APPLICATION OF SYNCHROTRON MICROTOMOGRAPHY … · matrix. For example, the ... the transport of...

Advances in Civil Engineering Materials The 50-year Teaching and Research Anniversary of Prof. Sun Wei, 15 October 2008, Nanjing, China

APPLICATION OF SYNCHROTRON MICROTOMOGRAPHY AT SPring-8 FOR MICROSTRUCTURE INVESTIGATIONS OF CEMENTITIOUS MATERIALS

Michael Angelo B. Promentilia (1), Takafumi Suhiyama (1), Takashi Hitomi (2) and Nobufumi Takeda (2)

(1) Environmental Material Engineering Laboratory, Division of Built Environment, Graduate School of Engineering, Hokkaido University, Japan

(2) Civil Engineering Materials Department, Technical Research Institute, Obayashi Corp., Japan

Abstract Concrete has been a ubiquitous material in many infrastructures throughout the world. The durability of this cementitious material is influenced by the microstructure of the cement paste matrix. For example, the transport of aggressive species through concrete structures is influenced by the pore interconnectivity and tortuosity in the cement paste. Thus, observations of microstructures in three dimensions (3D) become increasingly important nowadays as this allows even better understanding or modeling of such durability-related phenomena. Synchrotron microtomography, a noninvasive and nondestructive 3D imaging technique, allows us to visualize the microstructure at a spatial resolution on the order of micrometers. This paper describes the application of synchrotron microtomography at SPring-8, Japan to study the internal microstructure of cementitious materials at high spatial resolution with a voxel size down to 0.5 µm. 3D image processing and analysis routines such as segmentation and cluster multiple labeling technique were applied to high resolution microtomographic images of various specimens to extract and quantify features of interest in the microstructure. For example, the pore spaces that were extracted from microtomographic images were analyzed for porosity and pore connectivity. Diffusion tortuosity associated with the 3D micro-geometry of pore structure was also evaluated by employing a random walk simulation in the percolating pore space. The pore structure resolved from microtomography and the tortuosity derived from random walk simulation were found to be strongly correlated.

Keywords: microstructure, synchrotron microtomography, SPring-8, pore connectivity, tortuosity

223


1. INTRODUCTION

In many infrastructures throughout the world, concrete has been become a ubiquitous construction material. For a particular post-construction, durability performance of concrete must be assessed as these materials could be subjected to severe environmental conditions during the lifetime of the structure. It is known that durability of this cementitious material is influenced by the microstructure of the cement paste matrix. For example, the transport of aggressive species through concrete structures is influenced by the pore interconnectivity and tortuosity in the cement paste. Thus, observations of microstructures in three dimensions (3D) become increasingly important nowadays as this allows even better understanding or modeling of such durability-related phenomena. In this regard, synchrotron microtomography is a viable noninvasive and nondestructive imaging technique for three dimensional (3D) microstructure investigations of cement-based materials at spatial resolution of micron scale.

Synchrotron microtomography is similar in principle to medical or industrial computed tomography (CT) wherein volumetric measurements of the X-ray attenuation coefficient are obtained, creating images that map the variation of the X-ray attenuation coefficient within objects. However, the use of synchrotron radiation as X-ray source has several advantages compared to that of medical or industrial X-ray source. These include (i) a high photon flux permits measurements at high spatial resolution; (ii) the X-ray source is tunable, thus allowing measurements at different energies; (iii) the X-ray radiation is monochromatic, which eliminates beam hardening effects; and (iv) the beam is flat which simplifies the reconstruction [1-2].

This technique has therefore received considerable attention as a nondestructive 3D imaging method for cement and concrete research (e.g., see [3-10]). The continuing improvements of synchrotron imaging set-ups predestine the use of synchrotron microtomography as a powerful tool for microstructural investigations of cement paste [7]. Herein, we report the results of our studies as regard to the application of this technique to examine and characterize the pore microstructure of cement paste matrix using the X-ray CT system in SPring-8, Japan.

2. MATERIALS AND METHOD

2.1 Specimen preparation Four different specimens were investigated in this paper. From hardened cement pastes of

water-to-cement ratio of 0.50, shards of about 1 mm at its greatest width and 1 mm in length were prepared for microtomographic examinations. The three specimens namely OPC50-2d, OPC50-7d, and OPC50-28d were obtained from hardened cement paste of different ages of 2, 7 and 28 days of curing, respectively. On one hand, the fourth specimen referred to as OPC50-De was obtained from a deteriorated cement paste.

The OPC refers to the cement used in this experiment which is an ordinary Portland cement commercially available in Japan and designated as JIS R5210. By mass, this type of cement contains 67.80% of CaO, 21.30% of SiO2, 3.80% of Al2O3, 2.41% of Fe2O3, and 2.20% of SO3. The fineness of the OPC in terms of Blaine specific surface area is 3200 cm2/g.

In the preparation of cement paste (w/c = 0.50), chemical admixture was also added to the batch mix to prevent segregation. After the pre-determined age of curing, the samples were crushed and the crushed pieces were treated with acetone to suspend the hydration followed by drying under vacuum. Then, these prepared samples were stored in a sealed container prior

224


to the X-ray CT experimentation. In this way, the age of the hardened cement pastes prepared from the single batch mix allowed us to evaluate the pore microstructure evolution.

As for specimen preparation of the deteriorated cement paste, another sample was cured further for 20 weeks and then subjected to the accelerated leaching tests described in [11-12]. This leaching test based on the principle of electrochemical migration is shown to simulate the long-time degradation of cementitious material due to leaching of calcium ions when in contact with water. Note that the application of electrical field accelerates the dissolution of hydrated cement products such as portlandite as the cations such as the Ca2+ move rapidly to the cathode side. After the accelerated leaching test of the sample for 13 weeks, the deteriorated cement paste nearest to the cathode side was cut in preparation for microtomographic examination.

Figure 1: The experimental set-up of X-ray CT system in SPring-8.

2.2 Image acquisition, processing and analysis

Microtomographic images were acquired at high spatial resolution using the X-ray CT system (BL20XU) in SPring-8 (Super Photon ring-8 GeV). SPring-8 is located at Hyogo, Japan and it is one of the world’s largest third generation synchrotron radiation facility. A schematic illustration of synchrotron microtomography is shown in Figure 1. The X-ray CT system in SPring-8 consists of an X-ray light source from the beam line, double crystal monochromator, high precision rotation stage, and high resolution X-ray image detector [13]. In this study, the X-ray energy was tuned to X-ray beam energy of 15 keV. Using a high precision rotation stage, the image was taken at different views through 180 degrees rotation. The transmitted images are then detected by X-ray imaged detector which consists of thin scintillator, optic system and CCD camera. Tomographic reconstruction is done using a public domain computer program in use at SPring-8, which employs the convolution back projection algorithm to generate the slice images. The stack of these slices provides the reconstructed volumetric data of the scanned object. The reconstructed 3D-image data set was composed of

225


1300 contiguous grayscale images where each slice image contained 2000 x 2000 voxels (volume element or 3D pixel). The effective size of a cubic voxel in the CT image is 0.50 µm.

Normalization or contrast stretching was applied to the whole stack of the reconstructed slices to even out the brightness and contrast variation between the slices, as well as, to enhance the contrast in the said images. In the normalization process, the set of images was also down-sampled from 16-bit to 8-bit grayscale images resulting in a smaller image file size. To reduce the computational time and resource, a cubic volume of interest (VOI) of 2003 voxels was then extracted from the original data set for further image analysis. SLICE, a basic 3D-image analysis program developed in SPring-8, was used for pore segmentation and cluster labeling of the images in the VOI [14].

For pore segmentation, global thresholding was used to separate the pore from the “solid” matrix by defining the range of grayscale value (GSV) associated with pore voxels. The lower bound of GSV associated with pore voxels was set to 0 while the upper bound is set to the pore threshold value on the basis of transition point in segmented porosity-threshold dependency curve [10]. At this threshold value, the segmented porosity started to increase rapidly wherein the boundary between pore and the solid matrix is most likely to be segmented as pore space.

After pore segmentation, pore connectivity analysis was then performed on the basis of cluster multiple labeling that is commonly described in percolation theory [15]. In this analysis, pore voxels are considered connected to form the “pore cluster” when these voxels are in face-to-face contact to each other. In other words, two voxels are considered to be connected when the said pore voxel shares a common face with the other whereas if the pore voxels are in contact only at the vertex or edge, then the voxels are considered to be disconnected. This cluster multiple labeling procedure allowed us then to identify the largest percolating pore cluster if any from the other smaller isolated or dead-end pore clusters. The criterion we used to define percolation here is when this pore cluster is connected to the surface boundary of the cubic VOI. In other words, the largest percolating pore cluster contains pore voxels that are connected to the six faces of the VOI such that an external species can enter through this cluster to one of the faces and then exit to any of the faces. Thus, the largest percolating pore cluster is assumed to be the connected pores that most likely contribute to the macroscopic transport in the cement matrix.

After extracting the largest percolating pore space, random walk simulation was performed in the digitized pore space to probe the pore geometry and quantify the diffusion tortuosity [10,16]. Diffusion tortuosity is defined as the ratio of the self-diffusion coefficient of non-sorbing walkers in free space to the long-time self-diffusion coefficient of these walkers in pore space. A 3D random walk algorithm [16] was implemented in Mathematica to compute the mean-square displacement of random walkers in a simple cubic lattice with mirror image boundary conditions. In general, the program simulates the random migration of several walkers on the digitized connected pore space. For example, a pore voxel is chosen randomly by a walker as the starting position of the lattice walk at integer time equal to 0. The walker then executes a random jump to one of the nearest pore voxels and the time of lattice walk is incremented by a unit integer time after the jump. If the randomly selected voxel is a solid voxel, the jump is not performed but the time is still incremented by one unit. This is analogous to the restricted motion of the ‘blind ant trying to escape in the labyrinth’ as described in percolation theory to simulate the diffusion of a particle in a disordered media [15].

226


3. RESULTS AND DISCUSSION

The representative slices obtained from each specimen after the normalization process is shown in Figure 2. The slices are 8-bit grayscale images such that the grayscale value (GSV) of 0 and 255 are imaged as black and white voxels, respectively. Note that the brightness intensity of each voxel in the microtomographic images is proportional to the measured X-ray attenuation coefficient that is strongly correlated with mass density. Hence, the background or surrounding air is imaged as very dark voxels in contrast to the foreground or the scanned object. In addition, the darker voxels in the foreground image correspond to low density phases (e.g., air voids or pores), whereas the brighter voxels denote the high density phases component (e.g., anhydrous cement) in the cement paste. On one hand, the light gray to medium gray voxels that are distributed all over the cross-section are most likely associated with the hydrated cement products. Note that gray patchy regions were also observed in Figs. 2a-2c.

Figure 2: Representative slices of the specimen (voxel size = 0.5 µm).

An example of the VOI extracted from the original data set and the corresponding 3D images after pore segmentation and cluster labeling is shown in Figure 3. From the images after pore segmentation, the segmented porosity was quantified by dividing the number of pore voxels (imaged as blue voxels in Fig. 3b) to the total number voxels (2003) in VOI. From this segmented porosity, the largest percolating cluster (labeled as blue) was identified and differentiated from the isolated or dead-end pore clusters (labeled as green) as shown in

227


Fig.3c. The degree of pore connectivity was then quantified by dividing the number of pore voxels in the largest percolating pore cluster by the total number of pore voxels in the VOI. If all pore voxels in the segmented porosity are connected to each other, then the pore connectivity is equal to one. Moreover, we computed the effective porosity that is open and percolating in three orthogonal directions by multiplying the degree of pore connectivity to the segmented porosity. Figure 4 summarizes the results from pore segmentation and connectivity analysis of the VOI of each specimen. As expected, the deteriorated paste exhibited a much larger porosity and degree of pore connectivity as pores of larger size are detected that are attributed primarily to the dissolution of portlandite. On the other hand, the porosity and degree of pore connectivity of hardened cement pastes tend to decrease as aging progresses. It should be borne in mind that the interpretation of these results depends on the digital resolution of the microtomographic images. As the spatial resolution of the synchrotron microtomography is limited to 0.5 µm, a greater number of pores may not be detected appropriately as pores become finer and becomes much less than 0.5 µm. Nevertheless, synchrotron microtomography allow us to examine the 3D micro-geometry of the pore structure paste at spatial resolution relevant to the physical length scale of interest that mainly controls the transport properties of cement paste [4,10].

Figure 3: Example of VOI and 3D image after pore segmentation and cluster multiple labeling

228


0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

Seg. porosity Connectivity Eff.porosity

Por

osity

or d

egre

e of co

nnec

tivity

OPC50- 2d

OPC50- 7d

OPC50- 28d

OPC50- De

Figure 4: Computed porosity and pore connectivity in the VOI of the specimen

Figure 5: Output from random walk simulation.

Figure 5 describes the results from the random walk simulation in largest percolating pore cluster. Note that a random walk simulation was also performed in free space (i.e., porosity = 100%) of the same VOI size to serve as a reference. Figure 5 shows the sample trajectory of a walker in the 3D pore space and the output from the random walk simulation. In this figure, the dimensionless mean square displacement (MSD) averaged over 100,000 walkers is plotted

229


against the time (t) of lattice walk (maximum of 1.2 million steps). At 100 % porosity, the mean square displacement of walkers was observed to be directly proportional to the time of the lattice walk as this indicates unconstrained diffusion in free space. On the other hand, results from random walk simulation in pore space shows a curve of MSD against time as this indicates restricted diffusion resulting in a reduced self-diffusion coefficient of the walkers as they probe the tortuosity of the pore space. At long-time diffusion, the slope of MSD against time would correspond to the inverse (diffusion) tortuosity of the pore space. As expected, the slope and the resulting diffusion tortuosity in free space was computed to be equal to 1.0. On the other hand, the less steeper slope in that of the OPC50-De, OPC50-2d, OPC50-7d, and OPC50-28d indicated tortuosity values of greater than 1.0, and in increasing order, respectively. Figure 6 summarizes the pore structure characteristics of each specimen in terms of porosity, degree of pore connectivity and tortuosity. Indication suggests that tortuosity is correlated with the connected pore space that can be resolved by synchrotron microtomography. As shown in Figure 7, the effective porosity and the tortuosity derived from random walk simulation were found to be strongly correlated according to a power law function. Using a nonlinear regression analysis based on Levenberg-Marquardt algorithm, the fitting parameter (i.e., power law exponent) was found to be about 2.

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

OPC50- 2d OPC50- 7d OPC50- 28d OPC50- De

Por

osity

or de

gre

e o

f connect

ivity

1

21

41

61

81

101

121

141

161

181

Diff

usi

on tort

uosity

Seg. porosity Connectivity Eff.porosity Tortuosity

Figure 6: The pore structure parameters computed from the VOI of specimens.

230


Figure 7: The effective porosity-diffusion tortuosity correlation using a power law

model.

4. CONCLUSION

Synchrotron microtomography at SPring-8 allows us to examine directly the 3D micro-geometry of pore structure at spatial resolution down to sub-micron scale (voxel size = 0.5 µm). This paper presents a method to quantitatively characterize the 3D pore space from the high-resolution microtomographic images of cement pastes cured at different ages, as well as, that of the deteriorated cement paste. 3D-image analyses particularly pore segmentation and cluster multiple labeling were performed on the microtomographic images to gain information on the porosity and pore connectivity, respectively. 3D random walk simulation in the largest percolating pore cluster was also conducted to evaluate the so-called diffusion tortuosity. Indications suggest the pore structure resolved from microtomography and the diffusion tortuosity derived from random walk simulation were found to be strongly correlated. Future research would involve further investigation on the robustness of the method in quantifying these pore structure parameters and its potential application to predict the transport properties of cement-based material.

ACKNOWLEDGEMENTS

Part of this research work was funded by the Japan Society for the Promotion of Science (Research No.19360193, A representative: Sugiyama Takafumi). The synchrotron radiation experiments were performed at the BL20XU in SPring-8 with the approval of the Japan Synchrotron Radiation Research Institute (JASRI) (Proposal No. 2007A1951-NL-np). The first author also acknowledges the postdoctoral fellowship support from the Japan Society for the Promotion of Science (JSPS).

231


REFERENCES

[1] Kinney J.H. and Nichols M.C. ‘X-ray tomographic microscopy using synchrotron radiation’ Ann. Rev. Materials Sci, 22 ( 1992) 121–152.

[2] Ashbridge, D., Thorne, M., Rivers, M., Muccino, J., and O’Day, P.A. ‘Image optimization and analysis of synchrotron X-ray computed microtomography data’, Computers and Geosciences, 29(8) (2003) 23-836.

[3] Bentz, D.P., Quenard, D.A., Kunzel, H.M., Baruchel, J., Peyrin, F., Martys, N.S. and Garboczi, E.J. ‘Microstructure and transport properties of porous building materials. II: Three-dimensional X-ray tomographic studies’ Mater. and Struct. 33(3) (2000) 147-153.

[4] Bentz, D.P. Mizell, S., Satterfield, S. Devaney, J., George, W., Ketcham, P., Graham, J., Porterfield, J., Quenard, D., Vallee, F., Sallee, H., Boller, E., Baruchel, J., ‘The visible cement data set.’ Journal of Research of the National Institute of Standards and Technology, 107 (2002) 137-148.

[5] Burlion, N., Bernard, D. and Chen, D. ‘X-ray microtomography: Application to microstructure analysis of a cementitious material during leaching process’ Cem. Concr. Res. 36(2) (2006) 346-357.

[6] Gallucci, E., Scrivener, K., Groso, A., Stampanoni, M. and Margaritondo, G., ‘3D experimental investigation of the microstructure of cement pastes using synchrotron X-ray microtomography’ Cem. Concr. Res, 37(3) (2007) 360-368.

[7] Helfen, L., Dehn, F., Mikulik, P., and Baumbach, T. ‘Three-dimensional imaging of cement microstructure evolution during hydration.’Advances in Cement Research, 17(3). (2005) 103-111.

[8] Hitomi, T., Mita, Y., Saito H.and Takeda, N. ‘Observation of fine structure of mortar using X-ray CT images at SPring-8’ Proceedings of Annual Conference of Japan Concrete Institute, 26 (1) (2004) 645-650 (in Japanese).

[9] Lu, S., Landis, E.N., and Keane, D.T., “X-ray microtomographic studies of pore structure and permeability in Portland cement concrete.” Materials and Structures, 36(1)(2006) 11-20.

[10] Promentilla, M.A.B., Sugiyama, T., Hitomi, T. and Takeda, N. ‘Characterizing the 3D pore structure of hardened cement paste with synchrotron microtomography’ Journal of Advanced Concrete Technology, 6(2) (2008), 273-286.

[11] Saito, H., Nakane, S., Ikari, S. and Fujiwara, A. ‘Preliminary experimental study on the deterioration of cementations materials by an acceleration method’ Nuclear Engineering and Design, 138 (1992) 151–155.

[12] Sugiyama, T., Promentilla, M.A.B., Hitomi, T. and Takeda, N. ‘Quantification of pore structure characteristics for deteriorated mortar due to calcium leaching’ Abstract proceedings of 2nd International Workshop: Mechanisms and modelling of waste/cement interactions, Le Croisic, France, October 12-16, 2008.

[13] Uesugi, K., Suzuki, Y., Yagi, N., Tsuchiyama, A. and Nakano, T. ‘Development of high spatial resolution X-ray CT system at BL47XU in SPring-8’ Nuclear Instruments and Methods I Physics Research A, 467-468 (2)(2001) 853-856.

[14] Nakano, T., Tsuchiyama, A., Uesugi, K., Uesugi M., and Shinohara, K. ‘SLICE –Software for basic 3-D image analysis [online]’. (Japan Synchrotron Radiation Research Institute (JASRI), 2006, http://www-bl20.spring8.or.jp/slice/).

[15] Stauffer, D., and Aharony, A., “Introduction to percolation theory.” Revised 2nd ed. (Taylor and Francis, London, 1994).

[16] Nakashima, Y., and Kamiya, S. ‘Mathematica programs for the analysis of three-dimensional pore connectivity and anisotropic tortuosity of porous rocks using X-ray microtomography.’ Journal of Nuclear Science and Technology, 44 (9)(2007) 1233-1247.

232

APPLICATION OF SYNCHROTRON MICROTOMOGRAPHY … · matrix. For example, the ... the transport of...

Documents

Transcript of APPLICATION OF SYNCHROTRON MICROTOMOGRAPHY … · matrix. For example, the ... the transport of...