Determination of the porosity and pore size distribution of SiC ceramic ...

Determination of the porosity and pore size distribution of SiC ceramic foams by nuclear methodologies A. C. Moreira*1, C. R. Appoloni2, W. R. D. Rocha2, L. F. Oliveira3, C. P. Fernandes1 and R. T. Lopes4 Two nuclear methodologies were used for porosity and pore size distribution determination of SiC ceramic foams. Thirty samples were analysed, six of each one of the following pore densities: 30, 45, 60, 80 and 100 pores per inch (ppi). The two nuclear techniques employed were X-ray microtomography and gamma ray transmission. For the microtomography technique, the spatial resolution of the images was 32 mm. For the gamma ray transmission methodology, a NaI (Tl) scintillation detector and Am-241 radioactive source were used. The gamma transmission technique was precise for porosity determination in relationship to the nominal values supplied for the sample manufacturer. The 30 and 45 ppi samples analysed by the microtomography technique present average porosities equivalent to the nominal porosity, and the other samples present an average of 4?6% smaller values. The 30 and 45 ppi sample two-dimensional images show voids inside the structural solid material of the ceramic. Keywords: SiC ceramic, Porosity, Pore size, Gamma ray transmission, X-ray Microtomography

Introduction Silicon carbide ceramic foams are highly porous, low density and low mass materials with high strength, high resistance to chemical attack, high temperature resistance and high structural uniformity.1 SiC foams have a structure formed by three-dimensional arrangement of interconnected filaments and are employed to filter molten metals and hot gases. Two properties can be used to characterise the pore medium of the foams: the pores size distribution and the porosity. Commercial SiC foams generally exhibit a pore density in the range from 10 to 100 pores per inch (ppi), which corresponds to porosity from 88 to 95%. Most of the conventional methods for sample porosity determination, such as Hg porosimetry,2 Archimedes method,3 helium pycnometry and optical materialography,4 are destructive, require sample preparation and supply global average results for the whole sample.

1

Porous Media and Thermophysical Properties Laboratory (LMPT), Mechanical Engineering Department/PGMAT, Federal University of Santa Catarina, PO Box 476, Floriano´polis 8040-900, Brazil 2 Applied Nuclear Physics Laboratory (LFNA), Physics Department, State University of Londrina, PO Box 6001, Parana´ 86051-990, Brazil 3 Physics Institute (DFAT), Rio de Janeiro State University, Saõ Francisco Xavier Street, 524, B bloc, Rio de Janeiro 20559-900, Brazil 4 Nuclear Instrumentation Laboratory (LIN/COPPE), Federal University of Rio de Janeiro, Technology Center (CT) I bloc, I-133, PO Box 68509, Rio de Janeiro 21941-972, Brazil *Corresponding author, email [email protected]

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Nuclear techniques has become non-destructive alternatives for the characterisation of porous media.5–7 The gamma ray transmission and X-ray microtomography can be applied for structural characterisation of ceramic foams to evaluate porosity and pore size distribution.8–10 This paper shows the application of the nuclear techniques in the porous characterisation of SiC foams. The samples have pore densities of 30, 45, 60, 80 and 100 ppi.

Theory Gamma ray transmission technique The relationship between the attenuated radiation intensity by a sample and other parameters of the system can be written as I~I0 e{m’x

(1)

where I0 and I are the incident and emergent gamma ray beam intensities respectively (cont s21), m9 is the linear attenuation coefficient of the sample (cm21) and x is the thickness of the sample (cm). The mass attenuation coefficient m (cm2 g21) can be written as (2)

m~m’=r 2

21

where m is the mass attenuation coefficient (cm g ), and r is the density of the sample (g cm23). The porosity determination of the sample, in relation to its linear attenuation coefficient, is calculated by the following equation11 ß 2010 Institute of Materials, Minerals and Mining Published by Maney on behalf of the Institute Received 4 December 2009; accepted 26 March 2010 DOI 10.1179/174367510X12722693956158

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mp {ms g~100 mp

(3)

where g is the total porosity (open and close pores), mp is the linear attenuation coefficient of the samples that are totally solid (same material of the sample but without pores) and ms is the linear attenuation coefficient for the porous sample, both in square centimetre per gram. mp values can be found in tables or be determined on WinXCom software.12

X-ray microtomography technique X-ray microtomography is a characterisation method based on the investigation of internal sample structure by image analysis. This technique consists of the linear attenuation coefficient scanning of the sample crossed by the X-ray beam. The material density differences along the sample generate different coefficients, which were mapped under diverse angle positions. Each scanning position generates a projection of the sample in a charge coupled device camera. These projections are used as an input for the image reconstruction algorithm. The reconstructed images are the two-dimensional (2D) slices of the sample, which will be used for the structural characterisation. The Fourier transform was the adopted algorithm, based on the filtered back projection method.13 Measurements were carried out at the Nuclear Instrumentation Laboratory of Federal University of Rio de Janeiro (LIN/COPPE/UFRJ, Rio de Janeiro, Brazil).

Materials and methods The ceramic foams used in this research were acquired from Erg Materials and Aerospace Corporation (Oakland, CA, USA). The chemical composition of the samples was 66% of SiC and 34% of C (specifications

Porosity and pore size distribution of SiC ceramic foams

supplied by the manufacturer). We analysed samples with nominal pore density of 30, 45, 60, 80 and 100 ppi. For each pore density three samples were analysed with the gamma ray transmission methodology, for a total of 15 samples with dimensions 26468 cm, and with the microtomography technique, for a total of 15 samples, with dimensions 16164 cm. The only exception was the 80 ppi samples, for which only two samples were measured with the microtomography technique. The nominal porosities of the samples were in the range from 83 to 91?5%. For the porosity determination by gamma ray transmission technique, the values of mp and ms in equation 1 must be previously known. To determine the linear attenuation coefficient of the sample without pores, the WinXCom software was used.8 This program supplies mass attenuation coefficient values (m/density) when the input is the radiation energy (in the range from 1 keV to 100 GeV] and the chemical composition of the sample. The linear attenuation coefficient of the porous sample was obtained by beam transmission at four depths (or measure lines) along each sample. Ten linear attenuation coefficients were determined at each line. Three samples were scanned for every pore density (30, 45, 60, 80 and 100 ppi). Three samples for each pore density were scanned. The microtomographic images were accomplished with the X-ray tube voltage set in range of 30–40 kV and the intensity of the current was 0?5 mA. Five hundred projections were accomplished during the microtomography procedure. The spatial resolution of the system was around 32 mm. The measure time of each tomography was 1?5 h. For each sample, 200 images in grey level were obtained, and 180 images of each one were analysed. Ten 2D slices from the beginning and 10 from the bottom of the image package were discarded.

1 Two-dimensional sections of SiC ceramic foams for pores density of a 30 ppi, b 45 ppi, c 60 ppi, d 80 ppi and e 100 ppi. Grey levels next to white means solid material, and grey levels next to black correspond to pores. Spatial resolution is 32 mm


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The porosity and the pore size distribution of the industrial ceramic foams were obtained from the 2D image analysis using the IMAGO software. In order to select a section inside the images to perform the characterisation, initially, a region of interest was determined. The cropped images were then segmented into binary images based on a manual threshold setting using their grey level histogram. The binary images, in black and white colours designating porous and material phases, are the representation of the microstructure. Images filters were not applied on the images, before or after the binarisation process.

Results and discussion Figure 1 shows five 2D images of some ceramic foam analysed at this study. These images register the relationship between the pore density and the material pore size. Figure 2a shows a 2D section of the 45 ppi sample and the area of interest with small pore intramaterial, and Fig. 2b illustrates the histogram that represents the variation of the grey level among porous phase (range, 20–25 and 42–47 pixels), solid matrix (25–28 and 35– 42 pixels) and intramaterial pores (28–35 pixels). In order to analyse these voids, a resin cold mounting was accomplished for the 30 and 45 ppi samples. Figure 3 presents an image obtained from optical microscopy, from the 45 ppi sample. In this image, in detail, the connections (Fig. 3a) of the voids inside the SiC material (Fig. 3b) with the external medium can be observed. The resin filled the pores of the foam (Fig. 3c) but did not attain the internal cracks (Fig. 3d). The

2 a region of interest where small intramaterial pores occur and b grey levels profile of enhanced detail

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a connections with external medium; b solid material; c region with resin; d pores inside material 3 Image of 45 ppi sample obtained by microscope6150

internal cracks of the ceramic material produce a high influence on the values of apparent density and can produce lower compression strength of the composite.14 These voids are resulted from ceramic foam processing and are formed by the removal of the polymeric strut or by an incomplete sintering process. In fact, SiC foams are processed using polymeric struts as templates. The polymeric templates are burned out of the SiC foam after the infiltration of the slurry or ceramic former material. The processing route of ceramic materials derived from polymers can be found in full detail in Colombo15 and in Bao et al.16 Similar voids are found in cordierite foams,17 hydroxyapatite scaffolds18 and in Al2O3 foam,19 the processing route of these three porous materials being similar to that for SiC foams processing. Figure 4 shows the porosity versus pores per inch of the samples, for the values supplied by the manufacturer, values found in the literature20 and values determined by gamma ray transmission and microtomography results. The values calculated in this study are shown with averaged standard deviation with 95% confidence (Gaussian statistics). Considering the standard deviation, gamma ray determined the same porosity value supplied by the manufacturer (GRT), Emeryville, CA, USA for the 60 and 80 ppi samples. For the samples of 30, 45 and 100 ppi, the small differences were 0?2, 0?6 and 0?8% respectively. The manufacturer did not provide the nominal deviation porosity data.

4 Porosity data obtained with nuclear methodologies, nominal and reference values

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7 Porosity profiles for 45 ppi sample obtained with X-ray microtomography technique

5 Porosity profiles for 45 ppi gamma ray methodology

sample

obtained

with

6 Porosity profiles for 80 ppi gamma ray methodology

sample

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8 Porosity profiles for 80 ppi sample obtained with X-ray microtomography technique

Considering the values supplied by the manufacturer (microtomography) and those determined by X-ray microtomography in Fig. 4, it can be noticed that the smaller differences of 0?3 and 0?7% on the porosity data were found for the samples of 30 and 45 ppi respectively. For the 60, 80 and 100 ppi, the differences in porosity were 2?2, 6?7 and 4?7% respectively. The porosity profiles of the samples were determined with the two nuclear methodologies. Most of the conventional methodologies determine global porosity of the samples. The techniques presented at this paper are able to analyse specifics regions of specimens. Thus, the variation of the porosity along the samples can be accessed, defining a porosity profile.21,22 Macroscopic physical properties of porous materials, such as mechanical strength, depend upon pore structure, especially porosity. Amirthan et al.23 found flexural strength inconsistency of Si/SiC and SiC samples due to the inhomogeneous porosity distribution within the samples. Fernandes et al. produced glass ceramic foams from industrial residues with different amounts of SiC.

They concluded that the compressive strength is not only influenced by apparent density but also by the internal porosity and thickness of the struts and the crystalline phase composition.24 Wu et al. also produced glass foams with incorporation of SiC as foaming agent and reported the influence of apparent density and pore morphology in mechanical properties.10 The aim of the present study was just to analyse the spatial variation within the samples verifying the heterogeneity its porosity distribution. Figures 5 and 6 show two of these profiles for the 45 and 80 ppi samples, which were obtained from the gamma ray transmission technique along four different depths of the samples. Figures 7 and 8 present the porosity profiles for the samples with the same pores per inch number, obtained from the X-ray microtomography technique. Table 1 presents a summary of the pore radius range obtained with pore size distribution of the samples (microtomography method) and the range supplied by the manufacturer (nominal data). The nominal data are the pore radius range predominant for each sample; the manufacturer did not provide the frequency (%) value.

Table 1 Pores size intervals Manufacturer

X-ray microtomography

Sample, ppi

Predominant pore radius range, mm

Pore radius range, mm

Pore radius frequency, %

30 45 60 80 100

650–915 455–570 350–415 255–325 205–255

653–915 430–595 324–418 226–323 193–249

52.6 47.1 21.4 33.9 33.2


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higher than 60 need a better spatial resolution for their structural characterisation. Two important goals of the nuclear techniques employed in this research were the non-destructive way to SiC foams structural characterisation and the determination of the porosity profile of the samples, whereas most of conventional methodologies analyse the whole sample.

Acknowledgements The authors thank the PROCAD/CAPES project for the financial support in collaboration with the LMPT/ UFSC and the CAPES, which supplied the scholarship for two of the authors.

References

9 a 80 ppi ceramic foam pore size distribution and b 100 ppi ceramic foam pore size distribution

The considered frequency interval was obtained by the frequency histograms, as shown in Fig. 9a for the 80 ppi sample and Fig. 9b for the 100 ppi sample. All pore size distributions present an asymmetric mode, and the left side of the histogram has a larger frequency. The distribution becomes more symmetrical when the pore density increases, as can be verified at Fig. 9b (100 ppi distribution). The spatial resolution of 32 mm reached by the X-ray microtomography method was not ideal to characterise the samples with pores per inch bigger than 60. Figure 5 shows the discrepancies on the porosity values for the samples with pores per inch bigger than 60 in relation to the nominal values.

Conclusions The gamma ray transmission technique showed to be a powerful tool for the non-destructive quantification of the porosity of the SiC ceramic samples analysed in this research. The differences found between determined and nominal porosity values were very limited. The applied microtomography system was able to structurally characterise the 30 and 45 ppi samples with the spatial image resolution of 32 mm. With the images of 30 ppi samples, it was possible to observe the presence of small voids inside the solid material. The presence of these small voids would justify the average porosity obtained for those samples as being slightly smaller to the nominal and to the gamma ray transmission results (Fig. 4). The samples with pores per inch

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