Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group
  • Applied Spectroscopy
  • Vol. 45,
  • Issue 8,
  • pp. 1377-1380
  • (1991)

Quantitative Analysis of Powdery Sample by Diffuse Reflectance Infrared Fourier Transform Spectrometry: Determination of the α-Component in Silicon Nitride

Not Accessible

Your library or personal account may give you access

Abstract

An application of diffuse reflectance infrared Fourier transform (DRIFT) spectrometry to determine powdery sample with an unknown particle size has been proposed. The usefulness of this technique has been demonstrated for the analysis of the α-component in Si<sub>3</sub>N<sub>4</sub> powders. The particle size of the α-component in Si<sub>3</sub>N<sub>4</sub> powder could be determined by measuring the peak intensity ratio between two peaks (500 and 690 cm<sup>−1</sup>) on the DRIFT spectrum, and the concentration could be determined by comparing the peak intensity to that of standard α-Si<sub>3</sub>N<sub>4</sub> with same particle size. The particle sizes and concentrations obtained by the DRIFT method were in good agreement with those obtained by the light-scattering method and x-ray diffractometry, respectively.

PDF Article
More Like This
Diffuse reflectance infrared spectrometry: characteristics of the diffuse and specular components

Paul W. Yang and Henry H. Mantsch
Appl. Opt. 26(2) 326-330 (1987)

Hybrid sampling approach for imaging Fourier-transform spectrometry

Simon A. Roy, Jérôme Genest, and Philippe Giaccari
Appl. Opt. 46(35) 8482-8487 (2007)

Infrared specular reflectance of pressed crystal powders and mixtures

Frederic E. Volz
Appl. Opt. 22(12) 1842-1855 (1983)

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.