Data acquisition and treatment

Computer program, such as MacSimion [100] and its more recent equivalents, can be used to model the ion trajectories in ion optics after various assumptions. From these considerations, it becomes clear that when dealing with several elements any optimization will also lead to compromises. Thus, there will always be a difference in performance in mass spectrometry with respect to sensitivity and to the lowest matrix influences between single-element optimization and compromise conditions. 

In most cases, a linear calibration function can be used, as discussed earlier. It can be calculated by a linear regression with a number of values (c , Xi) where c is the concentration of a standard sample and Xi is the radiation intensity, absorption or ion current obtained for the element to be determined. It has the form  

R is the signal obtained for a reference element, which may be the matrix element, a main constituent or an element added in known concentration to all samples to be analyzed and not present in the sample. This approach is known as internal standardization. It may also happen that the calibration function is not linear, but can be described by a function of the 2nd or even of the 3rd degree. Then it has the form  

The a coefficients have to be calculated using regression procedures. In the case of a calibration function of a higher degree, the calibration graph is curved. The latter can also be approximated by a polygon, where different linear calibration functions are used for well-defined concentration ranges. 

Interferences or matrix effects occur when the analytical signals not only depend on the analyte element concentrations but also on the concentrations of other sample constituents. Additive and multiplicative interferences have to be distinguished. The first may result from spectral interferences. Here, the interference can be corrected for by an estimation of the magnitude of the interfering signal from a scan of the spectral background in the vicinity of the analytical hne. A mathematical interference correction can also be applied. Here, the net analytical signal is calculated as  

In most cases a linear calibration function can be used, as discussed earlier. It 

It could also happen that certain matrix constituents produce signal enhancements or depressions. The latter are known as multiplicative interferences and may be due to influences on the sampling efficiency, on the transport of the analyte into the source and on the generation of the species delivering the analytical signals. They can be written as  

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PECD in Camphor Convergence of the Partial Wave Expansion 1. Data Acquisition and Analysis Molecular Conformation and Substitution Effects 1. Data Acquisition and Treatment... 

PRELIMINARY S. OPERATIONS SIGNAL MEASURING AND TRANSDUCING DATA ACQUISITION AND TREATMENT RESULTS ACCORDING TO SPECIFICATIONS... 

The extent to which surface tension can be controlled by fluoroalkyl-containing coupling agent type treatments is summarized in Table 1. Its purpose is to simply illustrate the range of control possible detailed comparisons are unwarranted because of differences in sample preparation and choice of substrate, data acquisition and treatment. Some of the critical surface tensions (crc) are obtained with -alkanes, some with other liquids. Some of the dispersion force components (of) and polar components (of) of solid surface tension are derived by use of different equations. The reader is referred to the key references in Table 1 for full details. 

EG G PAR (USA), Model 273 A, Potentiostat/Galvanostat volt-ammetric analyzer controlled by PC equipped with a data acquisition and treatment software to record the signal generated in the electrochemical cell for DPY measurements. A 25 mL glass cell at 25°C with the carbon paste biosensor, Ag/AgCl (3.0 mol L-1 KC1) reference electrode, and a platinum wire as auxiliary electrode to perform the volt-ammetric measurements. 

The clear and practical approach adopted by the authors makes the book applicable to a wide audience. It will appeal particularly to those with a practical need (scientists, engineers, managers, research workers) who have completed their formal education but who still need to know efficient ways of carrying out experiments. It is also an ideal text for advanced undergraduate and graduate students following courses In chemometrics, data acquisition and treatment, and design of experiments. 

R. Jenkins and R. L. Snyder, Introduction to X-Ray Powder Diffractometry , John Wiley Sons, New York, 1996, Excellent introductory material, diffraction theory, instrumentation, and data acquisition and treatment. 

J.-J. Meyer, P. Ixvoir, and R. Dubest, Upgrading a rapid-scanning spectrometer with microcompu-terized data acquisition and treatment to measure spectrokinetic parameters of photochromic compounds, Analyst 120, 447-452 (1995) and references therein. 

In a modern diffractometer, data acquisition and treatment are mainly done by computer. To obtain adequate and data of sufficient quality for identifying a material, the following factors are important ... 

Relevant parameters such as the characteristics of the flow cell, type of detector and data acquisition and treatment are briefly presented here. For a further discussion of developments in instrumentation related to the detection unit, overview articles [81—83] are recommended. 

Apparatus. Fig. 1 depicts the schematic diagram of CL flow system used, which consists of a peristaltic pump, a six-way valve and a CR105 photomultiplier tube (Beijing Hamamatsu Photo Techniques Inc.). PTFE tubing (0.8 mm id) was used to connect all components in the flow system. CL data acquisition and treatment were performed using IFFL-D data processing system (Xi an Remex Eletronic Science-Tech Co. Ltd.). 

Inc). Data acquisition and treatment was handled by a MCDR-A multifunction data processing system (Xi an Remax Electronic Science-Tech Co. Ltd, China). 

Type 5. This Involves the automation of data acquisition and treatment in a traditional analytical Instrument —even a balance can be the subject of automation. As shown In Fig. 1.8, a microcomputer connected on-line with the analogue output of the Instrument ensures the automation of this stage of the... 

Fig. 1.8 Automation of the third stage of the analytical process (Type 5 analyser). On-line incorporation of a microcomputer for data acquisition and treatment.

Centrifugal analysers, discussed In Chapter 4, are discrete In nature. Sample collection and reagent dispensation take place In an automated dosing module. However, the transfer disc containing the radially arranged samples and reagents Is transferred manually to the analyser module, where reaction, signal measurement and data acquisition and treatment, all completely automated,... 

Hence, computers allow the ready automation of laboratory processes such as data acquisition and treatment, result delivery and process control. This great potential is further Increased by the possibility of linking computers to one another (intelligent instruments) and by the use of workstations, expert systems and data banks, ail of which are commented on In some detail below. 

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. 

As a rule, all the channels share a common system for data acquisition and treatment which must therefore be capable of discriminating between signals to assign them correctly to their corresponding analytes. Such discrimination can be effected in two ways, namely ... 

Automation In data acquisition and treatment can be aimed at a variety of objectives inherent in the above-mentioned factors. It should be pointed out that physical and physico-chemical kinetic factors play a decisive role in the reduction of human Intervention. The acquisition of data at a high rate imposed by the technique Itself (e.g. picosecond spectroscopy [19]) or by the system Investigated (e.g. meaurements of rates of reactions with half-lives of the order of a few milliseconds by the stopped-flow methodology [20,21]) demand the use of a computerized system without which application of the particular spectroscopic technique or method would not be feasible. On the other hand, the so-called microprocessor-controlled spectroscopy , widely commercialized at present, broadens the scope and facilitates the operator s work by eliminating various sources of error. 

From the point of view of the automation of data acquisition and treatment, spectrometric techniques must be divided Into two large groups according to the manner In which the spectral Information Is generated, which in turn depends on the optical design of the instrument used ... 

Schwlng at al. [7] developed a potentlometric-voltammetrlc system with digital data acquisition and treatment for the kinetic determination of mixtures of metal Ions based on ligand-exchange reactions. The resulte obtained from potentlometrlc measurements are more precise than those found with ampero-metrlc measurements (the typical relative errors are 5% and 5-10, respectively). 

Fig. 15.20 Experimental set-up for determination of ND2 by means of a photodiode system and dispersive spectroscopy with computerized data acquisition and treatment. (Reproduced from [74] wih permission of the Natural Research Council of Canada).

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