Titration rate data analysis

Later work by Farkas and Strohm [121], however, related the catalytic strength of an amine to its F1/2 value, the potential at the halfneutralization point in a potentiometric titration in ethyl acetate. In this analysis a high potential indicates low basicity. The F, y 2 value should be a better measure of the basic strength of the amine as a catalyst for the isocyanate/hydroxyl reaction than pK measures of base strength, since the pK value is obtained in aqueous media. The Fjy2 values do, indeed, correlate well with catalytic effect, and explain the unusual catalytic strength of triethylene diamine, as shown in Table 10. The rate data in this table are for the reaction between phenyl isocyanate and 2-ethyl-hexanol. 

Titrations may be automated using a pump to deliver the titrant at a constant flow rate, and a solenoid valve to control the flow (Figure 9.5). The volume of titrant delivered is determined by multiplying the flow rate by the elapsed time. Automated titrations offer the additional advantage of using a microcomputer for data storage and analysis. 

Composition The law of mass aclion is expressed as a rate in terms of chemical compositions of the participants, so ultimately the variation of composition with time must be found. The composition is determined in terms of a property that is measured by some instrument and cahbrated in terms of composition. Among the measures that have been used are titration, pressure, refractive index, density, chromatography, spectrometry, polarimetry, conduclimetry, absorbance, and magnetic resonance. In some cases the composition may vary linearly with the observed property, but in every case a calibration is needed. Before kinetic analysis is undertaken, the data are converted to composition as a function of time (C, t), or to composition and temperature as functions of time (C, T, t). In a steady CSTR the rate is observed as a function of residence time. 

Data collected for each run included acid analysis using inductively coupled plasma (ICF) to determine cation concentration and titration to determine H concentration. Filtering characteristics were determined using solid and filtrate yield rates, as well as back pressures during the filtration cycle. The filter cake was characterized by moisture content and composition. Solid samples were analyzed with scanning electron microscopy (SEM) to determine changes in particle shape and size under various process conditions, and X-ray diffraction (XRD) was used to determine the solids composition. 

The outcome of many biochemical experiments can be expressed as simple descriptive statements, such as the desired band or peak was observed . In others, such as studies of the rates of processes or the affinity of a ligand for its target, the results need to be given in quantitative form as numerical values of one or more parameters. These quantitative results are derived by mathematical analysis of the raw experimental data. As an example, Figure 8-4 illustrates the time course of an enzymatic reaction. The raw data are the dependence of product concentration (the dependent variable, conventionally shown on the y-axis) on the time (the independent variable, conventionally on the x-axis). Another example is the result of the fluorescence titration of a protein with DNA shown in Figure 7-14. In this case, the independent variable is the concentration ratio of protein/DNA and the dependent variable is the observed fluorescence intensity. 

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