To improve locally supplied water, many homes and businesses utilize a water pretreatment system at the junction where water is supplied into the facility. One common pre-treatment system in areas with hard water is a water softening system. Water softening systems utilize ion exchange resin beds to remove hardness ions from water, including calcium and magnesium, by removing them from the flowing water and replacing them with sodium. This process occurs as water flows through beds comprised of small polystyrene beads crosslinked at different percentages with divinylbenzene1.
We utilized the SkyScan 1272 desktop micro-CT to analyze a sampling of ion exchange resin removed from a home water softener system with the goal of characterizing the particle size distribution. X-ray micro tomography is a powerful tool for particle size analysis, and when combined with 3D image analysis of individual particles this is a very versatile method to obtain quantitative information about the size, shape, and arrangement of particles. Critical to this analysis is the ability to separate touching particles so that they can be identified and measured.
X-Ray Microscopic Imaging of Ion Exchange Resin Particles
Loose resin beads removed from a malfunctioning water softening system were collected and transferred to a small cylindrical tube for imaging. We examined the beads using our high-resolution SkyScan 1272 micro-CT at an isotropic voxel size of 2 µm. The SkyScan 1272 is a fine match for this project due to its high resolution and quick sample collection for organic materials such as the polystyrene beads used in water softening applications.
Figure 2: Planar 2D slices through the sample of ion exchange resin
As shown in Figure 2, DataViewer allows us to interactively view the overall shape and distribution of particles in our imaged sample volume- with visualization planes. As we click any individual particle in the dataset, the other two views respectively change to center upon the clicked location. From this view, we see a variety of particle sizes and, more importantly, we observe that the particles are in direct contact with one another. Considering how to separate particles from one another prior to analysis will be key to extracting a more accurate representation of particle size.
In general, the grayscale is consistent throughout the spheres, which matches our expectations since the spheres should be homogeneous mixtures of polystyrene and divinylbenzene. Both molecules are organic in nature and would be difficult to distinguish from one another within micro-CT images since both have similar interactions with the X-ray beam.
When moving our dataset into CTAnalyzer for particle size analysis, we notice spheres in close contact with one another are connected in 2D space and would be considered as one aggregate particle versus individual spheres as shown in Figure 3. Following the guidelines in Bruker Method Note 75, we utilized the watershed separation algorithm to analyze the location of each white pixel in the segmented dataset and attempt to automatically determine most likely locations for boundary lines between each particle. The successful selection of watershed separation parameters will split neighboring particles from one another while attempting to avoid over-splitting the data into bead fragments.
CTVox allows us to visualize the quantitative structural data as shown in Figure 4. Each size container calculated in the analysis can be assigned a color value in our rendered image, allowing us to highlight the locally calculated size of particles within our dataset. Since the particles in the study were not screened or sorted in any way, the random distribution of sizes throughout our sample volume is logical.
As shown in Figure 5, a normal distribution focuses upon our average particle diameter. At both extreme ends of our distribution, we see what are likely to be outliers. In this case, a portion of the lower diameters calculated could likely arise from broken or damaged beads within the sample that would not calculate to a single spherical diameter. Similarly, the larger bead diameters calculated on the upper end distribution could result from particles unsuccessfully split via the watershed algorithm.
| Sample | Resin Beads |
| Average Diameter | 356.01 ± 91.90 µm |
| Surface Area/Volume | 18.74 mm-1 |
| Total Particles | 875 |
Table 1: Extracted quantitative size data for the ion exchange resin beads
Table 1 documents the extracted quantitative data for the beads examined in this sampled volume.
From our reconstructed datasets and CTAn output files, we were able to import different versions of our dataset into Simpleware ScanIP software with the CAD add-on module to segment into volumetric models. Maverick Render Indie then allowed us to apply colors and textures to the models as shown in Figures 1 and 6.
Conclusion
Among the SkyScan product line, the SkyScan 1272 is a workhorse high resolution instrument which excels with imaging and analysis of organic samples. The small footprint and full self-shielding make the SkyScan 1272 a great fit for most laboratories.
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Scan Specifications
| Sample | Extracted Resin Beads |
| Voltage (kV) | 60 |
| Current (µA) | 100 |
| Filter | 0.25 aluminum |
| Voxel Size (nm) | 2 |
| Rotation Step | 0.2 |
| Exposure Time (ms) | 1600 |
| Rotation Extent (deg.) | 360 |
| Scan Time (HH:MM:SS) | 05:56:38 |
These scans were completed on our SkyScan 1272 micro-CT system at the Micro Photonics Imaging Laboratory in Allentown, PA. Reconstructions were completed using NRecon 2.0 while visualization and volumetric inspection of the 2D and 3D results were completed using DataViewer and CTVox. The ion exchange beads and plastic tubing were converted to STL volumetric models using Synopsys’ Simpleware ScanIP software with the CAD add-on module (Synopsys, Inc., Mountain View, USA) before 3D rendering using Maverick Render Indie (Random Control, Madrid, Spain).
Would you like your work to be featured in our monthly newsletter? If so, please contact us by calling Seth Hogg at 610-366-7103 or emailing seth.hogg@microphotonics.com.
References
*Simpleware software (Synopsys, Inc., Mountain View, USA) enables you to comprehensively process 3D image data (MRI, CT, micro-CT, FIB-SEM…) and export models suitable for CAD, CAE and 3D printing. Use Simpleware software’s capabilities to visualize, analyze, and quantify your data, and to export models for design and simulation workflows. Simpleware™ is a trademark of Synopsys, Inc. in the U.S. and/or other countries.