Defining the analytical problem

The full analytical procedure starts with formulation of the analytical problem (Fig.3). However a chemical analysis is never an end in itself. An external need defines the analytical problem and external expertise should participate in assessment and utilization. 

When the analyst has properly defined the analytical problem to be solved (see Chapter 1), he has to select an adapted analytical procedure. The selection and the development of the procedure will be based on the investigation of the scientific literature and on the experience of the analyst and of colleagues. The general equipment of the laboratory and the scope of its activity will also influence the choice of method and the selected approach. Several books deal with the most important methods applied by analytical chemists. Examples of their application are given and the reader should refer to them. A basic book, mainly foreseen for students in analytical chemistry, but also very valuable for senior analysts, has been published recently by Kellner et al. [18]. 

Define the analytical approach, such as the material and the analytes to be looked for so as to (possibly) answer the questions asked and to solve the problems. Select an appropriate analytical method, with definition of its purpose and utility. If none of the available methods fits the analytical purpose, try to deduce method approach(es) from existing methods for structurally related compounds or materials by introducing carefully selected modifications and adaptations. 

Despite the large amount of different analytical procedures, a regularily returning pattern of activities can be discovered in chemical analysis. This pattern of activities can be considered to define the analytical process. In the previous section it was explained that the analytical system, which consists of a sample input and result output (Fig. 2) represents only a part of the total analytical process. The sample is the result of several actions after the receipt of the customers chemical problem. The obtained analytical result, however, still needs to be converted into information. Therefore, the analytical process is better describe as a cycle, which logins with the formulation of the problem that needs a solution by chemical analysis and is finished after... 

The term chemical measurement can cover all these determinations, including identification [6], Identification defines the so called analyte by means of chemical, electrochemical, spectroscopical and other physical properties. In most cases identification is done by measurements. Identification is valid only in a reference system. The terms describing the analytical problem (see Fig. 4), the measuring system used, the reference methods and the reference materials, belong together as the reference system. 

This is the place to start, since most often, analytical chemists are trying to help solve someone else s problem. We need to define the solute and its matrix as well as the nature of the analytical problem. For example, in the world of pharmaceuticals, there are raw material identification and purity determinations, in-process testing, dosage-form determinations, content uniformity, dissolution testing, stability studies, bioavailability, pharmacokinetics, and drug metabolism, to name a few. Each of these analytical problems has its own specific requirements. The matrix can be a raw material, granulation, tablet, capsule, solution, lotion, cream, syrup, dissolution medium, blood serum, urine, or various body tissues and fluids. Similar definitions can be described for virtually any industrial area and problem set. These definitions will help select sample preparation, separation, and detection techniques. 

The process taking place during the thermal pretreatment (ashing) and atomization stages must be known in order to solve the analytical problem with high precision and accuracy. The chemical and physical characteristics of the analyte will determine its behaviour in the furnace. Chemical environment (matrix) of the analyte is also very important. It is possible to predict whether a given element can be determined in a particular matrix and to define the best operating conditions. 

To select an analytical method intelligently, it is essential to define clearly the nature of the analytical problem. Such a definition requires answers to the following questions ... 

It is inportant to define the correct problem, or to determine whether one even exists. One common situation is false identification of a problem or synptom. An instrument could have been read incorrectly or could be broken, the analytical analysis (online or in lab) may not be correct, reagents may have been prepared incorrectly, and so on. In this situation, there is no problem with the process it is a false indication of a problem. Never accept the initial problem identification without verification. 

Laplace transform, it also contains the value of Cb (0), i.e. the initial condition for solving the problem. After that, the form laplace ( Cb (t), t, s) is replaced with the variable LB and the resulting algebraic equation is solved for this variable. Next, the operator solution is subjected to the inverse Laplace transform (the operator invlaplace, s). The final expression defines the analytical form of the function Cb (t). 

There is a general criterion that defines what constitutes a proper choice of cell thickness. If one is dogmatic about it, then the cell thickness should be chosen such that the strongest band in the spectrum has a transmission between 1 and 5%. That is a reasonable rule, particularly for reference spectra, but there are exceptions to it. A far better generalization is to use the thickness that gives you the information you want from the sample. On the other hand, if quantitative work is to be done, the thickness should be chosen such that the transmission of the analytical band is roughly between 20 and 80%. Thus, there are several factors that dictate cell thickness and the decision should be a pragmatic one—use a thickness that corresponds to the analytical problem. 

Beeler defined the broad scope of computer experiments as follows Any conceptual model whose definition can be represented as a unique branching sequence of arithmetical and logical decision steps can be analysed in a computer experiment... The utility of the computer... springs mainly from its computational speed. But that utility goes further as Beeler says, conventional analytical treatments of many-body aspects of materials problems run into awkward mathematical problems computer experiments bypass these problems. 

Analytical solutions for the closure problem in particular unit cells made of two concentric circles have been developed by Chang [68,69] and extended by Hadden et al. [145], In order to use the solution of the potential equation in the determination of the effective transport parameters for the species continuity equation, the deviations of the potential in the unit cell, defined by... 

Once the target number of samples was defined, the frequency of collection and the number of samples to be collected on each collection date were determined, based on an overall total sampling period of 1 year. The sampling plan specified collection every other week, primarily to accommodate the workload at the analytical laboratories. Sampling had to occur early in the week to preclude problems with shipping samples over the weekend. With these considerations in place, specific dates for collection of commodity samples could readily be set. 

The analytical response generated by an immunoassay is caused by the interaction of the analyte with the antibody. Although immunoassays have greater specificity than many other analytical procedures, they are also subject to significant interference problems. Interference is defined as any alteration in the assay signal different from the signal produced by the assay under standard conditions. Specific (cross-reactivity) and nonspecific (matrix) interferences may be major sources of immunoassay error and should be controlled to the greatest extent possible. Because of their different impacts on analyses, different approaches to minimize matrix effects and antibody cross-reactivity will be discussed separately. 

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