Impurity distribution

Fig. 4.7. If the bar is repeatedly zone refined from left to right then more and more of the impurity will be swept to the right-hand end of the bar. A large number of zone-refining passes may be needed to make the left-hand half of the bar as pure os we need. The right-hand half is cut off and recycled. Note that eqn. (4.9) con only be used to calculate the impurity distribution produced by the first pass. A computer program has to be written to handle each subsequent pass.

Spatial information about a system can be obtained by analyzing the spatial distribution of PL intensity. Fluorescent tracers may be used to image chemical uptake in biological systems. Luminescence profiles have proven useftil in the semiconductor industry for mapping impurity distributions, dislocadons, or structural homogeneity in substrate wafers or epilayers. Similar spatial infbrmadon over small regions is obtained by cathodoluminescence imaging. 

It is for these reasons that zone-refining has found limited application, since actual purification by this method does not produce a crystal with a completely uniform impurity distribution. 

Individual size polymers may be used alone or in combination with one another and their performance may be further improved by the addition of other components such as waxes and lubricants. However, whilst sizing offers many benefits in the subsequent weaving of the yarns, it is anathema as far as wet processing is concerned. A typical sized yarn may contain as much as 34% of impurities, distributed as shown in Figure 10.15. These impurities can interfere with wetting-out and with bleaching. They may also affect coloration processes. Depending on the type of size and the dyes used, dye uptake may be increased or resisted ... 

This technique constitutes a good example of high-resolution laser spectroscopy. It has been successfully applied to a variety of systems to examine important aspects, such as the microscopic crystalline structure, the trace impurity distribution, or the degree of structural disorder. 

Impurities distribution in the sintering additions size distribution... 

The availability of inductively coupled plasma mass spectrometry (ICPMS) has provided a method of detection of many impurities at very low concentrations directly in the organometallic compound itself. ICP mass spectrometry is a relatively recently developed chemical analysis technique that is useful in the detection of trace element concentrations in a liquid or solid matrix. ICPMS can measure the presence of almost all elements simultaneously, thus giving a detailed, semiquantitative picture of the impurity distribution in the sample. This technique has sensitivities for many elements in the parts-per-billion to parts-per-trillion range. It has the advantage that it is extremely sensitive and can analyze small samples (10 ml or less) of organometallics directly. The ICPMS technique employs a plasma to dissociate the material to be characterized into... 

This Datareview discusses the redistribution of typical dopant atoms in GaN during the implant activation anneal. Secondary ion mass spectroscopy (SIMS) spectra of the impurity profiles (impurity concentration versus depth into the sample) before (as-implanted) and after annealing are presented. SIMS analysis is the primary method of characterising impurity distributions in semiconductors [2], This information can be used to roughly estimate a diffusivity, D , of the dopant at the temperatures studied by invoking the relationship... 

Unfortunately PIXE does not have any significant depth resolution and thus does not provide any information on the impurity distribution in this dimension. Micro-PIXE data from this tree taken at Ep = 2.5 MeV confirmed the presence of K, Ca, Fe and Cu. This data also showed the presence of Zn and Pb, as well as 20 ppm of Ti at a single point near the center of the tree. 

Theories and instrumentation of Fourier transform IR spectroscopy and electron spectroscopy for chemical analysis are briefly reviewed. The possibility of using these techniques in detection and analysis of acid impurities distributed at surfaces of paper documents produced during the period from 1790 to 1983 is demonstrated. Results show that all of the papers tested contained carboxylic groups. The carboxylic acids found in the paper of 1790 are the results of oxidation and aging. Acids in other papers are due to fiber oxidation as well as the presence of rosin acids. These techniques show promise as nondestructive methods for elucidating chemical characteristics of surfaces of paper documents. 

The two values differ by the impurity distribution coefficient, dangling bonds are the only deep defects which take up donor or acceptor electrons and holes. No other charged gap states of significant density have been found. 

Probably the most apparent result of the low electron density is the decisive role played by impurities in the semiconductor. Impurities in a semiconductor electrode, even at levels as low as 1 part in 10 , can contribute significantly to the space charge, can act as catalysts for the recombination of holes and electrons, or can furnish additional charge-transfer paths for electrochemical reaction. It is essential, therefore, to have control and knowledge of the impurity distribution before any meaningful kinetic measurements can be made on a semiconductor electrode. 

Figure 3. Impurity distribution in type I ores—SSMS data...

As the metal solidifies, impurities that were soluble in the liquid metal become concentrated in the last parts to solidify. This would normally give rise to non-uniform impurity distributions throughout the cast piece. Reservoirs are therefore often incorporated into the casting process to trap the impurities. 

D. J. Silversmith, Nonuniform lateral ionic impurity distributions at Si-Si02 interfaces, J. Electrochem. Soc. 119, 1589, 1972. 

The impurity distribution in the silicon melts and solidified silicon ingot was solved on the basis of solutions of the thermal field and melt flow in a... 

Here 2k 0 and 3are, respectively, the distribution coefficient of i in Si-i binary and Si-i-j ternary systems. Calculated A values for different impurities in pure Si are shown in Fig. 13.23. Most of the common impurities in pure Si have a positive contribution to the impurity distribution coefficient, i.e., the appearance of secondary impurities will increase the distribution coefficient of the primary impurity in silicon. 

Jackie J. (1980), Potential fluctuations in doped semiconductors with random impurity distribution , Phil. Mag. B 41,681-687. 

In the preceding chapters and in the present one, values of the FWHMs of the EM electronic transitions have been considered, either as intrinsic characteristics of the transitions or in connection with the broadening mechanisms which depend on concentration, compensation ratio, or inhomogeneous impurity distribution. In Chaps. 6 and 7, examples of resonant broadening with lattice phonons, which depend on the difference between the phonons and electronic frequencies, have also been given and they are not considered here. The broadening due to the inhomogeneous Stark effect has been discussed in... 

If the impurity distribution is assumed to be uniform the local field, on the average, can be approximated (in the mean polarizability approximation) by... 

The diffusion of impurities into Si wafers typically is done in two steps. In the first step, dopants are implanted into the substrate to a relatively shallow depth of a few thousand angstroms. After the impurities have been introduced into the Si substrate, they are diffused deeper into the substrate to provide a suitable impurity distribution in the substrate. The solid solubility and diffusion of dopant atoms in Si are given in the top and bottom, respectively, of Fig. 9.10. 

In this diagram, we show the actual distribution of impurities in the crystal after it has zone refined by 20 passes. The density of dots represents the concentration of impurities. What has happened is that we have moved many of the impurities from the front to the back, but not all. and we finally end up with an impurity distribution we cannot change. To understand this, we must examine the impurity-leveUng factor in more detail. 

---