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Infrared spectroscopy

Measurement of infrared radiation's interaction with matter

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  • 6 chapters
The OSIRIS-REx Visible and Infrared Spectrometer (OVIRS) will measure visible and near infrared light from the asteroid Bennu. The instrument's observations could be used to identify water and organic
NASA · Public domain

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Through Matter, Emission spectrum and Reflection (physics)

The infrared portion of the electromagnetic spectrum is usually divided into three regions; the near-, mid- and far- infrared, named for their relation to the visible spectrum. The higher-energy near-IR, approximately 14,000–4,000 cm−1 (0.7–2.5 μm wavelength) can excite overtone or combination modes of molecular vibrations. The mid-infrared, approximately 4,000–400 cm−1 (2.5–25 μm) is generally used to study the fundamental vibrations and associated rotational–vibrational structure. The far-infrared, approximately 400–10 cm−1 (25–1,000 μm) has low energy and may be used for rotational spectroscopy and low frequency vibrations. The region from 2–130 cm−1, bordering the microwave region, is considered the terahertz region and may probe intermolecular vibrations. The names and classifications of these subregions are conventions, and are only loosely based on the relative molecular or electromagnetic properties.

Uses and applications

Infrared spectroscopy is a simple and reliable technique widely used in both organic and inorganic chemistry, in research and industry. It is used in quality control, dynamic measurement, and monitoring applications such as the long-term unattended measurement of CO2 concentrations in greenhouses and growth chambers by infrared gas analyzers.

It is also used in forensic analysis in both criminal and civil cases, for example in identifying polymer degradation. It can be used in determining the blood alcohol content of a suspected drunk driver.

IR spectroscopy has been used in identification of pigments in paintings and other art objects such as illuminated manuscripts.

Infrared spectroscopy is also useful in measuring the degree of polymerization in polymer manufacture. Changes in the character or quantity of a particular bond are assessed by measuring at a specific frequency over time. Instruments can routinely record many spectra per second in situ, providing insights into reaction mechanism (e.g., detection of intermediates) and reaction progress.

Infrared spectroscopy is utilized in the field of semiconductor microelectronics: for example, infrared spectroscopy can be applied to semiconductors like silicon, gallium arsenide, gallium nitride, zinc selenide, amorphous silicon, silicon nitride, etc.

Another important application of infrared spectroscopy is in the food industry to measure the concentration of various compounds in different food products.

Infrared spectroscopy is also used in gas leak detection devices such as the DP-IR and EyeCGAs. These devices detect hydrocarbon gas leaks in the transportation of natural gas and crude oil.

Infrared spectroscopy is an important analysis method in the recycling process of household waste plastics, and a convenient stand-off method to sort plastic of different polymers (PET, HDPE, ...).

Other developments include a miniature IR-spectrometer that's linked to a cloud based database and suitable for personal everyday use, and NIR-spectroscopic chips that can be embedded in smartphones and various gadgets.

In catalysis research it is a very useful tool to characterize the catalyst, as well as to detect intermediates.

Infrared spectroscopy coupled with machine learning and artificial intelligence also has potential for rapid, accurate and non-invasive sensing of bacteria. The complex chemical composition of bacteria, including nucleic acids, proteins, carbohydrates and fatty acids, results in high-dimensional datasets where the essential features are effectively hidden under the total spectrum. Extraction of the essential features therefore requires advanced statistical methods such as machine learning and deep-neural networks. The potential of this technique for bacteria classification have been demonstrated for differentiation at the genus, species and serotype taxonomic levels, and it has also been shown promising for antimicrobial susceptibility testing, which is important for many clinical settings where faster susceptibility testing would decrease unnecessary blind-treatment with broad-spectrum antibiotics. The main limitation of this technique for clinical applications is the high sensitivity to technical equipment and sample preparation techniques, which makes it difficult to construct large-scale databases. Attempts in this direction have however been made by Bruker with the IR Biotyper for food microbiology.

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