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User Benefits Application News Fig. 3 The iSpect DIA-10 Dynamic Particle Image Analysis System Frame Rate: 8 fps Efficiency: 96.5 % Luminance: 249 Threshold of Binary Image: 90 % Pump Volume: 250 μL Background Correction: Enable Fig. 1 Sample Appearance Sample A commercially available polishing-grade colloidal silica slurry was used as the sample, with a solids concentration of approximately 30 wt% and water as the dispersion medium. Laser diffraction analysis using the SALD-7500nano nanoparticle size distribution analyzer showed a monodisperse particle size distribution with a median diameter of 88 nm. The dilution factor during measurement was 1000-fold. Since the particles used in precision polishing are typically tens to hundreds of nanometers in size, the laser diffraction/scattering results indicated a particle size distribution suitable for precision polishing. Table 1 DIA Measurement Conditions Methods and Results The DIA measurement conditions are shown in Table 1, and the results are shown in Figs. 4 and 5. Measurements were performed using the undiluted sample. The number concentration of micron-scale particles was 3315 particles/mL, and the largest detected particle had an area-equivalent diameter of approximately 73 µm. The volume concentration, calculated by determining the sphere-equivalent particle volume from the area-equivalent diameter for each particle and summing the volumes of all particles, was 2.337 ppm. Since laser diffraction/scattering measurements are typically performed at concentrations of several hundred ppm, and the sample was measured after a 1000-fold dilution, it is clear that detecting micron-scale foreign matter in this sample by laser diffraction/scattering would be difficult. However, conventional laser diffraction/scattering methods generally require sample concentrations on the order of several hundred ppm, and because the concentration must be adjusted to the main component, it can be difficult to detect trace microscopic foreign matter. Therefore, to detect and evaluate trace foreign matter, measurements were performed by dynamic image analysis (DIA) using the iSpect DIA-10. DIA captures images of a microcell channel in which particles flow, extracts each particle image from the channel images, and evaluates particle shape and concentration. In addition, by using the microcell method, the iSpect DIA-10 achieves highly reliable foreign matter detection and accurate concentration evaluation. Furthermore, when evaluating micron-scale foreign matter in samples containing relatively high concentrations of submicron particles, measurement can be performed without dilution or at a low dilution factor. (Related application: Application News No. Q124) Introduction Foreign matter in CMP* slurry used for precision polishing of semiconductor wafers may cause defects. Therefore, abrasive particles and foreign matter must be carefully controlled. In studies of filter-based foreign matter removal and process control, it is important to detect and evaluate even trace levels of foreign matter. However, laser diffraction and dynamic light scattering, which are commonly used for particle size distribution analysis, may require adjustment of the sample concentration to match the main component, making it difficult to detect trace amounts of microscopic foreign matter. In this study, colloidal silica used in CMP slurry was analyzed using the iSpect DIA-10 dynamic particle image analysis system to evaluate trace amounts of microscopic foreign matter. Machine learning-based clustering was then applied to assess the detected foreign particles. * Chemical Mechanical Planarization/Polishing Foreign matter in the micron range can be detected and evaluated at near-undiluted concentration using the microcell method. Telecentric optical system minimizes missed microscopic foreign matter (imaging efficiency: 90 % or higher). Particle images and morphological information obtained by dynamic image analysis can be used for particle classification, which enables a more detailed evaluation of microscopic foreign matter in CMP slurry. Evaluation of Microscopic Foreign Matter in CMP Slurry Using Dynamic Image Analysis and Machine Learning Hiroki Maeda Dynamic Particle Image Analysis System Laser Diffraction Particle Size Analyzer Fig. 2 Particle Size Distribution Obtained by Laser Diffraction (Dilution: 1000-fold; measured with the SALD-7500nano Nanoparticle Size Distribution Analyzer)
Application News www.shimadzu.com/an/ Shimadzu Corporation © Shimadzu Corporation, 2026 For Research Use Only. Not for use in diagnostic procedures. This publication may contain references to products that are not available in your country. Please contact us to check the availability of these products in your country. The content of this publication shall not be reproduced, altered or sold for any commercial purpose without the written approval of Shimadzu. See https://www.shimadzu.com/about/trademarks/index.html for details. Third party trademarks and trade names may be used in this publication to refer to either the entities or their products/services, whether or not they are used with trademark symbol “TM” or “”. Shimadzu disclaims any proprietary interest in trademarks and trade names other than its own. The information contained herein is provided to you "as is" without warranty of any kind including without limitation warranties as to its accuracy or completeness. Shimadzu does not assume any responsibility or liability for any damage, whether direct or indirect, relating to the use of this publication. This publication is based upon the information available to Shimadzu on or before the date of publication, and subject to change without notice. First Edition: Jun. 2026 01-00942-EN Fig. 7 Grouping Results for Particles Larger than 10 µm SALD and iSpect are trademarks of Shimadzu Corporation or its affiliated companies in Japan and/or other countries. Particle images obtained by DIA are shown in Fig. 4, while the corresponding particle size distributions are shown in Figs. 5 and 6. Even with DIA, only a very small number of foreign and coarse particles were detected at a 1000-fold dilution factor. This indicates that evaluation under undiluted conditions is preferable when assessing trace foreign matter. Conclusion To evaluate trace foreign matter and coarse particles contained in polishing-grade colloidal silica used as CMP slurry, DIA measurements were performed. Images and concentrations of micron-scale particles that could not be detected by laser diffraction were successfully measured. In addition, the microcell method enabled measurement to be performed without dilution. On the other hand, even with DIA, only a small number of particles were detected at a 1000-fold dilution factor, demonstrating the effectiveness of evaluating trace foreign matter in the undiluted sample. Furthermore, machine-learning- based clustering enabled quantitative evaluation of the particle types present. Thus, DIA is an effective analytical technique for evaluating trace foreign matter and coarse particles in CMP slurry. References 1) Syuhei Kurokawa: The Overview and Future Prospects for Planarization CMP Technology, Journal of the Japan Society for Precision Engineering, Vol. 84, No. 3, pp. 213–216 (2018) Related Applications 1. Evaluation of Concentration of Coarse Particles in High Concentration Silica Nanoparticle Slurry: Foreign Object Detection by Dynamic Image Analysis Method, Application News No. Q124 Particle type is important for identifying particle origin, developing reduction measures, and evaluating impact, and particle images provide useful clues for such identification. In addition to shape information, brightness contains information related to thickness in the observation direction, the relative refractive index between the particle and the dispersion medium, and surface roughness. To understand what particle types were present, particles larger than 10 µm, which accounted for more than 90 % of the total volume, were classified into six particle populations based on the results of clustering obtained by machine learning, using dimensionality reduction by UMAP and clustering by HDBSCAN (Fig. 7 and Table 2). To remove particle groups a, b, and d, which have small aspect ratios and are elongated, it is important to select a filter pore size that takes the minor axis into account. In addition, groups a and d, which have higher average brightness than particle groups of similar size, may be flake-like particles that are thin in the observation direction. In this way, more advanced foreign- matter control is possible by using the obtained particle images and shape information. Fig. 4 Particle Images Obtained by DIA (Undiluted Sample) Fig. 5 Particle Size Distribution Obtained by DIA (Undiluted Sample) Fig. 6 Particle Size Distribution Obtained by DIA (Dilution: 1000-fold) Table 2 Morphological Information for Each Particle Group [ABD]: Area Based Diameter [Circ.]: Circularity [AR]: Aspect Ratio [Br. Avg]: Average Brightness Volume Count ABD Circ. AR Br. Avg a 54.7 % 8.8 % 35.909 0.505 0.485 144 b 26.1 % 4.4 % 43.310 0.681 0.536 82 c 9.0 % 17.6 % 18.903 0.753 0.611 127 d 3.8 % 22.1 % 12.974 0.576 0.524 155 e 2.8 % 22.1 % 11.992 0.970 0.754 131 f 3.5 % 25.0 % 12.230 0.858 0.610 144 Cluster Particle Amount Morphology Parameter (Average)
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