Evaluation of Microscopic Foreign Matter in CMP Slurry Using Dynamic Image Analysis and Machine Learning

User Benefits

- 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.

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.

June 29, 2026 GMT