Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group
  • Applied Spectroscopy
  • Vol. 43,
  • Issue 3,
  • pp. 468-473
  • (1989)

Photoacoustic Detection of Rapid-Scan Fourier Transform Infrared Spectra from Low-Surface-Area Solid Samples

Not Accessible

Your library or personal account may give you access

Abstract

We have demonstrated that the PAS cell volume, and the state of the background material as well as the interferometer mirror velocity and the cell gas composition, must be controlled when one is recording spectra of solid samples. An optically thick, totally absorbing material with a volume matching that of the sample is needed in order to properly normalize spectra of solid samples. With the proper detection bandwidth, mirror speeds of up to 0.181 cm/s can be used with helium as a transfer medium, for the cell specified. The improvement attained at high frequency by using helium can be as much as 10-fold over that obtained with air. The Helmholtz design of the cell produces a resonance at 1.4 kHz with air and 2.65 kHz with helium. These resonances are also affected by the volume and composition of the gas in the sample chamber. Thus, it is essential to select an appropriate background sample for the purpose of normalizing spectra.

PDF Article
More Like This
Quantitative Fourier transform IR photoacoustic spectroscopy of condensed phases

Y. C. Teng and B. S. H. Royce
Appl. Opt. 21(1) 77-80 (1982)

High temperature Fourier transform photoacoustic spectroscopy: sample emission effects

S. McGovern, B. S. H. Royce, and J. Benziger
Appl. Opt. 24(10) 1512-1514 (1985)

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.