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Kinetic analysis specific rate

Measurements of overall reaction rates (of product formation or of reactant consumption) do not necessarily provide sufficient information to describe completely and unambiguously the kinetics of the constituent steps of a composite rate process. A nucleation and growth reaction, for example, is composed of the interlinked but distinct and different changes which lead to the initial generation and to the subsequent advance of the reaction interface. Quantitative kinetic analysis of yield—time data does not always lead to a unique reaction model but, in favourable systems, the rate parameters, considered with reference to quantitative microscopic measurements, can be identified with specific nucleation and growth steps. Microscopic examinations provide positive evidence for interpretation of shapes of fractional decomposition (a)—time curves. In reactions of solids, it is often convenient to consider separately the geometry of interface development and the chemical changes which occur within that zone of locally enhanced reactivity. [Pg.17]

A considerable improvement over purely graph-based approaches is the analysis of metabolic networks in terms of their stoichiometric matrix. Stoichiometric analysis has a long history in chemical and biochemical sciences [59 62], considerably pre-dating the recent interest in the topology of large-scale cellular networks. In particular, the stoichiometry of a metabolic network is often available, even when detailed information about kinetic parameters or rate equations is lacking. Exploiting the flux balance equation, stoichiometric analysis makes explicit use of the specific structural properties of metabolic networks and allows us to put constraints on the functional capabilities of metabolic networks [61,63 69]. [Pg.114]

Respiration inhibition kinetics analysis (RIKA) involves the measurement of the effect of toxicants on the kinetics of biogenic substrate (e.g., butyric acid) removal by activated sludge microorganisms. The kinetic parameters studied are max> the maximum specific substrate removal rate (determined indirectly by measuring the maximum respiration rate), and Ks, the half-saturation coefficient [19]. The procedure consists of measuring with a respirometer the Monod kinetic parameters, Vinax and Ks, in the absence and in the presence of various concentrations of the inhibitory compound. [Pg.22]

Kinetic analysis of a step polymerization becomes complicated when all functional groups in a reactant do not have the same reactivity. Consider the polymerization of A—A with B—B where the reactivities of the two functional groups in the B—B reactant are initially of different reactivities and, further, the reactivities of B and B each change on reaction of the other group. Even if the reactivities of the two functional groups in the A—A reactant are the same and independent of whether either group has reacted, the polymerization still involves four different rate constants. Any specific-sized polymer species larger than dimer is formed by two simultaneous routes. For example, the trimer A—AB—B A—A is formed by... [Pg.57]

Equation (25) is general in that it does not depend on the electrochemical method employed to obtain the i-E data. Moreover, unlike conventional electrochemical methods such as cyclic or linear scan voltammetry, all of the experimental i-E data are used in kinetic analysis (as opposed to using limited information such as the peak potentials and half-widths when using cyclic voltammetry). Finally, and of particular importance, the convolution analysis has the great advantage that the heterogeneous ET kinetics can be analyzed without the need of defining a priori the ET rate law. By contrast, in conventional voltammetric analyses, a specific ET rate law (as a rule, the Butler-Volmer rate law) must be used to extract the relevant kinetic information. [Pg.99]

The various k s are the rate constants for the specific reactions shown. Standard kinetic analysis of this mechanism predicts that the rate of product formation is given by... [Pg.380]

S.S. Cherry et al, Identification of Important Chemical Reactions in Liquid Propellant Rocket Engines , Pyrodynamics 6 (3—4), 275—96 (1969) CA 70,. 98394 (1969) [The authors state that the kinetics of nonequilibrium expansion of the propint system N204/A-50 (UDMH 49 plus hydrazine 51 wt%) can be described by the following gas phase reactions with an accuracy such that not more than 0.5 lb force-sec/lb mass variation in specific impulse (at a nozzle expansion rate of 40) is produced, as compared to the results of a full kinetic analysis ... [Pg.23]

The above example gives us an idea of the difficulties in stating a rigorous kinetic model for the free-radical polymerization of formulations containing polyfunctional monomers. An example of efforts to introduce a mechanistic analysis for this kind of reaction, is the case of (meth)acrylate polymerizations, where Bowman and Peppas (1991) coupled free-volume derived expressions for diffusion-controlled kp and kt values to expressions describing the time-dependent evolution of the free volume. Further work expanded this initial analysis to take into account different possible elemental steps of the kinetic scheme (Anseth and Bowman, 1992/93 Kurdikar and Peppas, 1994 Scott and Peppas, 1999). The analysis of these mechanistic models is beyond our scope. Instead, one example of models that capture the main concepts of a rigorous description, but include phenomenological equations to account for the variation of specific rate constants with conversion, will be discussed. [Pg.168]

As most NRPS multienzymes are multidomain proteins with multiple activation domains, multiple sites may participate in the reactions assayed, and no clear result concerning a single specific site may result. In ACV synthetases, the nonadditivity of the initial rates has been observed in the S. clavuligerus enzyme [35] and the A. chrysogenum enzyme [1]. Two or more site activations of one substrate amino acid could be expected to depend on different binding constants, and thus be detectable by kinetic analysis. So far, however, no evidence for mixed types of concentration dependence has been found. It is thus not yet clear if nonadditivity results from misactivation or alteration of kinetic properties in the presence of multiple substrates. In the case of gramicidin S synthetase 2, evidence for misactivations has been reported [59],... [Pg.14]

The identification of phenomena that explain the behavior of a studied system depends on the analysis of their kinetic data. Normally, this kinetic analysis is performed using characteristic variables calculated from the experimental data. The specific rates and the yield coefficients are the common values used in this task. When cell concentration data are available, cell growth and death rates, as well as cell viability, are the best kinetic variables to characterize the population physiological state. In the absence of this information - as can occur, for example, with immobilized cells - the treatment must be based on substrate consumption or on metabolites production (Miller and Reddy, 1998). [Pg.186]

There are other ways to identify the factors that regulate cell metabolism, and each researcher may establish suitable methods for a particular system based on kinetic data analysis (Sinclair and Kristiansen, 1987 Engasser et al., 1998 Bonomi and Schmidell, 2001). Nevertheless, the importance of adequate experimental data treatment is evident. This would allow precise specific rate calculations and identification of the associated phenomena. [Pg.192]

Figure 3-16 is helpful in the logical planning of a series of kinetic experiments to determine reaction orders and specific rate constants. However, it is important to remember the main goals and design of the entire experimental analysis. Table 3-5 gives methods used to determine direct or indirect measurements of a species concentration. [Pg.165]

As for deaminase, the kinetic analysis suggests a partial mixed-type inhibition mechanism. Both the Ki value of the inhibitor and the breakdown rate of the enzyme-substrate-inhibitor complex are dependent on the chain length of the PolyP, thus suggesting that the breakdown rate of the enzyme-substrate-inhibitor complex is regulated by the binding of Polyphosphate to a specific inhibitory site (Yoshino and Murakami, 1988). More complicated interactions were observed between PolyP and two oxidases, i.e. spermidine oxidase of soybeen seedling and bovine serum amine oxidase. PolyP competitively inhibits the activities of both enzymes, but may serve as an regulator because the amino oxydases are also active with the polyamine-PolyP complexes (Di Paolo et al., 1995). [Pg.106]

The solution for specific cases is greatly simplified when one of the reactions (87) or (88) is much slower than the other and thus controls the initiation rate. [In radical polymerizations, this is usually reaction (87).] We know, of course, that reaction (87) can be reversible, that R° can decay by secondary decomposition to R j (the reactivity of which generally differs from that of R°), and both reactions can only be a part of a much more complicated set of interactions, especially in ionic and coordination polymerizations. An exact kinetic analysis must be based on a proved scheme with identified intermediate transition states and products, and a knowledge of the rate constants and of the rates of various initiation stages. Such a complete and complex analysis does not yet exist. [Pg.153]

Instrumental. The Mettler TA2000B thermal analysis system is equipped with an interface system, and Hewlett-Packard 9815 desk top calculator and 7225 plotter. Samples, weighing 5-10 mg, sealed in aluminum pans and under a nitrogen blanket, were heated in the calorimeter at a rate of 10 deg/min from -35 or 10 deg C to 180 deg C respectively, for specific heat and kinetic scans. Specific heat measurements were calibrated with alumina to an accuracy of 3%. Temperatures and enthalpies were calibrated with an Indium sample. The accuracies were .02 deg C and 2% (Indium 28.5 J/g), respectively. [Pg.314]

A fundamental requirement for any correlation is that a qualitatively constant mechanism exists. For example, in kinetic studies, the rate determining step must be the same for all molecules, and more importantly, the transition state for the reaction for all molecules must be of the same type. The same demand of biological data means that, for example, the drugs bind to the same receptor through the same types of interactions. An apparent lack of correlation may be due to the fact that more than one mechanism can bring about the same effect. The analysis of the deviations could identify differences in mechanism within a series of compounds or differences in the effects of substituents on the reactivity of specific compounds in this series. [Pg.45]

Giovanoli and Brutsch [37] emphasize the necessity for supplementing thermoanalytical kinetic data for the dehydration of y-FeOOH yFcjOj) with diffraction and electron microscopy studies. The deceleratory rate process can be described by either the first- order, or various diffusion-controlled expressions and thus a specific reaction model does not result from this kinetic analysis. Values of... [Pg.279]

Theory and kinetic analysis (38 entries). Many aspects of the theory of kinetic analysis were discussed (27 entries). Some papers were specifically concerned with discrimination of fit of data between alternative kinetic expressions or with constant reaction rate thermal analysis. Other articles (11 entries) were concerned with aspects of the fundamental theory of the subject and with the compensation effect. The content of papers concerned with kinetic analyses appeared to accept the common basis of the applicability of the rate equations listed in Table 3.3. [Pg.551]

State may be incorrect in complex rate processes where there is reactant melting, (iii) Commercial software for kinetic analysis sometimes restricts coverage to reaction orders, and the wider range of rate equations (Table 3.3.) is simply not considered, (iv) Some specific reaction models have the same form as reaction orders. For example, random nucleation within a large number of small crystals can be regarded as formally identical with a first-order reaction. [Pg.569]


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