the angle of incidence in regard to the surface normal was 801. ECPs were recorded with a Hitachi SU-3500 thermo-ionic emission gun SEM equipped with a tungsten filament (Hitachi High-Technologies, Rexdale, Canada) and EBSPs were recorded with either a Hitachi SU-70 or a SU-8000 field-emission SEMs (Hitachi High-Technologies, Rexdale, Canada). Both were equipped with a HKL Nordlys electron backscatter diffraction (EBSD) system (Oxford Instruments, Concord, USA) controlled with the Channel 5 package. The EBSD camera screen resolution was 640  480 and 1344  1024 pixels for the SU-70 and SU-8000, respectively. Pattern acquisition, indexing and simulations were carried out with the Flamenco software which is part of the Channel 5 package. The EBSPs were recorded and stored following the same procedure as for standard EBSD acquisition, i.e., background subtraction and flat fielding was applied. The ECP was acquired with an accelerating voltage of 20 kV at normal incidence with a solid state semi-conductor backscattered electron detector placed on top of the specimen surface and normal to the beam (PD-BSE). The ECP image resolution was 1280  960 pixels. The EBSPs were recorded with accelerating voltages of 20 and 30 kV as specified in the text and a tilt angle of 701, except in Fig. 1 where the tilt angle was 801. The distance

collection, is only limited to the centre of the ECP [4]. Then, the specimen needs to be tilted and rotated to change the region of the ECP that will be located at the centre point. Payton and Nolze reported the use of diodes on top of the EBSD camera combined to EBSD scan to improve phase identification [5] following the work initiated by Prior et al. on using semi-conductor diodes attached to the EBSD camera [6]. Previous studies were also reported where large areas of the EBSPs were selected to reconstruct the image from an EBSD scan [7,8] and a similar technique was recently commercialized by EDAX researchers [9] during the course of our study, named PRIAS for Pattern Region of Interest Analysis System. However, in these techniques, because of the large regions of the EBSPs used to reconstruct an image, the intensity of one region is the average of several different diffraction conditions (area in the EBSP) and the original diffraction information present in the EBSPs is thus lost. In this work, we report on an innovating technique that provides controlled DF imaging in the SEM. At each pixel, the reported intensity is related to a specific diffraction condition with a better angular accuracy contrary to the previous works cited above. This technique is based on the post-processing of electron backscatter diffraction patterns (EBSPs) and may open interesting applications in the SEM.

2. Materials and instrumentation The Si specimen used in this work was a 1  1 cm² [001] (001) silicon wafer prepared by the cleavage technique. The iron sample was cut from a polycrystalline pure iron rod with a diameter of 7.6 mm (Alfa Aesar, Ward Hill, MA, USA). The small disc was annealed in vacuum at 800 1C for 24 h followed by slow cooling in the furnace. The thickness of the sample was reduced by 4.7% using a compression machine. The compressed sample was then ground with 800 and 1200 grit papers, followed by polishing using 3 and 1 mm diamond

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Fig. 1. Comparison between an electron backscatter diffraction pattern (EBSP) and an electron channeling pattern (ECP) of a [001] (001) silicon wafer. (A) Raw and (B) digitally filtered EBSP and (C) ECP. Both were recorded with an accelerating voltage of 20 kV. The working distance was 10 mm for the ECP and the detector distance was 80 mm for the EBSP. Tilt angles were 01 and 801 for the ECP and the EBSP, respectively. (D) Line profiles extracted from (A–C) show the higher resolution obtained with the ECP compared to the EBSP.

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from the EBSD detector and the specimen surface was varied from 16 mm to 80 mm and will be specified in the text when necessary. The ECP and EBSPs were recorded as 8-bit images, i.e., with a grey scale range of 256 levels. For display purposes, the EBSP images displayed in this report were noise-filtered by segmenting the fast Fourier transform (FFT) images of the original images and then by applying an inversed FFT to obtain the final images. The bottom diodes of forescatter detectors (FSDs) attached to both EBSD cameras were used to acquire orientation images. Band contrast (BC) images were extracted from the EBSD scan in Fig. 5 using the Tango software which is part of the Channel 5 package. In this image, the BC value is related to the relative contrast of the Kikuchi bands compared to the overall contrast of the whole EBSP [10] and reflects, more or less, its sharpness. The signal S extracted from the line profiles in Fig. 1 was normalized using S ¼(I  Imin)/(Imax þ Imin) and in Fig. 3 the contrast C was calculated using C ¼(Imax  Imin)/(Imax þ Imin), I being the grey value at each pixel of the profile and Imin and Imax the minimum and maximum grey value of the profile.

3. Experimental procedure As reported by Joy [4], channeling contrast images are obtained by reporting on each pixel of the final image the intensity from the center of the ECP that would be obtained from the material under investigation at this specific pixel position. The magnification must be high enough (higher than  100) for the beam to specimen surface angle to be considered as constant over the whole scanned area. Then, if an ECP is recorded, a specific reflection can be selected by rotating and tilting the specimen in order to bring a particular pseudo-Kikuchi line or a zone axis at the center of the ECP image [11–14] to obtain a new image related to the new area brought at the center of the ECP. Unfortunately, this facility being only available by tilting and rotating the specimen in the SEM, this limits greatly the applicability of such a technique. However, when EBSD is used to acquire and store EBSPs, an image can be generated where each pixel is given a specific value derived from the EBSP from this specific pixel position on the specimen surface. This value can be either an orientation related value, a misorientation value or a pattern quality value [15–18]. In the present work, the method used for ECCI is transposed to the EBSD case with the ECP being replaced by the EBSP. In this method, instead of moving the specimen to bring a specific reflection at the center of the ECP (optic axis of the SEM), a virtual beam is selected onto the EBSP by choosing a cluster of pixels and the final image is then reconstructed by reporting the intensity of the area defined by the virtual beam at each pixel position of the EBSD map. The advantage here is obvious: whereas the conventional ECCI technique provides an image from one reflection at a time, the EBSD-based technique can provide several images with different diffraction reflections at the same time. The correspondence between ECP and EBSP has never been studied in details, although some authors broached the topic [19,20]. It is generally accepted that both techniques are related to each other by the reciprocity theorem [21–23]. According to this theorem, the detector distance (DD) between the EBSD camera screen and the beam impact point on the specimen, that determines, with the EBSD camera screen size, the EBSP collection angle, is equivalent to the scan or rock angle necessary to generate the ECP. Similarly, the beam divergence angle in ECP is equivalent to the phosphorescent screen angular resolution used to record the EBSP. Based on these requirements, an EBSP recorded from the same orientation in the same angular configuration as for an ECP should exhibit the same contrast and shape. Fig. 1 shows a comparison of an EBSP (Fig. 1A) and an ECP (Fig. 1C) from a [001] (001) silicon wafer at

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801 and 01 tilt angle, respectively, both recorded close to the [001] zone axis. The EBSP was recorded at the maximum detector distance available (80 mm) on the SU-8000 microscope to magnify the pattern to have the same dimensions as the ECP. However, it was cropped to the same area as that of the ECP because it could not be magnified further more. Consequently the image resolution of the EBSP displayed was 470  366 pixels leading to a pattern resolution 2.7 times smaller than the ECP. Obviously, the angular resolution of the ECP looks much higher than that of the EBSP. The ECP was rescaled to the same image resolution than that of the EBSD (not shown) and mostly shows the same resolution than the full resolution image. This demonstrates that the loss of angular resolution is not due to its lower pixel resolution. However, the energy cutoff due to the conductive layer at the BSE detector and EBSD camera phosphorescent screen surfaces were experimentally estimated to 0.5 and 2 keV, respectively. Hence, there is a significant higher loss of signal in the EBSP than in the ECP at the same accelerating voltage. However, the main reason for the loss of resolution may reside in the fact that in semi-conductor type BSE detectors, the signal generated by the detection system is proportional to the electron energy and thus the high energy BSEs contribute more to the ECP [22]. Because the channeling contrast is handled by high energy BSEs [2], the contrast and resolution of the ECP are then enhanced by using this type of detectors. Recently, a higher EBSP quality was achieved by using a new type of EBSD detector based on the direct detection of the diffracted electrons [24]. However, the efficiency of charged couple device (CCD) camera is not well known in this range of energies and may explain this large loss of resolution and contrast in the EBSP compared to the ECP. It is known also that recording EBSPs on photographic emulsions permits to improve resolution and contrast to a certain extent [22]. To reduce the noise of the image, the fast Fourier transform (FFT) of the EBSP was digitally filtered using FFT and threshold features of ImageJ [25]. A mask created by segmenting the FFT image so that only the frequencies corresponding to the Kikuchi bands in Fourier space were selected. Then, the mask was applied on the complex FFT image and was inverse-fast Fourier transformed. The resulting image is displayed in Fig. 1B. It can be seen that the noise reduction did not improve the contrast significantly but enhanced slightly the ang ular resolution of the EBSP although it was still poor compared to the ECP. Line profiles were extracted from the three images in Fig. 1(A–C) normal to the (220) plane and were plotted in Fig. 1D. In order to compare ECP and EBSP images on the same basis, the line profile was averaged from 10 lines in the ECP and 3 lines in the EBSPs to cover approximately the same area on the image. These results confirm the higher resolution deduced from visual observations, especially when comparing profiles around (220) first, second and third orders at points 1, 2, 3. Clearly, more pseudo-Kikuchi lines were resolved in the ECP than in the EBSP even when a digital filtering procedure was used. However, based on this comparison, the contrast of an EBSP, although it showed a significant loss of angular resolution, was close to that of an ECP. The procedure used in this work was as follow: EBSPs were recorded and stored in a raster motion, like in the conventional EBSD mapping process. Then, the EBSPs from each pixel of the map were post-processed without any image adjustments or manipulation to extract the intensity from a specific cluster of pixels determined by the user in a square fashion. Different pixel clusters, named virtual beam collection area in the following text, could be selected leading to square areas for which an average grey level was calculated and reported in the final map at each pixel. The final DF images were computed using an automated code written with the Python programming language (www.python.org). The images, generated using this procedure, were further labeled EBSD-DF images. The brightness and contrast of all final EBSD-DF images where digitally adjusted to cover the full range of the 256 grey levels.

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4. Results 4.1. ECCI simulation To compare the EBSD-DF images contrast with a conventional ECCI image, a 200  200 pixels EBSD map of a Si–Fe NOES was recorded with a 10 mm step size and an accelerating voltage of 20 kV. Fig. 2A shows the ECCI image of the same area obtained at 20 kV and 01 tilt with the PD-BSE detector. The contrast observed is that expected from a polycrystalline material, i.e., different grey levels for different crystal orientations although two distinct oriented crystals can exhibit the same grey level. In Fig. 2(B–E) are shown EBSD-DF images with random reflections selected on the EBSD map first pixel EBSP (reference EBSP) and using a 2  2 collection area (0.221 collection angle). The image contrast is of the same type and it is clearly seen, as expected, that the contrast changes greatly when different reflections are used. Because the technique described in this work is only based on one small area of the pattern, it is assumed to be more sensitive to small angle crystal rotations than EBSD orientation calculations. Indeed, the latter is based on the measurement of angles between several Kikuchi bands and we assume that the very small pattern shift due to the crystal rotation in the subgrain will fall into the error of the angle measurement. However, when a very small cluster of pixel is used, the shift of the pattern immediately manifests as a change of contrast, making the subgrain visible. Hence, EBSD-DF images can be used for grain boundaries imaging with high angular resolution. As an example, over 4000 EBSD-DF images obtained from the same set of data were used to generate the image shown in Fig. 2F. Each EBSD-DF image was processed using the ImageJ software [25] to detect the edges in the image. As mentioned above, due to the origin of the contrast, some grains of different orientation can give the same contrast and to overcome this issue, the average of the 4000 images after edge detection was calculated to obtain the final image of Fig. 2F. This permitted to enhance the contrast at grain boundaries and have thus the realistic image of grain and subgrain boundaries network. The area encircled in Fig. 2G highlights a region of the EBSD map where the two upper grains, misoriented by only 31, were barely visible in the IPF map. However, they were detected while displaying grain boundaries (GB) (dark GB4101 and white GB411) but this resulted in an increase of the noise on the GB image (superimposed with the IPF map in Fig. 2G). This shows how the grain detection process from the EBSD software may be affected at these low misorientations, the grain size detection being based on the GB misorientations. This could be circumvented if smoothing techniques were applied to the original data, leading to a possible loss of information. In contrast, the image obtained with the EBSD-DF images (Fig. 2F) clearly separates the grains, even with a low misorientation, without additional noise on the image and without any further data manipulation. In order to support this statement, grain size distributions from the inverse pole figure map (Fig. 2G) and the image of Fig. 2F were compared. The grain distribution was measured with the Tango software for the EBSD data (based on the GB detection) and by using the GrainsJ plugin (available at https://bitbucket.org/hendrix_de mers/grainsj) in ImageJ software for the image of Fig. 2F (image analysis technique, i.e., not related to orientation). Both normalized distributions are displayed in Fig. 2H. The trend of the two distributions is mostly identical except for the low side of the histograms where an inversion is observed for grains smaller than 50 mm. This trend seems to confirm that this method provides a higher efficiency in detecting small grains compared to the EBSD-based grain distribution measurement. However, a more systematic study should be conducted to evaluate the reproducibility of the technique and monitor its precision on a wide range of samples. We also bring to the reader's attention that this comparison was conducted with two

different techniques, one based on GB detection (orientation) and the other based on segmentation of the grey scale image. However, the goal here was to show the benefit of our technique compared to the classical EBSD grain size detection technique. However, it has to be noted that because of the limited EBSP saving capabilities (maximum of 40,000 EBSPs) with the Flamenco software, the grain boundaries appeared enlarged due to the large step size used. Consequently, the grain distribution calculated from Fig. 2F was underestimated compared to that based on the EBSD data where the grain boundaries are sharper due the smoothing procedure. A higher resolution map would be necessary to compare the two sets of data. 4.2. Effect of virtual beam collection area The influence of the virtual beam collection area on the EBSP was measured on EBSD-DF images reconstructed around a microhardness indent in the same material as in Fig. 2. The virtual beam collection area was set to 2  2 (0.221 collection angle) (Fig. 3A), 4  4 (0.361 collection angle) (Fig. 3B), 8  8 (0.651 collection angle) (Fig. 3C), and 16  16 (1.221 collection angle) (Fig. 3D) around a pixel on the band edge corresponding to the (121) plane in Fig. 3F (white arrow). The line profile along the white arrow in the inset of Fig. 3E was extracted and the contrast C of the whole profile was calculated and plotted in Fig. 3E as a function of the collection area. As intuitively expected from the images in Fig. 3(A–D), the contrast was increased at small collection area on the EBSP but with a higher level of noise. On the contrary, the SNR was significantly improved when higher collection area values were used but the counterpart was a large drop of the image contrast due to the pixel cluster averaging. Hence, this post-processing technique allows the manipulation of one dataset to get the best optimized image. A 2  2 virtual beam collection area was used in the rest of the work reported here. 4.3. Dark-field imaging of micro-hardness indents The main advantage of the technique reported in this work is the ability to choose a particular reflection for imaging, in an interactive way after the complete set of EBSPs has been recorded and stored. This is illustrated in Fig. 4 where an enlarged view of an EBSP recorded from the first pixel of the image of Fig. 4(B–E). The EBSD map was recorded with an accelerating voltage of 30 kV and a pixel dwell time of 50 ms with 3 frames averaged. No camera binning was used and the EBSP image resolution was 640  480 pixels. Four positions, labeled B, C, D, and E, were selected along the white line drawn in this figure. This line is normal to the tilt axis of the microscope (with the tilt axis parallel to the camera plane) and then simulates the tilting of the specimen just like in an ECCI experiment. The line crosses the (1–10) plane. It has to be noted that in this particular case, the specimen was compressed and hence the grains exhibit some visible deformation which renders the choice of the reference EBSP delicate. However, in the images showed in Fig. 4(B–E), it clear that the contrast of each image changes drastically depending on the reflection used. Although each of the images show a typical indent ECCI contrast, the comparison between them permits to show that a single image could be misleading in describing the deformation structures around the indent. In Fig. 4B and C, when the virtual beam is close to the (1–10) and (3–10) band edges, the contrast is low and mostly monotone inside the bulbs around the indent, except the bottom one. On the contrary, when the virtual beam is placed inside the (1–10) band, more contrast are observed inside the bulbs, indicating that a more complicated deformation mechanism occurs in these regions. Also, the bottom bulb, that exhibited a more distinctive contrast compared to the other bulbs in Fig. 4B and C, is much more described in Fig. 4D and E. Especially in Fig. 4E, the bulb

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Diameter (µm) Fig. 2. Comparison between electron channeling contrast (ECCI) and electron backscatter diffraction dark-field (EBSD-DF) images and an electron backscatter diffraction (EBSD) map from the same region of a stress relief annealed non-oriented Si–Fe electrical steel. (A) ECCI image, (B–E) EBSD-DF images obtained with random reflections from the reference EBSP, (F) reconstructed image showing grain boundaries based on 4000 EBSD-DF images (see plain text for more details), (G) inverse pole figure map based on the same EBSD data as used in (B–F). The EBSPs image resolution was 640  480 pixels. (G) Grain size distribution obtained from the EBSD map (black) and the EBSD-DF reconstructed image (F) (grey) showing a higher number of small grains detected in (F).

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Fig. 3. Effect of the virtual beam collection area on the final EBSD-DF image contrast around a micro-hardness indent in a stress relief annealed non-oriented Si–Fe electrical steel with collection area of (A) 2  2 (0.221 collection angle), (B) 4  4 (0.361 collection angle), (C) 8  8 (0.651 collection angle), and (D) 16  16 (1.221 collection angle). (E) Plot of the contrast C between the points of highest and lowest grey value extracted from the line profile drawn in the top right insert (white arrow). (F) Reference EBSP showing the location of the virtual beam collection area centre point corresponding to the (121) reflection (white arrow). Optimum collection area was 4  4, corresponding to a square of 141 mm width on the phosphorescent screen.

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Fig. 4. EBSD-DF images of a micro-hardness indent on compressed iron obtained with an accelerating voltage of 30 kV and a detector distance of 16 mm as a function of the virtual beam position on the reference EBSP. (A) Reference EBSP taken from the first pixel of the EBSD map, (B) Magnified view of the squared area in the reference EBSP in the insert, (B–E) EBSD-DF images with specific reflections displayed on (A). (F) Band contrast and (G) inverse pole figure maps of the same data. The EBSPs image resolution was 640  480 pixels. The white arrow represents the line from which the points B to D were taken as if the sample was tilted toward the EBSD camera. The movie available in the supplementary data was generated with all the EBSPs along the white arrow.

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shows a symmetrical structure that could be related to iso-deformation contours occurring in this region. To emphasize the importance of using EBSD-DF images to monitor deformation structures, a movie (“EBSD-DF movie.avi”) is available as supplementary material on the Ultramicroscopy Journal website. This movie is a compilation of all the EBSD-DF images constructed with the virtual beam following the white arrow in Fig. 4A. In Fig. 4F and G, the band contrast and IPF maps from the same data are displayed. The band contrast map shows interesting features with quite good contrast but which is only related to the quality of the EBSP, i.e. not related to any diffraction condition. The IPF map, however, shows orientation related details around the indent, but the contrast is very weak compared to the EBSD-DF images in Fig. 4B–D.

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Supplementary material related to this article can be found online at http://dx.doi.org/10.1016/j.ultramic.2014.09.005. To take advantage of the capabilities of EBSD for mapping strains in materials, an EBSD camera with a better pixel resolution and a longer detector distance were used to record an EBSD map of a microhardness indent and generate EBSD-DF images of the deformation structures around it. The accelerating voltage was 30 kV and the EBSP image resolution was 1344  1024 pixels. The dwell time was 500 ms and 2 frames were averaged to generate the stored EBSP. The detector distance to the sample surface was increased from the normal 16 mm setting used in the scan presented in Fig. 4 to 50 mm to magnify the EBSP as described by Wilkinson [19]. However, in our experimental set-up, due to the geometry of the SU-8000 SEM specimen chamber, the maximum detector distance was only 80 mm compared to 140 mm used in Wilkinson's work. Finally, 50 mm was chosen to keep sufficient Kikuchi bands on the EBSD screen to select different reflections that may have been out of the screen at 80 mm. Despite this limitation, high resolution EBSPs were recorded as can be seen from the reference EBSP shown in Fig. 5A from a pixel located at the first quarter of the first row. The FSD (Fig. 5B) and band contrast (Fig. 5C) images are also displayed for comparison purposes. The EBSP displayed in Fig. 5A was centered on the (001) zone axis and [001], (200), (020), (031), (200), and (310) reflections were used to generate the EBSD-DF images in Fig. 5(D–H), respectively. In this example, a larger contrast between the deformation area and the rest of the grain was achieved in EBSD-DF images compared to that obtained with the standard EBSD settings used in Fig. 4 as well as that of the FSD image or the band contrast map in Fig. 5B and C. However, because the deformation pattern changes in the EBSD-DF images depending on the reflection chosen in the reference EBSP, a precise measure of the contrast for comparison was not possible and only visual observations could be done. Again, multiple EBSD-DF images help in monitoring more precisely the deformation structures around the indent compared to the FSD image displayed in Fig. 5B. In fact, the FSD image is based on the mean intensity collected by the diode which is several tens of mm2 in size, offering low contrast images compared to EBSD-DF images and Prior et al. [6] concluded some time ago that several FSD images with different tilt angles were necessary to locate clearly the grain boundaries of polycrystalline specimens. In addition, it is interesting to note the high contrast achieved with EBSD-DF image generated at the center of the [001] zone axis. This might be due to the high level of details observed inside zone axis in Kikuchi-like patterns as described by Joy [4] and Marthinsen and Hoer [26]. A similar treatment as that used in Fig. 2F was applied to this set of images (4000 images) and showed similar structures (not shown) as described in Welsch et al. [27]. However, the physical meaning of these structures could not be easily related to the microstructure, especially dislocation structures as described in their work. 5. Discussion 5.1. Dark-field imaging in the SEM As raised by our results, dark-field images can be extracted from an EBSD scan just by selecting specific pixels in each EBSPs of the map, and by that way, chose a specific reflection to generate an image. This is, theoretically speaking, the same concept as used in

Fig. 5. High contrast EBSD-DF images of a micro-hardness indent on compressed iron obtained using long EBSD detector distance for high angular resolution EBSPs with an accelerating voltage of 30 kV and a detector distance of 50 mm as a function of the virtual beam position on the high angular resolution reference EBSP. (A) Reference EBSP (see plain text for detailed description), (B) band contrast map, (C) FSD image and (D–H) EBSD-DF images with specific reflections marked by arrows in (A). The EBSPs image resolution was 1344  1024 pixels.

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TEM dark-field imaging. However, the main advantage here is the large field of view available in the SEM and the fact that this treatment of the EBSPs is offline, permitting to generate a large number of crystallographic orientation images at the same time. Also, the large collection angle of nowadays EBSD cameras allow recording large number of Kikuchi bands on only one EBSP, and thus, permits a large range of potential reflections to be used. A high angular resolution was achieved by increasing the EBSD camera angular resolution and high contrast deformation images were generated. In addition, the virtual beam collection area can be used to adjust the noise and contrast levels of each generated EBSD-DF image depending on the EBSP angular resolution and contrast as shown in Fig. 3. This parameter might be related to the accelerating voltage used in ECCI. In fact, the band width increases in the ECP when the accelerating voltage is decreased due to the Bragg relation. Consequently, using a small virtual beam collection area should have the same effect as reducing the accelerating voltage in terms of image contrast, except inside zone axis where it is well known that slight changes in accelerating voltage affect the position and visibility of zone axis fine structures. However, this was verified because the dwell time at low primary energy was too long to acquire a full EBSD map with the full EBSD camera resolution.

high angular resolution EBSD camera at long detector distance was used making the deformation area more visible. Apart from the fact that even with the latest generation of commercially available EBSD cameras the angular resolution of EBSPs is lower than that of ECPs, some limitations need to be mentioned. The more limiting parameter of the method is the choice of the reference EBSP on which are selected the reflections rendering the interpretation of EBSD-DF images more difficult if the reference area is also deformed. Secondly, this technique is even more valuable if high resolution EBSPs are recorded during the EBSD scan. This increases considerably the acquisition time which is still an issue when EBSD is performed at high magnification due to drift and carbon contamination. However, this latter issue may be solved when faster and more efficient EBSD camera will be commercialized. In the future, the technique developed here might be helpful if applied to improve our understanding of materials deformation and of the ECCI contrast mechanism through the use of EBSD-DF images with known conditions. In fact, because it permits to go back and forth from the EBSD-DF image to the EBSPs images, it will provide a simple and efficient way to relate the intensity of specific regions of the image to a virtual beam on the EBSP. This will lead to interpret more easily and rapidly the contrast observed on the ECCI and DF images in the SEM.

5.2. Limitations Acknowledgments As mentioned above, an important limitation, nowadays, is the long dwell time necessary for acquiring EBSD maps with the full resolution of the EBSD camera, although the miniaturization and the efficiency of the new generation of charge coupled devices tend to reduce dwell times at high EBSP image resolution. This is a key parameter because a high EBSP angular resolution is necessary to approach the contrast of standard ECCI images based on ECPs as shown with the comparison of the ECP and EBSP in Fig. 1. The work reported here should give even more credits in developing fast, efficient, and resolutive EBSD detectors in the future to apply more routinely this technique to any deformation characterization work. In addition to this, and similarly to the work reported by Wilkinson and Randman [28], the choice of the reference EBSP for the selection of the specific reflections to be used is critical. In both procedures, a strain free region is required to compare the deformed structures observed in the EBSD-DF images with a nondeformed area. Also, as reported by Britton [29], the accurate definition of the pattern centre in EBSPs is mandatory if quantitative interpretation of the strain-induced contrast is to be undertaken. This will be a necessary direction of progress in the future to bring this technique to a high level of precision.

6. Conclusions Similarly to ECCI where the intensity at the centre of the ECP is reported on each pixel of the BSE image, a technique was developed to generate offline orientation images with controlled crystallographic conditions. It is based on the stored EBSP at each pixel of a map, and the resulting DF images were given the name of EBSD-DF images. The offline process allows improving the quality of the final image by choosing the virtual beam collection area (number of pixels) to be used in the EBSP for the image reconstruction in order to enhance contrast and reduce noise. With only one EBSD scan, one can generate as many EBSD-DF images as the number of pixels in the EBSP image, i.e., tens of thousands images. By selecting specific reflections on a reference EBSP, the deformation of micro-hardness indents was assessed more precisely. Moreover, a high contrast was achieved when a

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