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Classification of highly monodisperse nanoparticles of NIST-traceable sizes by TDMA and control of deposition spot size on a surface by electrophoresis

Authors
Yook, Se-JinFissan, HeinzEngelke, ThomasAsbach, Christofvan der Zwaag, TillKim, Jung HyeunWang, JingPui, David Y. H.
Issue Date
Jun-2008
Publisher
Pergamon Press Ltd.
Keywords
TDMA; monodisperse particle generation; reduction of multiply charged particles; particle deposition by electrophoresis; NIST-traceable particle size
Citation
Journal of Aerosol Science, v.39, no.6, pp 537 - 548
Pages
12
Indexed
SCIE
SCOPUS
Journal Title
Journal of Aerosol Science
Volume
39
Number
6
Start Page
537
End Page
548
URI
https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/178567
DOI
10.1016/j.jaerosci.2008.03.001
ISSN
0021-8502
1879-1964
Abstract
It is required to characterize surface inspection tools using particles of known material and size, with controllable deposition spot size for adjusting deposited-particle number density on a mask or a wafer surface. Not all the materials commonly seen in semiconductor manufacturing are available in the form of monodisperse particles. Thus for some materials, it is inevitable to use polydisperse particles for characterizing the surface inspection tools. The differential mobility analyzer (DMA) is widely used to generate monodisperse aerosol. The DMA, however, can classify unwanted larger particles of multiple charges along with singly charged particles of a target size, due to the same electrical mobility. The present study proposed a Tandem-DMA (TDMA) system comprising two DMAs and two radioactive sources to reduce the fraction of multiply charged particles. Using this TDMA system, SiO2 nanoparticles with approximately 98% size-uniformity were fractionated from a broad size distribution. All DMAs utilized in this study were calibrated using Standard Reference Materials (SRM 1963) issued by the National Institute of standards and Technology (NIST), in order to produce particles with NIST-traceable sizes. An analytic equation was derived to predict the deposition spot size on a surface in case of the electrostatic particle sampling, and agreed well with experimental and numerical data.
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