Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group
  • Applied Spectroscopy
  • Vol. 71,
  • Issue 8,
  • pp. 1849-1855
  • (2017)

Determination of Depth in Transmission Raman Spectroscopy in Turbid Media Using a Beam Enhancing Element

Not Accessible

Your library or personal account may give you access

Abstract

This study demonstrates experimentally a method to enable prediction of depth of a chemical species buried in a turbid medium by using transmission Raman spectroscopy alone. The method allows the prediction of the depth of a single, chemically distinct layer within a turbid matrix by performing two measurements, with and without a beam enhancing element, or “photon diode.” The samples employed consisted of two different polymers, of total thickness 3.6 mm, whose optical properties are loosely relevant to pharmaceutical applications. A polymer layer of low-density polyethylene (LDPE) was placed at different positions within multiple layers of the polytetrafluoroethylene (PTFE) matrix and Raman spectra were recorded in each case. Both univariate and multivariate analyses were utilized to determine whether the depth of the LDPE layer could be predicted using the obtained data. The best-achieved RMSE of prediction was 4.2% of the total sample size (i.e., +/− 0.15 mm) with the multivariate approach.

© 2017 The Author(s)

PDF Article
More Like This
Characterisation of signal enhancements achieved when utilizing a photon diode in deep Raman spectroscopy of tissue

Martha Z. Vardaki, Pavel Matousek, and Nicholas Stone
Biomed. Opt. Express 7(6) 2130-2141 (2016)

Frequency offset Raman spectroscopy (FORS) for depth probing of diffusive media

Sanathana Konugolu Venkata Sekar, Sara Mosca, Andrea Farina, Fabrizio Martelli, Paola Taroni, Gianluca Valentini, Rinaldo Cubeddu, and Antonio Pifferi
Opt. Express 25(5) 4585-4597 (2017)

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.