Analysis of Mixtures by FT-IR: Spatial and Spectral Separation of Complex Samples

Aug 01, 2008
By Spectroscopy Editors

Many analytical challenges to modern laboratories involve mixtures, whether formulated or contaminated. The infrared spectra of mixtures exhibit peaks from each component, making separation of peaks due to specific components an essential part of the analysis. This can be accomplished in two ways — spatial separation of components through microscopy or spectral separation through multicomponent searches. In either case, the final result should not just be a chemical image or spectrum, but actionable information. Further, users of varying skill levels need to obtain the same results, so consistency must be a core metric of the problem-solving tools.

Analytical and forensic laboratories are inundated with samples from many origins — contaminated product, competitive materials, or crime scene evidence. Their task often focuses on identification. In infrared, this is based primarily on comparison of the sample spectrum to library spectra. This was once done by overlaying spectra on a light box. Computers accelerated the process but did not change the fundamental approach of spectrum-by-spectrum comparisons. Both methods are still useful but experience one major shortcoming — a limited ability to handle mixtures. Digital spectral subtraction filled that gap partially, but suffered when totally absorbing peaks occurred, or when environmental changes altered peaks slightly. Because mixtures represent such a large fraction of the sample load listed above, new approaches have been sought. The two leading approaches involve spatial separation and multicomponent searching.

Infrared (IR) microscopy permits the spatial analysis of mixtures through the collection of spectral images. For example, a tablet consists of various components pressed into a solid piece. The individual components are not distributed continuously on the micro scale, but reside in domains within the tablet. Thus, IR images of the tablet show spectral variations over the surface. In a real sense, how the image is collected — point by point or using an array detector — is not important (except as regards time). What matters is the analysis of the final image to extract information that can be acted upon. The key answers are identity, size, and distribution of the material in the tablet and relative concentrations of the components. Armed with this information, the scientist can make intelligent decisions.

In contrast, the IR spectra of homogeneous mixtures exhibit simultaneous absorptions from the constituents. Simple searching followed by spectral subtraction works in some cases but can result in erroneous starting points and difficult-to-handle residuals. Subsequent searches might return the same result again, or might be affected by derivative-shaped bands or totally absorbing peaks. True multicomponent searching would not rely upon subtractions or other spectral processing. The result would be a list of candidate constituents and a visual display, which would again represent actionable information.

Consistency must be an essential component of mixture analysis. Subtraction requires use of a variable factor, which can lead to poor agreement between different users. Completely removing this step is thus required to reach the consistency needed to enable less technically advanced users to obtain useable results. Further, the increased throughput demanded of analysis laboratories, coupled with the multitechnique skill sets required of the staff, mean that these tools must be automated and reliable. The following sections examine heterogeneous and homogeneous mixtures with automated analysis protocols in both micro and macro domains.


The Thermo Scientific Nicolet iN10 MX FT-IR imaging microscope with OMNIC Picta microscopy software (Thermo Fisher Scientific, Madison, Wisconsin) was used to collect images from pharmaceutical tablets. The ultra-fast scanning of this microscope allows collection of several square millimeters in a few minutes, with a 25-μm spatial resolution. The complete analysis presented used the OMNIC Picta Random Mixtures Wizard.

The Thermo Scientific Nicolet iS10 FT-IR Spectrometer, Smart iTR diamond attenuated total reflection (ATR) accessory, and OMNIC spectroscopy software were used to collect the IR spectrum of a pharmaceutical powder and a computer monitor cover. The thermogravimetric analysis (TGA) data were collected using the same spectrometer equipped with an internal TGA accessory. Data were exported to OMNIC Specta spectroscopy software for the multicomponent search.

Microscopically Granular Mixtures

Figure 1
Many solid materials display granularity in the 5–200 μm range — pharmaceutical tablets, fisheye distortions in polymer sheets, and sectioned museum artifacts are common examples. Consider the fisheye example: the questions may be what contaminant caused the fisheye? How prevalent is the contamination? How is it distributed in the sample? An image alone does not convey all this information. Consider Figure 1, which shows an image of a two-component pharmaceutical tablet. The color coding represents the intensity of the signal at the scroll bar location in the bottom spectrum (about 1680 cm–1) — red shows an intense signal, and blue shows a weak signal. The image communicates some distribution and identification information, but there is still untapped potential in the data. Further, if there were three components in this region, the image would not convey that information.

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