Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group
  • Applied Spectroscopy
  • Vol. 51,
  • Issue 10,
  • pp. 1460-1463
  • (1997)

Characterization of Surface Contaminants by a Silver Film-Enhanced IR-Johnson Method

Not Accessible

Your library or personal account may give you access

Abstract

Characterization of nanometer-order organic contaminants on polymer film and silicon wafer surface has been investigated by a modified IR-Johnson method. We have proposed a silver film-enhanced IR-Johnson method that is useful for surface contaminant analysis. In the present method, organic traces are transferred from the surface of a polymer film or silicon wafer onto the KBr particles deposited with silver film, and then the KBr particles are analyzed directly by diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS). Infrared absorption of organic traces was enhanced by the presence of silver island film. With this method, a spectrum of nanometer-order organic traces can be obtained without any interference from the polymer film substrate. The present method is as surface-sensitive as X-ray photoelectron spectroscopy (XPS) and provides a large amount of information on the chemical structure of surface contaminants. This is a promising method for the surface characterization of polymer films and silicon wafer.

PDF Article
More Like This
Excitation spectra of surface-enhanced Raman scattering on silver-island films

D. A. Weitz, S. Garoff, and T. J. Gramila
Opt. Lett. 7(4) 168-170 (1982)

Surface-enhanced Raman scattering from silver particles on polymer-replica substrates

R. M. Hart, J. G. Bergman, and A. Wokaun
Opt. Lett. 7(3) 105-107 (1982)

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.