Spectroscopy-06-01-2016

Spectroscopy

This column addresses the issue of degrees of freedom (df) for regression models. The use of smaller degrees of freedom (df) (e.g., n or n-1) underestimates the size of the standard error; and possibly the larger df (e.g., n-k-1) overestimates the size of the standard deviation. It seems one should use the same df for both SEE and SECV, but what is a clear statistical explanation for selecting the appropriate df? It is a good time to raise this question once again and it seems there is some confusion among experts about the use of df for the various calibration and prediction situations - the standard error parameters should be comparable and are related to the total independent samples, data channels containing information (i.e., wavelengths or wavenumbers), and number of factors or terms in the regression. By convention everyone could just choose a definition but is there a more correct one that should be verified and discussed for each case? The problem with this subject is in computing the standard deviation using different df without a more rigorous explanation and then putting an over emphasis on the actual number derived for SEE and SECV, rather than on using properly computed confidence intervals. Note that confidence limit computations for standard error have been discussed previously and are routinely derived in standard statistical texts (4).

Recent advances in instrumentation have enabled new forms of vibrational chemical imaging, including discrete frequency infrared (DFIR) microscopy and stimulated Raman scattering (SRS) microscopy. These technologies may represent a fundamental shift in how we approach spectroscopic imaging: rather than collecting full spectra which contain redundant information, measuring a few important spectral frequencies may enable significant gains in speed, throughput, signal to noise ratio, and/or image quality. For infrared microscopy, these advantages may be compounded by High Definition IR microscopy. Here we discuss recent advances in infrared and nonlinear Raman imaging through the lens of 'discrete frequency' approaches, including several examples of applications and critical issues in instrumentation that are likely to be dominating research themes in the near future.

Spectroscopy
Lasers and Optics Interface

June 01, 2016

Vassilia Zorba of Lawrence Berkeley National Laboratory in Berkeley, California, discusses what her studies have revealed about the mechanisms of plasma emission at small scales and what she has found when applying femtosecond LIBS to the study of advanced battery materials.

Spectroscopy Spotlight
Spectroscopy

June 01, 2016

Inductively coupled plasma (ICP), coupled with optical emission spectroscopy (OES) and mass spectrometry (MS), has seen a lot of recent growth for the direct analysis of organic samples such as petroleum and biofuels. José-Luis Todolí of the University of Alicante in Spain talks about his work to improve the analytical figures of merit in ICP-OES and ICP-MS in these analyses.

Spectroscopy
Application Notes (Advertising Content)

June 01, 2016

Miniature X-ray sources reached the development level that is appropriate for their use in the handheld and portable X-Ray diffraction (XRD) instruments. This note describes the application of X-ray sources for the residual stress measurements using XRD.

Spectroscopy

Spectrochemical analysis is a comparative technique; therefore, unknown samples are best analyzed against reference materials of similar composition.

Issue PDF
Spectroscopy

June 01, 2016

Click the title above to open the Spectroscopy June 2016 regular issue, Vol 31 No 6, in an interactive PDF format.