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  • 1
    Electronic Resource
    Electronic Resource
    Amsterdam : Elsevier
    Analytica Chimica Acta 272 (1993), S. 41-51 
    ISSN: 0003-2670
    Keywords: ESCA project ; Expert systems ; Liquid chromatography
    Source: Elsevier Journal Backfiles on ScienceDirect 1907 - 2002
    Topics: Chemistry and Pharmacology
    Type of Medium: Electronic Resource
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  • 2
    ISSN: 0021-9673
    Source: Elsevier Journal Backfiles on ScienceDirect 1907 - 2002
    Topics: Chemistry and Pharmacology
    Type of Medium: Electronic Resource
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  • 3
    Electronic Resource
    Electronic Resource
    Amsterdam : Elsevier
    Journal of Chromatography A 505 (1990), S. 1 
    ISSN: 0021-9673
    Source: Elsevier Journal Backfiles on ScienceDirect 1907 - 2002
    Topics: Chemistry and Pharmacology
    Type of Medium: Electronic Resource
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  • 4
    Electronic Resource
    Electronic Resource
    Amsterdam : Elsevier
    TrAC Trends in Analytical Chemistry 8 (1989), S. 350-352 
    ISSN: 0165-9936
    Source: Elsevier Journal Backfiles on ScienceDirect 1907 - 2002
    Topics: Chemistry and Pharmacology
    Type of Medium: Electronic Resource
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  • 5
    Electronic Resource
    Electronic Resource
    Amsterdam : Elsevier
    Chemometrics and Intelligent Laboratory Systems 18 (1993), S. 27-39 
    ISSN: 0169-7439
    Source: Elsevier Journal Backfiles on ScienceDirect 1907 - 2002
    Topics: Chemistry and Pharmacology
    Type of Medium: Electronic Resource
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  • 6
    Electronic Resource
    Electronic Resource
    Springer
    Chromatographia 15 (1982), S. 205-214 
    ISSN: 1612-1112
    Keywords: Solubility parameter ; Theory of liquid chromatography ; Retention ; Selectivity ; Specific effects
    Source: Springer Online Journal Archives 1860-2000
    Topics: Chemistry and Pharmacology
    Notes: Summary The solubility parameter concept is briefly discussed. It is then used to explain some of the current features of liquid partition and adsorption chromatography. Various phase systems are discussed on the basis of three characteristics.retention, selectivity (the general separation power of a system) andspecificity (increased separation power towards certain pairs of solutes). The emergence of two essentially different techniques, the ‘normal phase’ and ‘reversed phase’ modes, will appear as a logical consequence of simplified theory. It also becomes obvious why ‘reversed phase’ applications are so much more numerous. Some suggestions are given for the development of new stationary phases and the improvement of existing ones. The usefulness of the solubility parameter concept to predict the solvent strength of mixed eluents in reversed phase liquid chromatography (RPLC) is demonstrated. Some practical rules for the selection and operation of stationary and mobile phase systems are formulated.
    Type of Medium: Electronic Resource
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  • 7
    ISSN: 1612-1112
    Keywords: Column liquid chromatography ; Reverse phase ; Optimization
    Source: Springer Online Journal Archives 1860-2000
    Topics: Chemistry and Pharmacology
    Notes: Summary An interpretive optimization procedure in which pH can be one of the variables is presented with the emphasis on optimizing separations. When varying the pH in reversed-phase liquid chromatography the retention of ionogenic solutes will change. Thus, the selectivity between ionogenic and neutral solutes or between ionogenic solutes mutually can be optimized. However, pH also greatly affects the efficiency (plate count) and peak shape (asymmetry). Optimum selectivity (i.e. large differences in retention times) may be observed under conditions where peaks are broad and asymmetrical. Thus, it is essential to simultaneously consider retention, peak width and peak shape and their effects on separation (effective resolution) in pH-optimization studies. A procedure in which this is done is presented and applied to optimizing the separation of a synthetic mixture of selected pharmaceuticals. After initial experiments to establish the parameter space (boundaries for pH and binary methanol — water composition), twelve experiments are performed according to a 3×4 experimental design. At each loaction the retention, peak height, peak area and peak symmetry are recorded for each solute. These data are then used to build models for each of the four characteristics and for each solute. From this set of models the response surface, describing the quality of separation as a function of pH and composition, can be calculated. A variety of optimization criteria (quantifying quality of separation) can be used. The optimum corresponds to the highest point on the response surface.
    Type of Medium: Electronic Resource
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  • 8
    Electronic Resource
    Electronic Resource
    Springer
    Chromatographia 25 (1988), S. 737-748 
    ISSN: 1612-1112
    Keywords: Method development ; System selection and optimization ; Selectivity optimization ; Method validation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Chemistry and Pharmacology
    Notes: Summary This paper provides an overview of method development in liquid chromatography. It is explained why every practicing chromatographer needs to understand the process of method development. Thus, this paper is directed towards chromatographers who develop new separation methods, as well as to those who apply published methods. The method-development process is first explained in broad terms, after which the different aspects of the process are described in more detail. First, attention is paid to the initial stages of method development, which consist of the accurate definition of the separation problem and the selection of the most suitable chromatographic method. Method-development expert systems are discussed with regards to their applicability in this area. Selectivity optimization is shown to rely on three main factors,i. e. the selection of the parameter space, the experimental design and the optimization criterion. Selectivity-optimization procedures are described very briefly. System optimization concerns those factors which do not affect the chemistry of the system (mobile and stationary phase), but are essentially determining the analysis time and the sensitivity. The method-validation stage can be divided into three main parts: qualitative method validation (i.e. peak integrity and identity), calibration and quantitative method validation. The requirements of calibration procedures are briefly reviewed and an inventory of method-validation procedures is presented.
    Type of Medium: Electronic Resource
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  • 9
    ISSN: 1612-1112
    Keywords: High-performance liquid chromatography ; Expert systems ; System selection and optimisation ; Application to pharmaceutical analysis ; Selectivity optimisation ; Method validation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Chemistry and Pharmacology
    Notes: Summary This paper gives an overview of the structure and processes going on in the project Expert Systems for Chemical Analysis (ESCA), an international project within the ESPRIT research programme of the European Community. The application area, HPLC method development, is explained and broken down into four domains. The methods used for representing knowledge in the project are discussed.
    Type of Medium: Electronic Resource
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  • 10
    ISSN: 1612-1112
    Keywords: Column liquid chromatography ; Retention models ; Method development ; pH optimization
    Source: Springer Online Journal Archives 1860-2000
    Topics: Chemistry and Pharmacology
    Notes: Summary In this work we establish the basic layout of IONICS, an expert system for optimizing the separation of ionogenic solutes in Reversed-Phase Liquid Chromatography, using the pH and the organic-modifier concentration of the mobile phase as parameters. We also present REMO, a front-end system that automates the retention modelling stage, based on a 9-parameter model. This system uses a scale transformation to suppress several numerical problems previously observed and features a strategy for automatic calculation of an initial approximation to the model optimum. The successful application of this system to a set of seven drugs is described. The final models are accurate and have smaller numerical problems. We also describe the use of a genetic algorithm instead of classical non-linear least-squares for fitting the model to the experimental data. Results indicate that genetic algorithms are a valuable, complementary tool for retention modelling.
    Type of Medium: Electronic Resource
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