Microfocus X-ray Computer Tomography in Materials Research (original) (raw)

·Home·Table of Contents·Methods and Instrumentation	M. WEVERS, P. DE MEESTERKatholieke Universiteit Leuven, Department of Metallurgy and Materials Engineering,W. de Croylaan 2, 3001 Leuven, BelgiumR. SWENNENKatholieke Universiteit Leuven, Department of Geology, Fysico-chemical GeologyCelestijnenlaan 200C, 3001 Leuven, BelgiumScientific researchers: M. Van Geet, H. Van Oosterwyck, and A.-H. Benouali Contact

Introduction.

Computer tomography, initially implemented in the medical field, today is also used in materials research. Moreover the technology has been improved by implementing the microfocus X-ray sources in the computer tomography facilities. In microfocus computer tomography (mCT) the resolution of a system can be in the order of 10 mm x10 mm x10 mm depending on the object size, which is much better compared to the typical 60 mm x 60 mm x 1 mm resolution of the medical CT. The resolution of the two microfocus computer tomography systems available at the Department of Metallurgy and Materials Engineering (K.U. Leuven), being the desktop SkyScan 1072 computerised microtomograph (for small objects up to 4 cm3) and the AEA Tomohawk CT system on the Philips HOMX 161 microfocus system (for large objects up to 5 kg), is indicated in Table 1.

In this paper the usefulness of the mCT in different fields of material science is discussed with emphasis on sedimentary geology, research on bone remodelling around biomedical implants, research on light weight metal foams and electronic components. The various examples illustrate how mCT can be used quantitatively to investigate the microstructure and the behaviour of micro-heterogeneous structural materials. The vast number of examples also reflects the multidisciplinary use of the equipment and indicates how progress in one field can be beneficial to the other. Before this discussion some techniques will be presented to improve the image quality and to minimise artifacts.

Optimising techniques to enhance mCT images and to reduce artifacts.

If some internal feature of a material needs to be determined accurately in size or the material needs to be characterised based on density measurements for instance, artifacts in the reconstruction of a CT image must be avoided or minimised.
Ring artifacts are caused by inhomogeneities of the detector and are minimised by randomly moving the object and with it the field of detector used (Skyscan, 1997; Burch et al., 1998)
Star or streak artifacts are caused by secondary radiation that augments the noise and creates the artifacts. Metal filters such as aluminium (Al) or copper (Cu) placed in front of the detector can suppress to a major extent the star artifacts because they help to reduce the secondary radiation. However, some of the primary radiation will also be attenuated and as a consequence the contrast will be lowered. (ISO/WD 15708-2 and J. Baruchel et al., 2000)
Beam hardening is a consequence of the polychromatic X-rays used in a CT. The differential attenuation of photons within the investigated object leads to the rapid attenuation of the lowest energy photons and hence to the gradual increase of the mean energy. Beam hardening or cupping effect is the anomalous decreasing attenuation toward the center of a homogeneous object and to reduce it a mathematical correction at some stage in the reconstruction process can be very effective. Many systems allow the option of applying such a correction. Beam hardening can also be reduced by going to higher source energies or filtering the low energy content of the incident radiation with metal filters placed between the X-ray source and the object, or both. (ISO/WD 15708-2 and J. Baruchel et al., 2000)

Microfocus computer tomography in sedimetary geology.

Current research of mCT in geological sciences focuses on the characterisation of reservoir rocks (Tricart et al., 2000; Van Geet et al., 2000a) like sandstones, carbonates and coal. The most important advantage of the mCT is the possibility of 3D visualisation and quantification of porosity and mineralogical pore-relating phases. Classical geological studies are based on 2D light microscopy techniques on thin sections and polished surfaces. To validate the mCT-data, 2D slices will be correlated with other 2D classical techniques, like light microscopy and scatter electron microscopy. Such a correlation is currently worked out for coal samples (Van Geet et al., 2000b) and will be performed on classical sand and carbonate reservoirs and on igneous rocks. To perform such correlations, however, an optimisation of the image quality was originally the most important research topic. In this respect two artifacts mostly degrade the image quality of reservoir rocks. The first one is a star artifact caused by secondary radiation. This artifact is especially related to high attenuating materials and consequently important for studies on sedimentary rocks with iron-containing minerals (pyrite). The second artifact is beam hardening, which is again most pronounced in high attenuating materials like quartz, carbonates and iron containing minerals. The artifacts are reduced by placing metal foils in front of the detector system, which cut off the lower X-ray energies that cause the artifacts (Van Geet et al., 2000a).
Once a good image quality is realised, characterisation of the different mineral phases can be carried out. However, the linear attenuation coefficient of mineral phases is a poorly known parameter. As the latter depends mainly on the density and the atomic number of the studied object and the used X-ray energy, a dual energy technique is worked out (Alvarez and Mackovski, 1975; Coenen and Maas, 1994; Van Geet et al., 2000a). Here, the same sample is scanned at two different energy levels and, after a calibration procedure, the density and atomic number information of the internal features on voxel level can be extracted. The data of the density measurements are the most reliable, because this information is incorporated in the high energy photons, which have a higher flux when using metal foils as filters. Figure 1 shows the correlation between the real density of some calibration samples and the linear attenuation coefficient at two different energies. Figure 2 shows the enhanced correlation by using the dual energy technique. The density is obviously easier to interpret since it corresponds to parameters often used in petrophysical research.

Further research on the use of mCT will be focused on the characterisation of fractured reservoirs, which involves a 3D quantification of fracture sizes and orientation. Other research topics will focus on dynamic processes. Firstly, it will focus on a two component system, namely free water uptake measurements, which enable the visualisation and quantification of moisture content profiles of several materials. Subsequently, a three component system can be analysed, like enhanced oil recovery, in which oil displacement by means of different gases or fluids is tested. Some examples are given here, which illustrate the usefulness of a three-dimensional visualisation of geological samples. Other examples can be found in Van Geet et al. (2000a).

A first example (figure 3) shows a porous carbonate of 8 mm in diameter. At this magnification, a voxel size of about 22 mm in three dimensions is achieved. The carbonate is build up of oolites and fossils, especially shell material. The shell material is now dissolved and represents a secondary pore. Oolites are small spherical carbonate parts. Here they have been dissolved and cause the high porosity. The pores are clearly visualised by their white colour, which represents the attenuation of air.

A second example (figure 4) shows another oolitic reservoir rock, which shows some precipitates within the pores. The dual energy technique has been used to discriminate several minerals and to estimate the porosity of the sample. A gypsum crystal (arrow), barite precipitates (blue colour) and carbonate were found and the porosity was estimated at about 20% (Van Geet et al., 2000).

Microfocus computer tomography for research on bone remodelling around biomedical implants.

Recent research has proved that the mCT can be of great value to study the microstructure and the remodelling behaviour of trabecular bone (Feldkamp et al. 1989, Rüegsegger et al. 1996). The high resolution enables individual trabecels to be seen. For the first time mCT has been used to study the bone structure around titanium oral screw implants (Van Oosterwyck et al. 1999). Bone-implant specimens were scanned with a resolution of 60 mm. Due to the large difference in attenuation coefficient between titanium and bone it is not easy to obtain optimal images. The trabecular bone structure as well as the differences in bone densities in the screw windings are clearly visible. The advantages of the mCT in this research are: speed, nondestructive character, complete threedimensional characterisation of the bone structure around the implant, reconstruction of 2D images in oblique slices and 3D reconstruction facilities. (figure 5 and 6)

The obtained results are promising and show a good correlation with the histological slices. (figure 7) The mCT therefore offers a valuable alternative for the classic histological techniques to study the osseointegration process with implants. The mCT also allows an in vivo evolution of the bone remodelling around implants when small animals are involved, reducing hereby drastically the number of animals to be sacrificed. The mCT data are also being used to generate precise finite element models of the trabecular bone structure around the implant. (figure 8a and 8b)

In this way the stress transfer between implant and bone can be analysed on a microstructural level. The validation of the FE models can then be carried out as well: the measured displacements in a mechanical test on a scanned specimen have to be compared with the displacements calculated via a finite element model of the same specimen and the same loading. The accuracy of the finite element modelling can therefrom be retrieved and this approach opens the possibility to simulate numerically biological mechanisms like adaptive bone remodelling.

Microfocus computer tomography of aluminium foams and electronic components.

Metallic foams are porous metals with high porosity (from 50 to 99 %). In the past few years the interest in metal foams, especially made of aluminium or aluminium alloys, has increased considerably. The unique properties of aluminium foams like high stiffness to weight ratio, high energy dissipation, low density, reduced acoustic, thermal and electrical conductivity, chemical resistance, easy recycling etc..., make them potentially useful in many high technology industries such as automotive and aerospace.
The efficient use of foams requires a detailed understanding of their mechanical behaviour. Previous models developed to predict the mechanical performance of foams have been dependent on the variation of the apparent density, the properties of the solid material from which the cell face is made, and the cell geometry. The geometrical features include cell shape and size, distribution in cell size, defect and flaws in the cell structure as well as the microstructural parameter like cell wall and edge thickness and material distribution between cell face and cell edge. Therefore a clever characterisation of this material is required. (A.-H. Benouali et al., 2000)
The mCT provides images of the internal details of Al-foams without special specimen preparation. Figure 9 shows mCT images of Al-foam samples made by a casting process. The pictures reveal a broad density distribution through the samples. One can also distinguish that the cells are oriented in a preferred direction and that there is a broad cell size distribution.

mCT images of Al-foam samples made by the powder metallurgical route are given in figure 10. The samples have an average density of resp; 0.22 and 0.35 g/cm3. Two slices at two different heights have been extracted for each sample. The cell size distribution seems to be homogeneous but the presence of big holes around the centre of the structure leads to a broad density distribution through the specimens. These holes might be caused by the foaming process itself because the latter is stopped by simply allowing the mould to cool. The temperature in the centre of this mould is still sufficiently high to enabling the foaming process to continue while it has stopped elsewhere.
Microfocus computed tomography provides 3D information of the scanned specimen concerning cell arrangement like orientation, gradient, homogeneity, etc.. Images of contiguous planes can be stacked by mean of a reconstruction algorithm to form 3D images of a section or if the entire part has been scanned, a full volumetric image of the specimen (figures 11).

Once the data are imported, the reconstruction algorithm can quickly generate slices in any orthogonal plane or at oblique angles through the 3D data volume as well as creating cut-outs in the reconstructed 3D foam structure (figures 12).

Further image processing can create binary images which can be used for quantitative measurements. Some results based on the binary image of figure 13b are presented in figure 14 and 15.

Fig 13: Manually closing and opening of cells on the binary image of an Al-foam slice (casting process)

A temperature sensor for a laundry washing machine needs to work reliable. Therefore the polymer which encapsulates the sensing device needs to be void/porosity free. Using only X-ray projection radiography to reveal those is very hard (figure 16), taking 2D slices of this component in the sensing area leads to a clear identification and even reveals the distribution of the voids over the cross section. Based on this information even temperature profiles can be pre-calculated (prior to production) or back-calculated (in case of failure).

Conclusions.

This paper discusses the possibilities of microfocus computer tomography in materials research. In this large interdisciplinary field not only high quality 2D and 3D images of the internal structure of the material can be obtained but with intelligent processing of the data even quantitative information. Several attempts in this direction have been pointed out and are subject of present research projects within the Katholieke Universiteit Leuven.

Acknowledgements:

The fund for Scientific Research (FWO) in Flanders (project number G.027.97) and the Flemish Institute for Scientific Reseach and Technology (project number IWT 950330) are acknowledged for the financial support of this research.

References.

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