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How Near Infrared Chemical Imaging Works

Near Infrared (NIR) spectroscopy is a widely used technique that detects the presence of different chemical bonds through the analysis of optical absorption in the wavelength range 700 to 2500 nm.

by Ulf Willén
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Problem: For some analytical applications it is essential to have a non-destructive technique that identifies, quantifies and locates chemical species within a sample. This is important where product performance or verification depends on the physical location of a substance—within a tablet or granule for example—or where the aim is to detect “the needle in the haystack.” Near Infrared (NIR) spectroscopy is a widely used technique that detects the presence of different chemical bonds through the analysis of optical absorption in the wavelength range 700 to 2500 nm. In this range lie absorption bands attributable to overtones and combination bands of O-H, N-H and C-H stretching and bending vibrations, so the technique is suitable for analyzing many organic molecules. Conventional NIR is extremely useful but it is an averaging analytical method, yielding just one spectrum for each sample. Imaging techniques, on the other hand, provide spatially resolved information, presenting statistically relevant results derived from thousands of individual measurements.

The SyNIRgi near infrared chemical imaging system from Malvern Instruments.

Solution: Near Infrared Chemical Imaging (NIRCI), as its name suggests, combines the advantages of conventional NIR and advanced optical imaging technology to give spatially resolved chemical analysis. The technique is nondestructive, requires no sample preparation and is suitable for a very broad range of products including: powders, granules, tablets and skin tissue. Although it is relatively new, made possible by recent advances in imaging technology and computing power, the capabilities NIRCI offers have generated significant interest. This is especially true in the pharmaceutical industry where robust, easy-to-use commercial systems are proving to be valuable tools for counterfeit detection and product development.

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Produces not one, but tens of thousands of spectra, with a typical analysis capturing around 80,000 spectra. Each spectrum is associated with an individual area or pixel, across the surface of the sample. Interpreting the data demands detailed statistical analysis, but this is facilitated by powerful software that makes a range of mathematical techniques accessible, and provides chemometric and morphological tools in a user-friendly format. The results identify not only the chemical species present but their exact location within a sample.

The principal components of a NIRCI analyzer are: a radiation source, a tunable wavelength filter and a two-dimensional array detector. Quartz lamps are a safe and easy choice for the provision of NIR radiation while the liquid crystal filter enables wavelength discrimination and maintains image quality. The two-dimensional array is a key feature of a true NIRCI instrument since it eliminates the need for sample movement during analysis and the ‘step and acquire’ mode of operation associated with more basic mapping instruments that have a line array or single detector. A NIRCI analyzer has no moving parts. Consequently it does not require specialized laboratory benching, and because there is nothing present that can become mis-aligned, there is no need for frequent calibration. Also, the optics have long working distances that allow the analyst to configure for a small field of view (a single tablet or granule) or a larger area, such as a complete blister pack, at lower magnification.

For exploratory research into, for example, inter-component bonding or association and its impact on product performance, data may be gathered over the complete NIR wavelength range. However, where the aim is to determine, say, the abundance of a specific component or blend homogeneity, it may be sufficient to simply analyze data at one or two pre-determined wavelengths. In this case measurement times are slashed from minutes to seconds. This is a good approach for applications such as counterfeit detection where, in the first instance, the analyst wants to rapidly determine whether the product is genuine or not.

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