4.6 Article

Automated Quantitative Spectroscopic Analysis Combining Background Subtraction, Cosmic Ray Removal, and Peak Fitting

期刊

APPLIED SPECTROSCOPY
卷 67, 期 8, 页码 949-959

出版社

SAGE PUBLICATIONS INC
DOI: 10.1366/12-06766

关键词

Automated baseline subtraction; Cosmic ray removal; Peak analysis; Quantitative spectroscopic analysis; Raman spectroscopy; Rolling-circle filter

资金

  1. Helmholtz Association (HGF)
  2. German Ministry for Education and Research (BMBF) [05A08VK2, 05A11VK3]
  3. Deutsche Forschungs Gemeinschaft (DFG) [SFB/TR 27]
  4. UK Engineering and Physical Sciences Research Council (EPSRC)
  5. Karlsruhe House of Young Scientists (KHYS)

向作者/读者索取更多资源

An integrated concept for post-acquisition spectrum analysis was developed for in-line (real-time) and off-line applications that preserves absolute spectral quantification; after the initializing parameter setup, only minimal user intervention is required. This spectral evaluation suite is composed of a sequence of tasks specifically addressing cosmic ray removal, background subtraction, and peak analysis and fitting, together with the treatment of two-dimensional charge-coupled device array data. One may use any of the individual steps on their own, or may exclude steps from the chain if so desired. For the background treatment, the canonical rolling-circle filter (RCF) algorithm was adopted, but it was coupled with a Savitzky-Golay filtering step on the locus-array generated from a single RCF pass. This novel only-two-parameter procedure vastly improves on the RCF's deficiency to overestimate the baseline level in spectra with broad peak features. The peak analysis routine developed here is an only-two-parameter (amplitude and position) fitting algorithm that relies on numerical line shape profiles rather than on analytical functions. The overall analysis chain was programmed in National Instrument's LabVIEW; this software allows for easy incorporation of this spectrum analysis suite into any LabVIEW-managed instrument control, data-acquisition environment, or both. The strength of the individual tasks and the integrated program sequence are demonstrated for the analysis of a wide range of (although not necessarily limited to) Raman spectra of varying complexity and exhibiting nonanalytical line profiles. hi comparison to other analysis algorithms and functions, our new approach for background subtraction, peak analysis, and fitting returned vastly improved quantitative results, even for hidden details in the spectra, in particular, for nonanalytical line profiles. All software is available for download.

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