Stages in the Analytical Process

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 

In the present time with almost unlimited computer facilities in the analytical laboratory, analytical chemists should be able to obtain substantial benefits from the application of time series, information theory, multivariate statistics, a.o. factor analysis and pattern recognition, operations research, numerical analysis, linear algebra, computer science, artificial intelligence, etc. This is in fact what chemo-metricians have been doing for the past decades. 

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Ideally both the control materials and those used to create the calibration should be traceable to appropriate certified reference materials or a recognised empirical reference method. When this is not possible, control materials should be traceable at least to a material of guaranteed purity or other well characterised material. However, the two paths of traceability must not become coincident at too late a stage in the analytical process. For instance, if control materials and calibration standards were prepared from a single stock solution of analyte, IQC would not detect any inaccuracy stemming from the incorrect preparation of the stock solution. 

There are a number of difficulties encountered with quantification after employing derivatization. These include the fact that we are now considering another analytical step, with the concomitent increase in cost and time of each analysis. In addition, because derivatization is another handling stage in the analytical process, there is always the risk of sample contamination. Furthermore, the assumption is made that the derivatization reactions are complete and that the corresponding derivatives are stable for the period between derivative formation and analysis. Further factors are that dilutions need to be extremely accurate and precise to obtain reliable numerical data and that derivatization can potentially lead to increases in numerical errors for such data. 

Positive-liquid-displacement pipettes are used for specimen handling in most discrete automated systems. With them, specimens, calibrators, and controls are delivered by a single pipette to the next stage in the analytical process. 

The second category of discrete automatic analyzers consists of those machines in which transfers of the samples from one stage in the analytical process to the next do not require the intervention of the operator. Examples in this class currently available are the Robot Chemist (Warner-Chilcott Laboratories, Instruments Division, Richmond, Calif.)... 

The final stage in the analytical process is to measure the concentration of the environmental pollutant. This chapter has described appropriate techniques for the measurement of both metals and organic compounds. While the primary descriptions have focused on atomic spectroscopy for metals and chromatography for organic compounds, some related techniques have been discussed briefly. 

In situations where the analyte is present in trace quantities (as usually occurs in environmental samples), it is vitally important to maximize the recovery of the analyte from the sample matrix and to lose as little of the analyte as possible during any subsequent processing or work-up stages in the analytical process. Extensive recovery testing is usually required to determine the efficiency of the collection and processing procedures. 

The methods used for testing at various stages in the manufacturing process must be validated to show that they are fit for their intended application. For example, a method may be capable of measuring an analyte to a high of degree of accuracy and... 

In the following, the stages of the analytical process will be dealt with in some detail, viz. sampling principles, sample preparation, principles of analytical measurement, and analytical evaluation. Because of their significance, the stages signal generation, calibration, statistical evaluation, and data interpretation will be treated in separate chapters. 

Automatization of all stages of the analytical process is a trend that can be discerned in the development of modern analytical methods for chemical manufacture, to various extents depending on reliability and cost-benefit considerations. Among the elements of reliability one counts conformity of the accuracy and precision of the method to the specifications of the manufacturing process, stability of the analytical system and closeness to real-time analysis. The latter is a requirement for feedback into automatic process-control systems. Since the investment in equipment for automatic online analysis may be high, this is frequently replaced by monitoring a property that is easy and inexpensive to measure and correlating that property with the analyte of interest. Such compromise is usually accompanied by a collection of samples that are sent to the analytical laboratory for determination, possibly at a lower cost. 

Moreover, such conventional off-line approaches often result in the reisolation ( replication ) of already known compounds. Here, LC-NMR offers an unique insight into the composition of mixtures at an early stage of the analytical process for identifying ( dereplicating ) unwanted or already known compounds and thus guide the targeted isolation of potentially new substances. 

In Fig. 2a, we see that a 7.5 kDa peptide purified by reversed-phase HPLC shows several peaks by CE, indicating that at this stage in the purification process, the sample is not pure. Further fractionation by cation-exchange HPLC yielded a much purer sample, as shown in Fig. 2c. However, this sample shows a minor component just before the main component the same component is seen after the main component by cation-exchange HPLC. This is explained by the fact that positively charged analyte appears first in the electropherogram, whereas, the same peak would elute last from a... 

Type 2. This Involves partial automation of the first stage of the analytical process the accurate measurement of a sample volume (sampling) and Its transport to the detector without human Intervention. However, sample treatment (e.g. dissolution) and the analytical reaction development —if required— are carried out manually. Figure 1.6 shows, a representative example the incorporation of an automatic sampler In a thermal-vaporization atomic absorption spectrometer. This instrumental configuration is representative of those where the automation of one stage Is highly recommendable —in this Instance to ensure reproducible results. 

Type 3. The Implementation of all the preliminary operations in the analytical process without human Intervention represents a remarkable degree of automation. By Incorporating a sampler In ordinary FIA assemblies or the classical AutoAnalyzers, the first stage of the analytical process could be regarded as automated. However, It should be noted that the sampler holds pre-treated samples, so that the automation of the first stage Is only apparently complete. 

Fig. 1.7 Automation of the second stage of the analytical process (Type 4 analyser). Use of a microprocessor incorporated in a molecular absorption spectrometer to control its functioning through an active interface and an analogue-to-digital converter.

Fig. 1.9 Automation of the first and third stages of the analytical process (Type 5 analyser). Scheme of automatic continuous analyser for determination of pollutants in waste water, based on a reversed FIA configuration. (Reproduced with permission of the copyright holders).

As stated In Chapter 1, the first few stages of the analytical process are also the more complex and the source of potential major errors, and the concept of a sample is rather extensive. 

The automation of preliminary operations in the analytical process Is rendered particularly difficult by (a) the large variety of existing samples, available in all three states of aggregation (solid, liquid and gas) and In different particle sizes, (b) the diversity of circumstances (sampling location and distance to the laboratory, need for preservation) and (c) the pretreatment required (dissolution, preconcentration, interference removal, etc.). All this makes the first stage of the analytical process one that cannot be automated In every case In fact, endeavours In this field are often aimed at a particular type of sample or application (e.g. clinical, food, agricultural or pharmaceutical analysis). 

The problem of the state of aggregation of the sample is a major consideration in the automation of the preliminary stages of the analytical process however, it has been tackled only rarely, probably because of the technical difficulties involved. Problems such as the potentially different compositions... 

The transient signals provided by the detectors were formerly registered with a strip-chart recorder, which required human participation in the final stage of the analytical process the operator had to measure signals, contrast samples with standards and match samples and results. The later use of microcomputers for data acquisition and treatment allows the easy delivery of results, expressed in the preselected units, through a printer. Technicon market hardware and software suited to their simpler AutoAnalyzers, which can also be adapted for this purpose with the interesting innovations reported recently [22-25]. Multi-channel models (e.g. SMAC) feature a built-in central computer which, in addition to serving this function, controls the analyser operation. 

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