Determination of Aggregate Surface Morphology at the Interfacial Transition Zone (ITZ)

1. Preparation of the model concrete with a single ceramic particle

1. Mold preparation
   1. Use a brush to clean the mold (25 mm x 25 mm x 25 mm) and ensure that the inner surfaces of the mold are impurity-free.
   2. Use another brush to uniformly apply diesel oil on the inner surfaces of the mold for easier mold-release.
      NOTE: Here, we did not use the common mold for mortar or concrete preparation. As the ceramic particle is around 15 mm in diameter, a cubic plastic mold around 30 mm in length is used for sample preparation. Ensure that the size of plastic mold is larger than the ceramic particle.
2. Molding the model concrete
   1. Weigh 1,000 g of cement and 350 g of water with an electronic balance (the designed water to cement mass ratio is 0.35).
   2. Wipe the 5 L mixing pot with a wet towel to moisten it. Add 350 g of water and 1,000 g of cement into the mixing pot sequentially. Place the mixing pot on the mixer and raise it to the stirring position.
   3. Mix at 65 rpm for 90 s, and let the mixture stand still for 30 s. During this period, scrape off the paste on the inner wall of the pot. Then, mix at 130 rpm for another 60 s.
   4. Remove the pot from the mixer and put the ceramic particle into the paste, manually mixing it with the cement paste thoroughly.
   5. Half fill the mold with well mixed fresh cement paste.
   6. Place the ceramic particle on the top surface of the cement paste and fill the rest of the mold with cement paste. Wipe off excess cement paste with a scraper knife and vibrate the mold on a vibrating table for 1 min at 50 ± 3 Hz.
   7. Seal the mold surface with cling film to prevent moisture evaporation.
3. Curing
   1. Cure the specimen in a curing room for 24 h (20 ± 1 °C and 95% ± 5% relative humidity).
   2. Remove the specimen from the mold and further cure the specimen for 28 d under the same environmental conditions.

2. Scanning electron microscopy preparation

1. Determination of the ceramic particle inside the matrix
   1. Scan the specimen with X-ray computed tomography to obtain a stack of slices³¹.
   2. Roughly choose the slice where the ceramic particle appears to be largest. Fit the boundary of the ceramic particle with a circle and determine the center of the circle as the geometrical center of the ceramic particle. Due to the gray value difference between cement matrix and ceramic particle, a rough boundary of the particle appears on each CT slice (Figure 1).
2. Cutting
   1. Cut the cubic specimen into two parts through the geometrical center of the ceramic particle in a cutting machine. Figure 1³² is a schematic map showing the cutting direction.
      NOTE: The ceramic particle was split into two equal parts, while the specimen was not cut into two exactly equal halves. If the ceramic particle is in the exact center of the cubic specimen, the specimen will be split into two equal halves. However, in a real situation, the ceramic particle typically is not in the exact center of the specimen.
3. Hydration termination
   1. Immerse the two parts into isopropyl alcohol (≥99.5%) for 3 days at room temperature to remove the unbounded water and terminate the internal hydration process. Replace the isopropyl alcohol solution every 24 h.
   2. Place the two parts in the vacuum drying even for 7 days to dry the sample at temperature of 40 °C.
4. Solidifying the microstructure
   1. Use a finger to smear the inner surface of two cylindrical plastic molds (31 mm in diameter and 25 mm in height) with demolding paste. The molds are all bottom removable.
   2. Place each piece of the sample into each mold with the surface to be examined facing downward.
   3. In a paper cup, weigh 50 g of low viscosity epoxy resin and add another 5 g of hardener. Manually stir the mixture with a wooden stick for 2 min.
   4. Put the mold into the cold mounting machine along with the paper cup with the mixture.
   5. Start the vacuum on the cold mounting machine and pour the epoxy resin into the mold until it merges with each sample.
   6. Keep the mold in the cold mounting machine for 24 h until the epoxy resin hardens.
   7. Remove the bottom of each mold and squeeze out the sample. Store the sample in a vacuum drying oven.
5. Grinding and polishing
   1. Grind the sample with SiC paper and alcohol as a lubricant on an automatic polishing machine at the speed of 300 rpm in the following sequence for 3 min each: 180 grit, 300 grit, 600 grit, and 1200 grit.
   2. Attach the flannelette to the turntable of the automated polishing machine.
   3. Polish the sample on the flannelette with diamond paste of 3 μm, 1 μm, and 0.25 μm for 15 min at the speed of 150 rpm, each.
   4. Remove the debris in an ultrasonic cleaner with alcohol as the cleaning solvent after each grinding and polishing step.
   5. Store each sample in a plastic box of similar size to the sample with each surface to be examined facing up to avoid cause any scratches on the testing surface.
   6. Keep the boxes containing the samples in a vacuum dry oven³².
      NOTE: The grinding and polishing process could be completed on an automated polishing machine and at most 6 samples could be polished at the same time. The grinding and polishing time should be carefully chosen to obtain an extremely smooth surface for the SEM without creating height differences between the cement paste and the aggregate. A typical sample is shown in Figure 2³².

3. Backscattered image acquisition and processing

1. Acquisition
   1. Spray a thin layer of gold foil on the surface to be examined in a vacuum environment with an automatic sputter coater.
   2. Place a strip of adhesive tape on the side of the sample to connect the testing surface and opposite surface and place the sample on the test bench with the testing surface facing upward.
   3. Move the sample to focus the lens on region 1 as labelled in Figure 2³².
   4. Vacuum the SEM and change to backscattered electron mode. Set the magnification at 1,000x and carefully adjust the brightness and contrast before capturing images.
   5. Move the lens along the direction of the aggregate boundary to another position of the aggregate and take another image. Repeat this moving and imaging process at least 15 times so that enough images can be obtained for statistical analysis.
   6. Move the lens to region 2 and region 3 and repeat the imaging process.
      NOTE: Each image should include three phases: the matrix, the aggregate, and the ITZ. Since ITZ is a narrow section existing between another two phases and hard to be distinguished, each image should include both the cement matrix and the aggregate.
2. Processing
   1. Pre-treat the image with a best fit and 3 x 3 median filter three times to reduce the noise and enhance the boundary of different phases on ImageJ.
   2. Manually capture the boundary of the ceramic particle and cut off this part from the original image using ImageJ.
   3. Roughly determine the upper threshold value of pore phases by setting different threshold values and segmenting the image to compare with the original one.
   4. Obtain the gray-scale distribution of the remaining part of the image. Choose two approximatively linear parts of the distribution curve just around the roughly determined upper threshold value of pore phases. Fit these two parts with linear curve and the intersection point will be set as the exact upper threshold value of this image (see Figure 3c³²).
   5. Use this value to do the segmentation and compare the binary image with original gray-scale image for final threshold value determination.
   6. Convert the gray-scale image to a binary image with white (gray value = 255) representing pore phase and black (gray value = 0) representing solid phases.
      NOTE: The exact determination of threshold value is called the overflow point method³³ since the brightness and contrast are kept the same for different images obtained from same sample. Once the upper threshold value is precisely determined, this value could be applied to other images obtained from the same sample.

4. Data processing

1. ITZ thickness determination
   1. Delineate twenty 20 successive strips that are 5 μm in width (use the included strip_delineation.m file), along the captured boundary in the direction of starting from aggregate surface and going into the bulk paste (see Figure 3d³²).
   2. Count the number of pixels with a gray value lower than the threshold in each strip and normalize the values by the number of total voxels contained in each strip. Each normalized value will be viewed as the porosity of each strip.
   3. Repeat the counting and normalization process for all the images. Average the porosity profiles of the same strip number from different images.
   4. Draw the porosity distribution graph as a function of distance away from aggregate surface. Determine the inflection point on the curve where porosity become stable as the thickness of the ITZ.
      NOTE: The number of strips and width of each strip could vary; make sure that the total width of the delineated strips includes all of the ITZ. According to previous research, the ITZ thickness ranges between 20-50 μm¹³. Even in some model concrete samples with an enlarged ITZ, this value does not exceed 70 μm^34,35.
2. Aggregate surface roughness (SR) characterization
   1. Save the manually captured boundary as a curve. Fit the irregular boundary with both straight line and circle arc according to the Eq. (1) and Eq. (2) based on least square algorithm.
      (1)
      (2)
      with (a,b) being the center of the fitting circle.
   2. Define the deviations between original irregular boundary and fitting smooth curve as the surface roughness (SR).
   3. For straight line, calculate the SR_s by averaging the absolute value of the perpendicular distance of the center of each pixel on the boundary to the fitting line:
      (3)
      with n being the number of pixels included in each boundary and (x_i, y_i) being the coordinates of the ith pixel on the boundary.
   4. For a circle arc, define SR_C as:
      (4)
   5. Compare the value of SR_S and SR_C for each boundary and determine the minimum value as the final surface roughness for this curve (use the included surface_roughness_calculation.m file).
      NOTE: The surface roughness of boundary should be defined against a smooth baseline curve. Both straight line and circle line were used for the following reason. Though the boundary of the spherical ceramic particle appears like a circle in 2D, some local regions appear to be more appeal to a straight line.
3. K-means clustering
   1. Define a slope index (SL) to describe the porosity gradient within the interfacial transition zone according to the Eq. (5).
      (5)
      where φ_max is the value of the porosity in the first strip (0 μm to 5 μm) and φ_min is the value of the porosity in the sixth strip (25 μm to 30 μm).
   2. Combine the SR and SL of each boundary to be an observation. And for total n boundaries and ITZs, there exist n observations to be saved as a cluster {(SR₁,SL₁),(SR₂,SL₂), … , (SR_n,SL_n)}.
   3. Apply a K-means clustering^36,37 algorithm (use the included k_means_clustering.m file) to all the observations and subdivide them into 2 clusters: rough and smooth aggregate surface group, respectively.
   4. Average the porosity distributions of ITZ in rough and smooth cluster, respectively. Compare the average porosity distribution between two clusters.
      NOTE: Herein, K-means clustering is a method of vector quantization, which is originally used in signal processing and currently widely applied to cluster analysis in data mining. The aim of the method is to subdivide the observations into 2 or more subgroups.