Infrared spectroscopy

Infrared spectroscopy is the measurement of the interaction of infrared radiation with matter by absorption, emission, or reflection. It is used to study and identify chemical substances or functional groups in solid, liquid, or gaseous forms. It can be used to characterize new materials or identify and verify known and unknown samples. The method or technique of infrared spectroscopy is conducted with an instrument called an infrared spectrometer which produces an infrared spectrum. An IR spectrum can be visualized in a graph of infrared light absorbance on the vertical axis vs. frequency, wavenumber or wavelength on the horizontal axis. Typical units of wavenumber used in IR spectra are reciprocal centimeters, with the symbol cm⁻¹. Units of IR wavelength are commonly given in micrometers, symbol μm, which are related to the wavenumber in a reciprocal way. A common laboratory instrument that uses this technique is a Fourier transform infrared spectrometer. Two-dimensional IR is also possible as discussed [|below].
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 can excite overtone or combination modes of molecular vibrations. The mid-infrared, approximately 4,000–400 cm⁻¹ is generally used to study the fundamental vibrations and associated rotational–vibrational structure. The far-infrared, approximately 400–10 cm⁻¹ 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 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.
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.

Theory

Infrared spectroscopy exploits the fact that molecules absorb frequencies that are characteristic of their structure. These absorptions occur at resonant frequencies, i.e. the frequency of the absorbed radiation matches the vibrational frequency. The energies are affected by the shape of the molecular potential energy surfaces, the masses of the atoms, and the associated vibronic coupling.
In particular, in the Born–Oppenheimer and harmonic approximations, the resonant frequencies are associated with the normal modes of vibration corresponding to the molecular electronic ground state potential energy surface. Thus, it depends on both the nature of the bonds and the mass of the atoms that are involved. Using the Schrödinger equation leads to the selection rule for the vibrational quantum number in the system undergoing vibrational changes:
The compression and extension of a bond may be likened to the behaviour of a spring, but real molecules are hardly perfectly elastic in nature. If a bond between atoms is stretched, for instance, there comes a point at which the bond breaks and the molecule dissociates into atoms. Thus real molecules deviate from perfect harmonic motion and their molecular vibrational motion is anharmonic. An empirical expression that fits the energy curve of a diatomic molecule undergoing anharmonic extension and compression to a good approximation was derived by P.M. Morse, and is called the Morse function. Using the Schrödinger equation leads to the selection rule for the system undergoing vibrational changes :

Number of vibrational modes

In order for a vibrational mode in a sample to be "IR active", it must be associated with changes in the molecular dipole moment. A permanent dipole is not necessary, as the rule requires only a change in dipole moment.
A molecule can vibrate in many ways, and each way is called a vibrational mode. For molecules with N number of atoms, geometrically linear molecules have 3N – 5 degrees of vibrational modes, whereas nonlinear molecules have 3N – 6 degrees of vibrational modes. As examples linear carbon dioxide has 3 × 3 – 5 = 4, while non-linear water, has only 3 × 3 – 6 = 3.
Simple diatomic molecules have only one bond and only one vibrational band. If the molecule is symmetrical, e.g. N₂, the band is not observed in the IR spectrum, but only in the Raman spectrum. Asymmetrical diatomic molecules, e.g. carbon monoxide, absorb in the IR spectrum. More complex molecules have many bonds, and their vibrational spectra are correspondingly more complex, i.e. big molecules have many peaks in their IR spectra.
The atoms in a CH₂X₂ group, commonly found in organic compounds and where X can represent any other atom, can vibrate in nine different ways. Six of these vibrations involve only the CH₂ portion: two stretching modes : symmetric and antisymmetric ; and four bending modes: scissoring, rocking, wagging and twisting, as shown below. Structures that do not have the two additional X groups attached have fewer modes because some modes are defined by specific relationships to those other attached groups. For example, in water, the rocking, wagging, and twisting modes do not exist because these types of motions of the H atoms represent simple rotation of the whole molecule rather than vibrations within it. In case of more complex molecules, out-of-plane vibrational modes can be also present.

	Symmetric	Antisymmetric
Radial	Image:Symmetrical stretching.gif Symmetric stretching	Image:Asymmetrical stretching.gif Antisymmetric stretching
Latitudinal	Image:Scissoring.gif Scissoring	Image:Modo rotacao.gif Rocking
Longitudinal	Image:Wagging.gif Wagging	Image:Twisting.gif Twisting

These figures do not represent the "recoil" of the C atoms, which, though necessarily present to balance the overall movements of the molecule, are much smaller than the movements of the lighter H atoms.
The simplest and most important or fundamental IR bands arise from the excitations of normal modes, the simplest distortions of the molecule, from the ground state with vibrational quantum number v = 0 to the first excited state with vibrational quantum number v = 1. In some cases, overtone bands are observed. An overtone band arises from the absorption of a photon leading to a direct transition from the ground state to the second excited vibrational state. Such a band appears at approximately twice the energy of the fundamental band for the same normal mode. Some excitations, so-called combination modes, involve simultaneous excitation of more than one normal mode. The phenomenon of Fermi resonance can arise when two modes are similar in energy; Fermi resonance results in an unexpected shift in energy and intensity of the bands etc.