- Open Access
Image Analysis and DC Conductivity Measurement for the Evaluation of Carbon Nanotube Distribution in Cement Matrix
© The Author(s) 2015
- Received: 22 September 2015
- Accepted: 26 November 2015
- Published: 18 December 2015
The present work proposes a new image analysis method for the evaluation of the multi-walled carbon nanotube (MWNT) distribution in a cement matrix. In this method, white cement was used instead of ordinary Portland cement with MWNT in an effort to differentiate MWNT from the cement matrix. In addition, MWNT-embedded cement composites were fabricated under different flows of fresh composite mixtures, incorporating a constant MWNT content (0.6 wt%) to verify correlation between the MWNT distribution and flow. The image analysis demonstrated that the MWNT distribution was significantly enhanced in the composites fabricated under a low flow condition, and DC conductivity results revealed the dramatic increase in the conductivity of the composites fabricated under the same condition, which supported the image analysis results. The composites were also prepared under the low flow condition (114 mm < flow < 126 mm), incorporating various MWNT contents. The image analysis of the composites revealed an increase in the planar occupation ratio of MWNT, and DC conductivity results exhibited dramatic increase in the conductivity (percolation phenomena) as the MWNT content increased. The image analysis and DC conductivity results indicated that fabrication of the composites under the low flow condition was an effective way to enhance the MWNT distribution.
- cement composites
- carbon nanotubes
- distribution evaluation
- image analysis
- electrical conductivity
The electrical and mechanical properties of cement composites with conductive fibers are significantly influenced by the fiber distribution (Sorensen et al. 2014; Liu et al. 2011; Lee et al. 2009). The electrical properties can be enhanced by the formation of conductive fiber networks. The mechanical properties can also be improved by the effect of fibers bridging micro-cracks, whereas they deteriorated in the base of a non-uniform distribution of fibers (Sorensen et al. 2014; Liu et al. 2011). Accordingly, evaluation of the fiber distribution is important in understanding its influence on the physical properties of the composite materials and making full use of fibers (Liu et al. 2011).
Evaluation methods for the fiber distribution can be classified into two categories—image analyses and electrical property analyses. An image analysis entails acquisition of images via a microscope (optical microscope, scanning electron microscope (SEM), etc.) or a transmission X-ray and image processing and analysis. Lee et al. (2009) and Kang et al. (2011) obtained cross sectional images of composite materials via an optical microscope (Lee et al. 2009; Kang et al. 2011). Lee et al. (2002) and Liu et al. (2011) obtained images via digital cameras (Lee et al. 2002; Liu et al. 2011). Redon et al. (1999) used X-ray photography and Fan et al. (2000) used a SEM to capture fiber distribution images (Redon et al. 1999; Fan et al. 2000). On the other hand, the fiber distribution state can also be evaluated by the DC conductivity or AC impedance. Li et al. (2007) analyzed MWNT distribution states using the DC conductivity and Ozyurt et al. (2006) evaluated the degree of carbon fiber clumping and fiber orientation by AC impedance spectroscopy (Li et al. 2007; Ozyurt et al. 2006). In the case of the electrical property analysis method, it is only applicable to conductive fiber-incorporated composite materials.
The image analysis is a more direct and convincing approach in that actual fiber distribution states in the composite materials can be evaluated. The electrical property analysis method is an indirect approach for evaluation of the fiber distribution, but sometimes it is affected by other parameters (matrix type, moisture content in matrix, etc.), possibly leading to incorrect electrical property results. Accordingly, the image analysis plays an important role in the evaluation of fiber distributions and it is a critical technique that should be carried out along with an electrical property analysis (Li et al. 2007; Ozyurt et al. 2006).
Uncovered in 1991, carbon nanotube (CNT) has gained great attention from researchers attributable to its remarkable physical properties (Li et al. 2007; Kim et al. 2014). From 2010s, CNT has been used as a nano-scale fiber in cement-based composites in an effort to enhance physical properties of the composites (Kim et al. 2014). Various approaches have been explored to evaluate CNT distributions in the literature. SEM observation has been the most common approach to study the CNT distribution state, carried out in tandem with an electrical property analysis (Konsta-Gdoutos et al. 2010). However, the SEM observations may vary depending on observation spots in the same sample since it is mostly conducted with high magnification levels (up to 3000-fold). Accordingly, the CNT distribution should be observed and evaluated at low magnification levels and the evaluation results should be compared with electrical properties of the CNT-embedded composites.
In the present work, a novel image analysis method to evaluate the multi-walled carbon nanotube (MWNT) distribution in cement-based composites is proposed. In this approach, white cement was used instead of ordinary Portland cement (OPC) with MWNT in an effort to differentiate MWNT from the cement matrix. MWNT distribution images in the cement matrix materials were acquired by using an optical microscope in conjunction with image processing tools. The MWNT distribution was quantitatively assessed in terms of the planar occupation ratio of MWNT. In preparation of specimens, a novel method was adopted for dispersion of CNT in cement. This method was proposed on the basis of experimental attempts previously conducted by the authors. It was suggested that the distribution of CNT can be enhanced by means of lowering the fluidity of CNT/cement mixture at fresh state. It is notable that the suggested method does not require sonication technique, acid treatment, etc., which were widely demonstrated in the literature. To verify correlation between the MWNT distribution and flow of the mixtures, MWNT-embedded cement composites were fabricated under different flows, incorporating a constant MWNT content (0.6 wt%). The image analysis demonstrated that the MWNT distribution was significantly enhanced in the composites fabricated under a low flow condition, and DC conductivity measurement results revealed the dramatic increase in the conductivity of the composites fabricated under the low flow condition, which supported the image analysis results. The composites were also prepared under the low flow condition (114 mm < flow < 126 mm), incorporating various MWNT contents. The image analysis and DC conductivity results demonstrated remarkable enhancement in the planar occupation ratio of MWNT and the conductivity, respectively, which indicated that fabrication of the composites under the low flow condition was an effective way to enhance the MWNT distribution.
MWNT, Portland cement, nylon fiber, super-plasticizer, tap water, and silica fume (SF) were used in the present work. MWNT produced through the chemical vapor deposition (CVD) growth method, a proprietary product of Hyosung Inc. (M1111), was used (Nam et al. 2012). Their purity, diameter, and aspect ratio were 96.2 %, 12.29 ± 2.18 nm, and 930 (aspect ratio was approximate value), respectively. Type I ordinary Portland cement was used in the present work. SF, a proprietary product of Elkem Inc. (EMS-970 D), contained over 90 % silicon oxide (SiO) and 80 wt% of its primary particles have a diameter greater than 5 μm. White cement was used instead of OPC when image analysis samples were fabricated. Nylon fiber, a proprietary product of Nycon fibers Inc. (NYMAX), was used in an effort to prevent cracks that occur due to shrinkage while cement matrix materials cured. Their diameter and length were 23–36 μm and 3 mm, respectively. A poly-carboxylic acid-based super-plasticizer (SP), a proprietary product of BASF Pozzolith Ltd., (Rheobuild SP8HU), was utilized in an effort to improve the workability of the fresh cement matrix materials. The true specific gravity of MWNT, Portland cement, SP, tap water, and SF was 1.32, 3.15, 1.07, 1, and 2.1, respectively.
3.1 Image Analysis of MWNT Distribution in MWNT-Embedded Cement Composites
3.1.1 Specimen Preparation and Image Acquisition for Image Analysis
A novel image analysis approach was proposed in an effort to evaluate the MWNT distribution in cement matrix materials. In order to distinguish MWNT with black color from OPC, which also shows a fairly dark color, white cement was used in place of OPC when composite specimens were fabricated for the image analysis. In addition to using white cement instead of OPC, the incorporation of nylon fiber was omitted in the preparation of the samples for the image analysis since crack control was unnecessary. The constituent materials (white cement, MWNT, water, and SP) were weighed according to mixing ratios and placed together in a steel bowl.
Constituent materials and their mix proportions of the MWNT-embedded cement composites fabricated under different flow.
Mix proportions (g)
Constituent materials and their mix proportions of the composites fabricated under the low flow condition (114 mm < flow < 126 mm).
Mix proportions (g)
Wt% by cement
In an effort to produce a fracture surface, a cutting knife was used to make a cutting guide line with depth of approximately 1 mm at the center of the sample. The sample was split into two parts applying manual force by hand to the cutting guide. Each split part was sliced by means of a hand saw at 3 mm from the fracture surface. As a result, a specimen with size of 10 × 10 × 3 mm3 was prepared from the original sample.
A magnification to cover MWNT agglomerates whose diameter ranged from 3 to 200 μm was selected by a trial and error process and determined as 50-fold. An auto stage optical microscope (Olympus MX51) was used so that visible light could be used to distinguish MWNT (black) from the cement matrix (white). The microscope system illuminates the specimen with uniform brightness and transfers the observation image to image processing software, DotSlide. Since the optical focus at each local spot of the fractured specimen changes due to unevenness of the specimen surface, the microscope system captured observation images at every 3 μm along the out of plane direction from the deepest level to the highest level of the fractured surface. By using the image processing software, focused local spots in the captured images were collected and combined to form a single image that is in focus overall. Two images of each specimen were gained through the aforementioned procedure.
3.1.2 Image Processing and Analysis Procedures
Image acquisition by microscope in collaboration with a digital camera
Capture areas that are optically well focused and assemble them so a well-focused image can be completed (conducted by DotSlide)
Convert the image to a black and white image by thresholding
Reverse the black and white image
Convert the black and white image to a binary image
Acquire data (area) of agglomerate regions
Steps (1) to (2) were conducted by the microscope system and the remaining steps were conducted using a MATLAB Image processing tool box. Automatic brightness control was applied in step (1) by the microscope system. The effect of change of brightness level on the image thresholding was considered a minor factor and hence was ignored in the present work. Otsu (1979)’s automatic thresholding method was used in the thresholding process of step (3) (Otsu 1979). The gray-level scale, which is determined between 0 and 1, was used with a 15 % reduction (gray-level scale × 0.85) since the brightness of MWNT was considered high when compared with the original image. After the reversion process (4), bright parts indicated MWNT. Accordingly, the planar occupation area of the bright parts expressed as 1 in the corresponding binary image, was summed. The planar occupation ratio of bright parts can be calculated by dividing the sum total of the bright parts by the total area of the corresponding image. The planar occupation ratio of MWNT was calculated from each of two images and an average value was determined from the ratios.
3.2 DC Conductivity of the MWNT-Embedded Cement Composites
3.2.1 Specimen Preparation for DC Conductivity Measurement
The constituent materials and their weight content ratios of the composites fabricated under different flow in an effort to understand change of the MWNT distribution by examining the DC conductivity of the composites.
Mix proportions (g)
The constituent materials and their mix proportions of the composites fabricated under the high flow condition (flow > 250 mm).
Mix proportions (g)
Wt% by cement
3.2.2 Measurement Method
Li et al. (2007) and Xie et al. (1996) revealed that the CNT distribution in CNT-added composite materials can be assessed by examining the DC conductivity of the materials (Li et al. 2007; Xie et al. 1996). Once SEM or transmission electron microscopy (TEM) reveal that CNTs are homogeneously dispersed in the composite materials, DC conductivity evaluation can be used in an effort to identify the percolation network, which is a large cluster network spanning from one side to the opposite side without disconnection in the composite materials (Stauffer and Aharony 1994).
3.3 Flow of the Composite Mixtures
The flow of fresh mixture of the composites was tested on the basis of ASTM C1437 (ASTM International 2013). In addition, the flow was determined from an average of mixture’s diameter after dropping the flow table.
4.1 MWNT Distribution in Composites Fabricated Under Different Flows
4.1.1 Image Analysis of MWNT Distribution State in the Composites Fabricated Under Different Flows
Through preliminary tests on MWNT-embedded cement composites, it is found that the flow of the fresh mixture may influence the MWNT distribution. Accordingly, MWNT-embedded cement composites fabricated with different W/C values were prepared and the MWNT distribution state of the composites was evaluated. The constituent materials are listed in Table 1. The mixing ratio of MWNT was 0.6 wt% in order to provide a sufficient amount of MWNT. 0.6 wt% of MWNT exceeded the percolation threshold as reported in the literature (Nam et al. 2015). Accordingly, the distribution of MWNT was expected to be pronouncedly visible. The volumetric fractions (vol%) of MWNT were also provided in the table. In determination procedures of volumetric fractions of MWNT, volume of each constituent material had to be calculated by using true specific gravity of the materials shown in the Sect. 2, then volume ratio of MWNT to total volume of the mixture was obtained. 20 % (by cement weight) SF was added in the mixtures under the consideration that SF can improve the MWNT distribution (Nam et al. 2012). The white cement was substituted for OPC and the incorporation of nylon fiber was omitted, as addressed in Sect. 3.1.1. The specimens were prepared and images of fractured surfaces of the specimens were obtained according to the method described in Sect. 3.1.2.
In an effort to express the change of the MWNT distribution states in a quantitative manner, the proportion of MWNT agglomerates, indicated by white color, to the total area of the image, was calculated by the MATLAB image processing tool box. This proportion is designated as a q value. The q value refers to the planar occupation ratio of MWNT on a fractured surface of the composite.
The planar occupation ratio of MWNT, q, was increased twofold with decrease of W/C ratio from 42 to 26 % as shown in the image analysis result of Fig. 4. However, electrical conductivity of the composites is expected to increase more than hundreds of times as the W/C ratio decreases. This stems from that disconnected CNTs can be electrically connected attributable to the enhancement of MWNT distribution. Accordingly, it can be said that the twofold greater q value can lead to a dramatic increase in the electrical conductivity. This will be dealt in the electrical property characterization section.
4.1.2 DC Conductivity of the Composites Fabricated Under Different Flows
The image analysis of the MWNT distribution state of the MWNT-embedded cement composites fabricated under different flows (or W/C) studied in Sect. 4.1.1 showed that the MWNT distribution improved as the flow of the composite decreased. In the present section, the DC conductivity of the composites was examined in an effort to understand the change of the MWNT distribution in the composites and also to verify whether it supported the image analysis results. The constituent materials and respective weight content ratios of the composites are given in Table 3. To make specimens with different flows, one group of specimens was fabricated by varying the water content, as described in Sect. 4.1.1, and an additional group of specimens was fabricated by varying the SP content in the present section. The fabrication procedures of the specimens followed descriptions in Sect. 3.2.1 and the measurement method was described in Sect. 3.2.2.
It is worth noting that the electrical conductivity of the M06–W30 was greater than that of the M06–SP04 although the flow of the M06–W30 was higher than that of the M06–SP04. This indicates that control of water content can be a more effective way of enhancing the electrical conductivity of the composites.
Therefore, two categories of specimens were prepared in the subsequent experiments. One category included MWNT-embedded cement composites fabricated under a high flow condition (flow > 250 mm) and another category included composites fabricated under a low flow condition (114 mm < flow < 126 mm) by adjusting the W/C ratio and the SP/C ratio. To understand the MWNT distribution states, the image analysis and DC conductivity measurement for the specimen groups were carried out.
4.2 Influence of the Flow on MWNT Distribution in the Composites Incorporating Various MWNT Contents
4.2.1 Image Analysis of the MWNT Distribution State in the Composites
It is generally agreed that an increase in the MWNT content is accompanied with an increase in the total area of MWNT if it is uniformly distributed throughout composites. Such phenomena was in close agreement with the test result provided in Fig. 7 where the total area of MWNT was observed to increase with the MWNT content. In addition, the MWNT clumps were not found even when the MWNT content was increased up to 1.5 %. Observation of the images thus indicated that MWNT was satisfactorily distributed throughout the composites in the LF–M group.
An image analysis of the MWNT distribution state in the composites fabricated under the high flow condition was not carried out because it was not possible to present reliable q values due to the presence of the MWNT clumps, as shown in the W42–M06 specimen of the Fig. 3.
4.2.2 DC Conductivity of the Composites Incorporating Various MWNT Contents
The electrical percolation phenomenon of the LF–M group was found in the Fig. 9. The percolation threshold, which refers to the critical volume fraction of MWNT inducing remarkable change in the conductive phase, existed in a MWNT content range of 0–0.3 wt% for the LF–M group. Accordingly, the percolation threshold corresponded to 0.196 vol% if it is determined as the mean value of the percolation threshold range.
The percolation phenomena manifested in the MWNT-embedded cement composites fabricated under the low flow condition indicated that MWNT was well distributed throughout the composites and the MWNT distribution was consistent in the specimen group. The results supported the image analysis results obtained in Sect. 4.2.1. Based on the image analysis results and the electrical percolation phenomena, an acceptable MWNT distribution was attained by reducing the flow of the composites. Consequently, it can be concluded that maintaining the low flow of fresh mixtures of the composites is crucial to improve the MWNT distribution.
The change of the DC conductivity of the composites fabricated under the high flow condition with various MWNT contents was also investigated. The constituent materials and respective weight content ratios of the composites are given in Table 4 (Nam et al. 2012). MWNT was incorporated in each composite type at 0, 0.3, 0.6, and 1.0 wt% by weight of cement. To fabricate specimens with high flow, the W/C ratio was fixed to 0.4 in the composites and the SP/C ratio was 0.016.
The MWNT distribution, which was evaluated by the planar occupation ratio of MWNT, q, was enhanced as the flow of fresh composite mixtures decreased.
The DC conductivity of MWNT-embedded cement composites fabricated with different flows was examined and it was observed that the conductivity increased as the flow was decreased.
The image analysis of the MWNT-embedded cement composites fabricated under the low flow condition (114 mm < flow < 126 mm) revealed that the q value linearly increased as the MWNT content increased. The linear relationship between the q value and the MWNT content demonstrated that fabrication of the composites under the low flow condition is an effective way to enhance the MWNT distribution.
The DC conductivity of the MWNT-embedded cement composites fabricated under the low flow condition showed percolation phenomena, thus indicating that MWNT was well distributed in the composites, as evaluated in the image analysis.
The proposed image analysis procedures for evaluation of the MWNT distribution can be used as an evaluation method to quantify the distribution of carbon nano-materials in the cement matrix. The conductive MWNT-embedded cement composites with percolative networks produced by controlling the flow are expected to be utilized as piezoresistive sensors, EMI shielding materials, electrostatic discharge materials, heating elements, etc. Future work will be focused on in-depth study of the origin of the flow effect on the MWNT distribution.
This research was supported by the KUSTAR-KAIST Institute, KAIST, Korea and also sponsored by a research project ‘Development of fabrication method for floor heating material by use of CNT-cement composites with self-heating capacity of 5W-50 °C’ (Project code: 15CTAP-C098086-01) funded by Ministry of Land, Infrastructure and Transport (MOLIT) of Korea Government and Korea Agency for Infrastructure Technology Advancement (KAIA). Authors also deeply thank Prof. Hyeong-Ki Kim in Chosun University and Prof. Sung-Min Choi in KAIST for their important comments on this research and acknowledge June Lee in National NanoFab Center for cooperation in the image analysis.
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