3.7 Image Tool 3.0 as Particle Size Distribution Analysis Software
For this research, the ion beam induced secondary electron images and BSE images of grades 91 and 92 steel samples were analysed using an image analysis software programme; Image Tool 3.0. The FIB and BSE images were first edited using Photoshop software, and transferred into grey-scale digital images consisting of an area of 1024 x 768 pixels. Using this Image Tool 3.0 software, several measurement options are available, such as feret diameter, length, width, area, perimeter and aspect ratio and so on. However, the feret diameter was used as the main factor to quantify the particle size distribution of the M23C6 particles. FIB and BSE images are ideal for automatic image analysis as the contrast between the particles and the matrix is achieved by conductivity contrast and chemical composition contrast, respectively. When using Image Tool 3.0 to analyse the particle size data of M23C6
particles and Laves phase, several factors which may affect particle size analysis results from FIB and BSE images are first considered and discussed.
Particle size distributions may be affected by “overlapping” particles, in which case two or more close particles may count as one when measured using the Image Tool 3.0 software. In general, the “overlapping” particles may decrease the interphase surface area per unit volume and the number density of the particles present in material microstructure, and at the same time increase the mean particle size in the microstructure [3]. Normally, these “overlapping” particles in the system had a very limited effect on the particle size distribution because of the small population; no more than 5 “overlapped” particles were observed in a FIB or BSE image. What is more, these “overlapped” particles typically occurred as a result of nucleation of particles on pre-existing particles, and thus they need not to be measured individually since the effective “obstacle” area should be considered as the sum of independent particles.
In FIB or BSE images, defects may also produce contrast, and if these defects were counted as particles when measurements are taking place, the particle size data may be affected. Normally, the defects like voids produce contrast, but exist as dark particles with bright edges which can be easily separated from the M23C6 particles which appeared as purely dark particles in FIB images or Laves phase which appeared as white particles in BSE images.
Figure 3.4 shows the image analysis procedure of a FIB image of M23C6 particles using Image Tool 3.0. Firstly, the FIB image was transferred into a grey-scale digital image consisting of an area of 1024 by 768 pixels using Photoshop software, shown as Figure 3.4 (a). A similar procedure is applied to the BSE images, the only difference is the Laves phase appeared as white particles and matrix appeared as a black area. This grey-scale digital image was then threshold according to the contrast between the matrix and particles, and changed into a white and black image, in which white parts are matrix phase and black parts are M23C6 particles, shown as Figure 3.4 (b).The size analysis was then taken on this threshold image, shown as Figure 3.4 (c) in which the different colours represent different size categories.
When using the grey-scale digital images to analyse the particle size distribution of M23C6 particles or Laves phase, the accuracy is greatly dependent on the number of pixels that can be assigned to any given particle, which means the greater the
number of pixels that can be assigned to any given particle the more accurate the measurement is going to be. For this research, the smallest detectable particle size was set as 5 pixels, which means that any particles present in the image smaller than 70 nm in diameter would remain as unmeasured. The reason for excluding the particles below 70 nm are because these particles are difficult to separate from dirty or other secondary particles such as MX particles and the absence of these particles in data analysis have a very limited effect on the particle size distribution of M23C6
particles or Laves phase.
(a) (b)
(c)
Figure 3.4: a) FIB image of M23C6 particles in T91-AR-1 Gauge sample, b) the same image after threshold process and c) after size analysis. The different colours represent different size categories.
To improve the accuracy of the particle size distribution of the M23C6 particles and Laves phase particles in 91 and 92 steels, 5 FIB or BSE images in the scale of 25 x 22 µm2 were analysed together to work out the mean particle size and number density of M23C6 particles or Laves phase particles in the same investigated area, 2750 µm2. The mean particle size of M23C6 particles or Laves phase particles of individual images were investigated and compared with the mean particle size of all of the images, for the T92-AR-2 sample for example, as shown in Table 3.4.
Table 3.4: The mean particle size of M23C6 particles or Laves phase particles of individual images compared with total images and standard deviation of T92-AR-2 sample (Each image consists of more than 200 M23C6 particles or 100 Laves phase particles).
Secondary
For all the samples, the standard deviation in mean particle size of M23C6 particles is in the range < 5 nm and that in the mean particle size of Laves phase particles ranged up to 25 nm. This standard deviation value calculated from individual images indicated the homogeneous nature of the particle size distribution of M23C6 or Laves phase particles in the 91 and 92 samples, the smaller value of standard deviation means that there is a more uniform particle size distribution. These standard deviation values were thus included into the investigation of the particle coarsening in M23C6 or Laves phase particles with different heat treatment or stress conditions, which proved very reliable because the change in the particle size was larger than the standard deviation values.