A method to deposit a known number of polystyrene latex particles on a flat surface. Issue 12 (2nd December 2019)

• Record Type: Journal Article
• Authors: Tajima, Naoko; Iida, Kenjiro; Ehara, Kensei; Khumpuang, Sommawan; Hara, Shiro; Sakurai, Hiromu
• Is Part Of: Aerosol science and technology. Volume 53:Issue 12(2019)
• Page Start: 1353
• Page End: 1366
• Publication Date: 2019-12-02
• Subjects: Pramod Kulkarni; Aerosols -- Periodicals; Aerosol Propellants -- Periodicals; Aerosols -- Periodicals; 660.294515
• DOI: 10.1080/02786826.2019.1666969
• Languages: English
• ISSNs: 0278-6826

Abstract

Abstract: This study introduces a method to deposit polystyrene latex (PSL) particles on a silicon wafer in a manner that allows their number to be predicted with a high degree of accuracy. A laminar flow growth tube is used to condense supersaturated water vapor on seed aerosol particles that are water-insoluble. After condensation is complete the droplets are accelerated through a nozzle to form an aerosol jet, and the number of droplets in this jet is counted optically. The droplets are then deposited on a flat surface by inertial impaction. The particle number on the surface is predicted by multiplying the droplet number by an experimentally evaluated conversion coefficient of 0.991 ± 0.011 ( k = 2). Uncertainty analysis showed with a 95% confidence interval that the particle number on a flat surface is ± 2.0%. The primary application of this method is to make a particle number standard (PNS) wafer whose intended use is to evaluate the counting efficiencies of wafer surface scanners, and this study demonstrates the fabrication of such PNS wafers. A motorized XY-stage moves the surface horizontally to deposit PSL particles along desired paths over a half-inch wafer. The particle number was varied over seven levels ranging from 10 to 10, 000. The particle diameter was varied at four levels: 0.814, 0.18, 0.102, and 0.046 µm. In all PNS wafers, the number of deposited particles was counted using optical microscopes. The observed particle numbers were all within the 95% confidence interval of the predicted value. Copyright © 2019 American Association for Aerosol Research