External reflection spectrometry

Figure 21.23. Typical arrangement for IR spectroelectrochemical measurement by external reflection spectrometry. In this case, a trapezoidal CaFa window was used to optimize the amount of radiation passed through the cell. (Reproduced from [19], by permission of John Wiley Sons, Ltd. copyright 2002.)...

External-Reflection Spectrometry for Thin Films and Surfaces... 

Hasegawa, T., Nishijo, J., Umemura, J. and Theiss, W. (2001) Simultaneous evaluation of molecular-orientation and optical parameters in ultrathin films by oscillators-model simulation and infrared external reflection spectrometry. J. Phys. Chem. B, 105, 11178-11185. 

In the case that an organic phase contains light absorbing compounds, an external reflection (ER) absorption spectrometry is more useful than a TIR spectrometry [30,31]. Another advantage of the ER method is its higher sensitivity than the TIR method, especially as using s-polarized light. Therefore, it can be used as a universal absorption spectrometry of adsorbed species. Typical optical cells used for the TIR spectrometry and ER absorption spectrometry are shown in Fig. 3. 

Fig. 3. Total internal reflection cell used for the interfacial fluorescence lifetime measurement (left) and the external reflection absorption spectrometry (right).

If a material could be made extremely thin, for example, to the level of a single layer of molecules, this thin layer would transmit almost all of the infrared radiation, so that its infrared transmission spectrum could be measured. In fact, it is possible to measure a mid-infrared transmission spectrum from a thin soap film. It is usually practically difficult, however, to maintain such a thin film without it being supported by a substrate. For a thin film supported on a substrate, its infrared spectmm is often obtained by utilizing a reflection geometry. Two reflection methods are available for measuring infrared spectra from substrate-supported thin films, depending on the dielectric properties of the substrates used. External-reflection (ER) spectrometry, which is the subject of this chapter, is a technique for extracting useful information from thin films on dielectric (or nonmetallic) substrates, while reflection-absorption (RA) spectrometry, described in Chapter 10, is effective for thin films on metallic substrates [1]. In addition to these two reflection methods, attenuated total-reflection (ATR) spectrometry, described in Chapter 13 and emission spectroscopy, described in Chapter 15 may also be useful in some specific cases. 

Geriche A., Huhnerfiiss H., In situ investigation of saturated long-chain fatty acids at the air/water interface by external infrared reflection-absorption spectrometry, J. Pf s. Chem. 97 (1993) pp. 12899-12908. 

R. Mendelsohn, J.W. Brauner, and A. Gericke, External Infrared Reflection Absorption Spectrometry of Monolayer Films at the Air-Water Interface, Ann. Rev. Phys. Chem. 46 (1995) 305. (Review theory and practice of IRRAS as applied to Langmuir monolayers determination of conformational states of hydrocarbon tails and H-bonding, ionization states of head groups, and molecular orientation illustrated with experimental results on monolayers of single-chain amphiphiles, phospholipids and proteins.)... 

Mendelsohn R, Brauner J W and Gericke A 1995 External infrared reflection absorption spectrometry of monolayer films at the air-water interface Ann. Rev. Rhys. Chem. 46 305-34... 

As mentioned above a spectral profile in infrared spectrometry contains absorbencies at each wavenumber or wavelength of the absorbed radiation. This can be represented by an array of numbers that represent the absorbencies at different wavenumbers or wavelengths. This spectral profile may contain information that reflects the nature of the sample or can be correlated to a physical or chemical property of the system. When measurements are made with this intention, the spectral profiles can be represented by a matrix containing rows of numbers representing the spectral profiles and a column representing the external property (see Fig. 6.1). The relationship between the samples, that is, the relationship between the rows of the matrix, requires some clever mathematical decomposition of the data. 

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