Quantitative analysis DRIFTS

For quantitative analysis, determine the linear range required to measure the least concentrated and most concentrated analytes. If desired, select an internal standard. If the migration time or peak area of the standard changes, then you have an indication that some condition has drifted out of control. 

There are a variety of other factors that influence the accuracy of quantitative analysis. Noise, in the form of baseline disturbances and baseline drift, affects area more than it does height, as it can cause area to be lost at the tailing edges of the peaks where they are widest. Peak asymmetry and detector saturation or nonlinearity, however, have a more detrimental effect on peak height. Figure 7.6 shows a calibration curve comparing peak height measurements with peak area measurements.13... 

Diffuse reflectance IR spectroscopy has become an attractive alternative to mulls with the introduction of DRIFT cell by Griffiths,29 later modified by Yang.30 Since materials are dispersed in a nonabsorbing medium and not subjected to thermal or mechanical energy during sample preparation, DRIFT spectroscopy is especially suitable for the qualitative/quantitative analysis for polymorphs, which are prone to solid-state transformations. The Kubelka-Munk (K-M) equation,31 which is analogous to Beer s law for transmission measurements, is used to quantitatively describe diffusely-reflected radiation ... 

The majority of Raman spectra reported in the literature are uncorrected for instrument response, so one could argue that the most common response correction is none at all. Uncorrected spectra are still valuable for qualitative applications involving comparison of peak frequencies and for quantitative comparisons where the response function is unknown but constant. For example, a quantitative analysis of two components based on the relative heights (or areas) of two Raman bands can be calibrated with known solutions and applied to unknowns without determination of the response function. However, there are many situations in which response function calibration is important, including variations in relative intensity with different instruments, variations caused by instrumental drift or repair, and subtraction of library spectra (see Fig. 5.6). If a quantitative analysis is based on a calibration curve without response correction, a new curve must be collected if a change in response... 

Quantitative analysis is normally performed by preparing calibration curves using external standards. To compensate for instrument drifts, instabilities, and matrix effects, an internal standard is usually added to the standards and to the sample. Multiple internal standards are sometimes used to optimize matching of the characteristics of the standard to those of various analytes. 

Images of the adsorbed PEI can be captured at different scan sizes < 500 x 500 nm2. The choice of the scan rate is a trade-off between optimized feedback loop and the effect of instrumental drift. In the dual height and phase images shown in Fig. 3.12 individual molecules, as well as clusters, can be differentiated. The quantitative analysis of the observed features together with results from a series of experiments with a systematic variation of the charge density led to the... 

The data generated from a NIR or Raman spectrum do not immediately provide the concentrations of the species at any time, so there is no predictive capability. Construction of a calibmtion set requires an independent measure of the property, e.g. by HPLC or by NIR of known mixtures of the components. Two such methods are principal-component regression (PCR) and partial least squares (PLS). As soon as quantitative analysis is considered, the question of noise and reproducibility of the data set becomes important. It is therefore necessary to treat the mw data to remove the drift in baseline etc. which will occur over a long period of spectml acquisition. 

In all quantitative analysis the drift in the spectra is commonly addressed hy normalization of all peaks against an invariant peak. This requires knowledge of the system as well as assignments for the major hands. Where possible, normalization is the first step in pretreatment of the data. If Raman spectm are strongly influenced by fluorescence then this is removed (by a polynomial fit to the broad, underlying profile) prior to normalization (Stellman et al, 1995). 

Qualitative and Quantitative Analysis of the DRIFT Spectra. DRIFT spectra are usually presented in Kubelka-Munk units. DRIFT spectra with small baseline errors can be obtained when measurements are made at ambient temperature. However, if measurements are performed at higher temperatures, IR radiation emitted from the heated sample can affect the collected spectra, especially if MCT detectors are employed. This is even more pronounced when the refractivity of the sample changes with time. The baseline artifacts are added to the collected spectra. 

Diffuse reflectance or DRIFTS (diffuse reflectance infrared Fourier-lransform spectroscopy) allows the sain)le to be analysed neat, ot diluted in a non-absorbing matrix (e.g. KCl or KBr at 1-5% w/w analyte). DRIFTS also may be used to obtain the spectrum of a solute in a volatile solvent by evaporating the solution onto KBr. When the IR radiation interacts with the powdered sample it will be absorbed, reflected and diffracted. The radiation which has been diffusely reflected contains vibrational information on the molecule. This technique allows non-destructive testing of neat materials and is suited to quantitative analysis, although care must be taken to ensure that a consistent particle size is used. 

F. C. Meunier, D. Reid, A. Goguey, S. Shekhtman, C. Hardacre, R. Burch, W. Deng, M. F. Stephanopoulos, Quantitative analysis of the reactivity of formate species seen by DRIFTS over a Au/Ce(La)02 water gas shift catalyst first unambiguous evidence of the minority role of formates as reaction intermediates, J. Catal. 247 (2007) 277-287. 

The final point concerns the units in which a DR spectrum of adsorbed species should be represented for quantitative analysis. The application of DRIFTS for quantitative measurements is restricted not only by the variation in band intensities caused by irreproducible sample preparation but also by the nonlinear behavior of the reflectance due to scattering effects [168]. To increase the linear range, some authors [168-170] use KM units [Eq. (1.133)], while others [171-174] prefer absorbance, -logRoo (or l/Roo), where Roo is the reflectance spectrum of an inflnitely thick sample relative to that of a nonadsorbing reference. For small values of K/S (where K and S are the KM absorption and scattering coefficients, respectively), such as is the case for DRIFTS of ultrathin films. Burger et al. [175] have shown that absorbance is proportional to the square root of KM units ... 

It follows that KM units are more suitable for quantitative analysis. However, in some cases the transformation into absorbance leads to a more linear relation between — log Roo and analyte concentration [175]. Selecting units for representing spectra, it should be taken into account that the DRIFTS spectral pattern drawn in absorbance can be different from that drawn from the KM equation [172]. 

Application of such a calibration to quantitative analysis of sample extracts requires that these extracts be spiked with the identical quantity Qvis.a of volumetric internal standard as used in the calibration experiments. (It is emphasized that all of these spiking procedures, i.e. calibration solutions plus sample extracts, should be done at the same time, to minimize any drift in the value of Cyis as a result of uncontrolled evaporation.) Then it is straightforward to show that ... 

SPC requires reliable data that can be analyzed either in real time or historically. Visual inspection collects defect data, such as the number of solder joint defects per assembly right after the solder reflow process (either reflow or wave soldering). Some manual and automated inspection techniques also take quantitative measurements of key assembly parameters, such as solder paste volume or solder joint fillet height. To the extent that these data are repeatable, manufacturers use defect data or measurements to characterize the amount of process variation from assembly to assembly or from solder joint to solder joint. When the amount of variation starts to drift outside its normal range or outside its control limits, manufacturers can assess the assembly process and monitor or choose to take action until the process is adjusted to eliminate this drift. Historical analysis of the defect or measurement... 

Meunier, F., Reid, D., Goguet, A., et al. (2007). Quantitative Analysis of the Reactivity of Formate Species Seen hy DRIFTS over an Au/Ce(La)02 Water-Gas Shift Catalyst First Unambiguous Evidence of the Minority Role of Formatesas Reaction Intermediates, J. Catal., 247, pp. 277-287. 

Culler [138] has recently reviewed the sampling techniques for qualitative and quantitative analysis of solids by DRIFTS. 

For semiquantitative analysis that uses a stored response table, the purpose of the internal standard is similar, but a little different in implementation to quantitative analysis. A semiquant internal standard is used to continuously compensate for instrument drift or matrix-induced suppression over a defined mass range. If a single internal standard is used, all the masses selected for the determination are updated by the same amount based on the intensity of the internal standard. If more than one internal standard is used, which is recommended for measurements over a wide mass range, the software interpolates the intensity values based on the distance in mass between the analyte and the nearest internal standard element. 

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