Multi-component spectra

It is usually quite difficult to control the experimental conditions such that only one paramagnetic species is present. ESR-methods that are capable of discriminating between different species were discussed in Chapter 2. At present these methods have lower sensitivity than CW-ESR. An analysis of ESR-spectra containing several radicals illustrates the procedure when only ESR data are available. 

When coronene, C24H12, (C) is treated with thallium(III) trifluoroacetate as oxidant under dried nitrogen atmosphere in l,l,l,3,3,3-hexafluoropropane-2-ol solvent coronene radical species are formed. Depending on the sample preparation the ESR spectra are dominated by the monomeric ion (C) , or are superpositions of spectra due to ( ) and the dimeric ion (C2) or even the trimeric ion (Cs). A stick-plot analysis of the spectrum of the nearly pure monomer is part of Exercise E3.5. It is also possible to accurately measure the hyperfine coupling constant (0.0766 mT for 24 H) and the corresponding peak-peak line-width (AHpp = 0.009 mT) for the ( 2) species in Eig. 3.7(b), since the lines are quite sharp, compared to those from the monomer. The line shape of ( 2) can therefore be obtained by simulation, that of ( ) from experiment The component spectra are then superimposed in a ratio appropriate for the experimental spectrum. This ratio is usually obtained by manual adjustment for best visual agreement with the experimental line shape in the present 

---

Fig. 4.3 Ranges of isomer shifts observed for Fe compounds relative to metallic iron at room temperature (adapted from [24] and complemented with recent data). The high values above 1.4-2 mm s were obtained from Co emission experiments with insulators like NaCl, MgO or Ti02 [25-28], which yielded complex multi-component spectra. However, the assignment of subspectra for Fe(I) to Fe(III) in different spin states has never been confirmed by applied-field measurements, or other means. More recent examples of structurally characterized molecular Fe (I)-diketiminate and tris(phosphino)borate complexes with three-coordinate iron show values around 0.45-0.57 mm s [29-31]. The usual low-spin state for Fe(IV) with 3d configuration is 5 = 1 for quasi-octahedral or tetrahedral coordination. The low-low-spin state with S = 0 is found for distorted trigonal-prismatic sites with three strong ligands [30, 32]. Occurs only in ferrates. There is only one example of a molecular iron(VI) complex it is six-coordinate and has spin S = 0 [33]...

Although there are some similarities between the (iSR data for the Pd and the Th-doped samples (in both cases latger-moment magnetism is induced and multi-component spectra are observed in the ordered state), distinct differences exist in details. Part of this is due to the fact that the Th-containing samples predated the availabiUty of high-quality UPts as the starting material. It would be desirable to repeat the study of Th-dqied UPts with high-quality samples in order to draw a more direct conqrarison. 

Several Auger point spectra were recorded for each material, showing that all were laterally homogenous except for the occasional contaminant particle. In addition, time-dependent spectra confirmed that the chemistry of the. surfaces was not altered by electron irradiation. In general the spectral components were poorly resolved in the expanded spectra, even when the analyzer was operated at a nominal resolution of less than I eV. Curve fitting would in principle have assisted in resolving the spectra, but the complex shapes involved in the multi-component spectra would have made interpretation problematic. 

The relationship between what is recorded in a SSIMS spectrum and the chemical state of the surface is not as straightforward as in XPS and AES (Chap. 2). Because of the large number of molecular ions that occur in any SSIMS spectrum from a multi-component surface (e. g. during the study of a surface reaction), much chemical information is obviously available in SSIMS, potentially more than in XPS. The problem in using the information from a molecular ion lies in the uncertainty of knowing whether or not the molecule represents the surface composition. For some materials. 

The fact that LEIS provides quantitative information on the outer layer composition of multi-component materials makes this technique an extremely powerful tool for the characterization of catalysts. Figure 4.19 shows the LEIS spectrum of an alumina-supported copper catalyst, taken with an incident beam of 3 keV 4He+ ions. Peaks due to Cu, A1 and O and a fluorine impurity are readily recognized. The high intensity between about 40 and 250 eV is due to secondary (sputtered) ions. The fact that this peak starts at about 40 eV indicates that the sample has charged positively. Of course, the energy scale needs to be corrected for this charge shift before kinematic factors Ef/E-, are determined. 

A more complex situation is a multi-component mixture where all pure standards are available, such as a mixture of four pharmaceuticals.3 It is possible to control the concentration of the reference compounds, so that a number of carefully designed mixtures can be produced in the laboratory. Sometimes the aim is to see whether a spectrum of a mixture can be employed to determine individual concentrations, and, if so, how reliably. The aim may be to replace a slow and expensive chromatographic method by a rapid spectroscopic approach. Another rather different aim might be impurity monitoring,4 how well the concentration of a small impurity may be determined, for example, buried within a large chromatographic peak. 

The intensities of the bands in the spectrum of a mixture are usually proportional to the concentrations of the individual components. It is thus possible to determine the concentration of one substance or to carry out a multi-component analysis. 

There are limits on this method which are imposed by the la e pacing of laser mode-noise peaks (130 MKz), setting an upper decay time limit of 7 ns, by detector noise background setting a lower Ifanit of 200 ps, of cost (of a spectrum analyser) and of difficulties in analysis of multi-component fluorescence. Since however any source could in principle be used to measure a noise spectmm, the method is worth further consideration. 

Multi-component spectrophotometric analysis The composition of mixtures of ribonucleotides, which may be obtained from RNA by alkaline hydrolysis or enzyme digestion, may be determined from the absorption spectrum of the solution in the range 220-300 nm. The calculation may be based on a large number (say 50) of absorptions throughout the spectrum and the... 

Understanding the knee of the spectrum remains an outstanding problem in cosmic-ray astrophysics. KASCADE-Grande (Haungs et al., 2003) will cover the energy range from below the knee to 1018 eV with a multi-component air shower array at sea level. The IceCube detector at the South Pole (Ahrens et... 

The concentration of certain components in a multi-component sample can be determined by quantitative analysis of its vibrational spectrum. Similar to quantitative analysis of X-ray diffraction spectra, the concentration of a component can be evaluated from the intensities of its vibration bands. For an IR spectmm, concentration is proportional to absorbance (A) according to the absorption law, also called Beer s Law. 

An intramolecular electronic energy transfer leading to Cr" emission takes place in the multi-component system 2 [6]. After the irradiation on the [Ru"(bpy)2(CN)2] luminescent fragment, the excitation is transferred to one of the -[CNCr (cy-clam)CN] subunits, whose emission spectrum is observed. However, it should be noted that system 2 does not really belong to the class of two-component sensore as... 

Without subtracting the residual sharp spectral components of spin-labeled ASYN in the presence of SUVs, a multi-component spectral simulation strategy is required in order to describe the experimental data (Fig. 9b, c). Three different contributions featuring different isotropic rotational mobilities can be allocated to free spin labels, labeled residues not bound to SUVs, and residues bound to SUVs by the following approach. The spectra of ASYN in the absence of liposomes are well described by a superposition of two components. Si and S2, where Si corresponds to the spectrum of the free spin label MTSSL measured independently. In the presence of SUVs, an additional component S3 is needed, corresponding to the broadened part of the spectra. The shape of component S3 and the prefactors... 

In this present chapter, an introduction is provided on how infrared spectroscopy can be used for quantitative analysis. First, the various ways in which an infrared spectrum can be manipulated for analysis are outlined. Concentration is an important issue in quantitative analysis and the important relationships are introduced. Not only may quantitative infrared analysis be carried out on simple systems, it can also be applied to multi-component systems. Here, some sttaight-forward examples will be used to demonstrate the analysis of the data obtained, while the calibration methods commonly applied to such infrared data will also be described. 

The various ways in which a spectrum can be manipulated in order to carry out quantitative analysis were examined. These included baseline correction, smoothing, derivatives, deconvolution and curve-fitting. The Beer-Lambert law was also introduced, showing how the intensity of an infrared band is related to the amount of analyte present. This was then applied to the simple analysis of liquid and solid samples. Then followed a treatment of multi-component mixtures. An introduction to the calibration methods used by infrared spectroscopists was also provided. 

Multi-component analysis can be readily apphed to the infrared spectra of minerals. The latter contain non-interacting components and so the spectrum of a mineral can be analysed in terms of a linear combination of the spectra of the individual components. However, the spectra of such solids exhibit a marked particle-size dependency. The particle size should be reduced (to 325 mesh) prior to preparation of an alkali halide disc. The pellet preparation involves separate grinding and dispersion steps because minerals tend not to be effectively ground in the presence of an excess of KBr. Figure 5.8 illustrates the analysis of a mineral containing several components. The sample spectrum (a) is shown, as well as the calculated spectrum (b) based on the reference spectra of a variety of standard mineral components. The residual difference spectrum (c) shows that the error between the two spectra is small. 

More complex mixtures can be analyzed in a similar way providing that there are no deviations from Beer s law. Derivative spectrophotometry can also be used to mathematically process the data after acquisition in order to improve spectral resolution in multi-component systems. In this approach the zero-order spectrum is derivatized to give first order (dA/dA) or higher plots of the rate of change of absorbance against absorbance. 

In particular, the ensemble of a new phase during phase separation proceeding in a multi-component system belongs to such systems. In this case, the turbidity spectrum method provides the determination of the mass-volume new-phase particle concentration, as well as the degree of phase transition this can be used to construct the molecular-mass polymer distribution function (the method of spectroturbidimetric titration for polymer solutions—subsection 3.2.3) and for a phase analysis (identification) of the pheise separation type in polymer. systems (paragraph 3.6.2.5, sections 6.2 and 6.4). 

The material presented above is based upon binary density data fits and multi-component density prediction at a single temperature. In order to handle a broad spectrum of temperatures, fits should be done across several Isotherms and then, ultimately, the fit coefficients (e.g. A, B, C and D in equation (8.15)) can themselves be fit to functions of temperature. 

This cell provided an increased NMR resolution of 2-4 Hz and reduced the sample volume to 10-25 il which is stiU very large in comparison with those normally employed in analytical LC. A set of NMR spectra obtained from the cell is shown in Figure 5. The flow rate was 1 ml/min and the first 15 spectra were taken over a period of 15 sec each (250-pl windows). Spectra 17-32 were taken over 30 sec intervals (OOO-pl windows) and spectra 36 - 40 over 60 sec intervals (1-ml windows). It is clearly seen that even with the improved cell the chromatographic resolution is seriously compromised to obtain NMR sensitivity. Multi-component mixtures that are only just resolved would result in a number of solutes being contained in the sample cell at one time and consequently impair the integrity of the NMR spectrum. Nevertheless, the work of Haw et al. (5), at the time, represented a significant advance in the LC/NMR technique. 

Nuclear hyperfine coupling results in a multi-line ESR spectrum, analogous to the spin-spin coupling multiplets of NMR spectra. ESR spectra are simpler to understand than NMR spectra in that second-order effects normally do not alter the intensities of components on the other hand, ESR multiplets can be much more complex when the electron interacts with several high-spin nuclei, and, as we will see in Chapter 3, there can also be considerable variation in line width within a spectrum. 

---