Semi-Quantitative Profiles

Semi-quantitative profiles are used for elements present at low content levels (< 0.3% weight) and/or if the matrix is heterogeneous (the composition of the matrix varies from one analysis point to another). This is the analysis method most commonly used for the study of catalysts. 

Zr02 films become thicker with increasing numbers of dips in the sol gel solution, reaching more than 200 nm after 4 dips in the solution. However, GDOES semi-quantitative profiles reveal that the increase in film thickness is limited for... 

Although analytical procedures based on GC/MS analysis usually involve a relatively long analysis time, requiring a wet chemical pretreatment of the samples, they are unsurpassed in their capacity to unravel the molecular composition of the lipids used in works of art and in archaeological findings at a molecular level. In addition to obtaining a qualitative molecular profile, GC permits quantitative or semi-quantitative measurements on specific molecules. 

First of all it is seen that the SCF results are free of any noise, whereas there is plenty of noise in the MD profiles (note, however, that the density profiles on both halves of the bilayer are in this case not averaged the close resemblance between the profiles on both halves thus indicates that the membranes are well equilibrated). Apart from this, inspection of Figure 18 shows a remarkable resemblance between the two set of predictions. Many details are in semi-quantitative agreement. Moreover, many of the features of membranes composed of SOPC resemble those of DMPC discussed above. For example, the width of the membrane-water interface is about 1 nm, i.e. the size of just two to three water molecules. This width is consistent with the scaling arguments mentioned at the beginning of this chapter. A more accurate comparison... 

In contrast to SIMS, in SNMS - where the evaporation and ionization processes are decoupled -the matrix effects are significantly lower, because the composition of sputtered and post-ionized neutrals corresponds more closely to the composition in the solid sample (compared to the sputtered secondary ions in SIMS), which means the RSCs of elements vary by about one order of magnitude. Consequently, a semi-quantitative analysis by SNMS can also be carried out if no suitable matrix matched CRM is available. This is relevant for thin film analysis, especially for the determination of elemental concentration profiles in depth, for studying the stoichiometric composition of thin films and interdiffusion effects. 

Fast, semi-quantitative elemental analysis (less accurate than XPS owing to a combination of less well-known cross-sections, and the manner in which the data are usually taken). Simultaneous Ar+ profiling. 

Figure 1. Phase identification using Si/Al ratio images, a) silicon b) aluminum c) Si/Al ratio image d) Si/Al intensity profile e) selection of intensity cut-offs f) "semi-quantitative" phase map...

Histology may be reported in descriptive terms, evaluated by a semi-quantitative methods, or by computer-assisted histomorphometric methods. This information then can be used for quantitative statistical analysis. For the very specific add-on methods of in situ hybridization and gene expression, a description of the observed changes is generally appropriate together with quantitative data generated by computer-assisted analysis of gene expression profiles. 

Medium resolution Semi-quantitative Differential expression Detects PTMs Medium resolution Semi-quantitative Improved differential Detects PTMs Low resolution Rapid profiling biofluids Signatures Small sample size Immunoaffinity separation Rapid multiplex analysis Immunoaffinity protein ID Small sample size... 

A comparison of the values of I1 and n[Al] (where N[A1] refers to the number of aluminium atoms per unit cell) reveals a semi-quantitative correlation between the framework aluminium content and the integrated intensities of the difference profiles (i.e. n[A1]/I = 4 1). 

This semi-quantitative approach of displaying the electron density profile at the resolution appropriate to the data shows that the range of data acquired in a CTR measurement is closely coupled with the aspects of the structure that can be uniquely determined from the data. This approach is also a useful way to test the uniqueness of a particular set of fitting results. Different models that reproduce the reflectivity data equally well might suggest a lack of uniqueness in the CTR data, but in many cases actually correspond to identical electron density profiles. In some cases, best-fit structural models simply cannot be distinguished on the basis of the X-ray reflectivity data alone. 

Multivariate curve resolution is widely applicable to separations data and is one of the most common approaches (Franch-Lage et al, 2011 Marini et al., 2011, de la Mata-Espinosa et al., 2011a). The aim of this technique is to determine the number of components present in a sample and the contribution of each component to the sample. In performing MCR, the concentration and response profiles for each analyte are obtained, providing a qualitative and semi-quantitative overview of the components in an unresolved mixture without a priori knowledge of the mixture composition. 

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