Model kinetic processes iron

Fe(III) displacement of Al(III), Ga(III), or In(III) from their respective complexes with these tripodal ligands, have been determined. The M(III)-by-Fe(III) displacement processes are controlled by the ease of dissociation of Al(III), Ga(III), or In(III) Fe(III) may in turn be displaced from these complexes by edta (removal from the two non-equivalent sites gives rise to an appropriate kinetic pattern) (343). Kinetics and mechanism of a catalytic chloride ion effect on the dissociation of model siderophore-hydroxamate iron(III) complexes chloride and, to lesser extents, bromide and nitrate, catalyze ligand dissociation through transient coordination of the added anion to the iron (344). A catechol derivative of desferrioxamine has been found to remove iron from transferrin about 100 times faster than desferrioxamine itself it forms a significantly more stable product with Fe3+ (345). 

An interesting aspect of kinetics is tha question of how species interact when multiple extraction inactions occur. Most extractants are not perfectly selective and are capable of extracting several species from a multicomponent equeous solution. Complete equilibrium models should indicate extraction selectivity for a given system at equilibrium, but selectivity may vary considerably in a nonequilibrium process because of rate differences. In fact, iron(UI) can be extracted by some of the copper-chelating extractants, but their effective selectivity for copper is based on the very slow kinetics of iron extraction. 

Kinetic experiments with synthetic iron oxyhydroxides have shown that the initial microbial reduction rate increases with increasing initial ferric iron concentration up to a given maximum reduction rate (Bonneville et al. 2004). This observation was explained by a saturation of active membrane sites with Fe(III) centers. The respective reaction was best described with a Michaelis-Menten rate expression with the maximum reduction rate per cell positively correlating with the solubility of the iron oxyhydroxides (Bonneville et al. 2004). Kinetic studies involving iron are not only inherently important to describe reaction pathways and to derive rate constants, which can be used in models. Kinetic studies also increasingly focus on iron isotopic fractionation to better understand the iron isotopic composition of ancient sediments, which may assist in the reconstruction of paleo-environments. Importantly, iron isotope fractionation occurs in abiotic and biotic processes the degree of isotopic fractionation depends on individual reaction rates and the environmental conditions, e.g. whether reactions take place within an open or closed system (Johnson et al. 2004). 

Summarizing, dynamical effects may be theoretically observed in such nanocomposites, despite the fact that these phenomena are impossible to understand from thermodynamic criteria, assuming chemical equilibrium. This section merely serves to emphasize that, clearly, such kinetic processes can only be properly dealt with if time plays an explicit role in the modelling of the system, to be accomplished by molecular-dynamics simulations. The reaction phenomenon found here appears to arise both from the drastic synthetic conditions as well as from the preference of nitrogen to be three-dimensionally bonded to the iron host. The numerical analysis of such dynamical processes will certainly gain importance in the coming years. 

Mukherjee studied the gas phase equilibria and the kinetics of the possible chemical reactions in the pack-chromising of iron by the iodide process. One conclusion was that iodine-etching of the iron preceded chromis-ing also, not unexpectedly, the initial rate of chromising was controlled by transport of chromium iodide. Neiri and Vandenbulcke calculated, for the Al-Ni-Cr-Fe system, the partial pressures of chlorides and mixed chlorides in equilibrium with various alloys and phases, and so developed for pack aluminising a model of gaseous transport, solid-state transport, and equilibria at interfaces. 

Klupinski et al. (2004) conclude that the reduction of nitroaromatic compounds is a surface-mediated process and suggest that, with lack of an iron mineral, reductive transformation induced only by Fe(II) does not occur. However, when C Cl NO degradation was investigated in reaction media containing Fe(II) with no mineral phase added, a slow reductive transformation of the contaminant was observed. Because the loss of C Cl NO in this case was not described by a first-order kinetic model, as in the case of high concentration of Fe(II), but better by a zero-order kinetic description, Klupinski et al. (2004) suggest that degradation in these systems in fact is a surface-mediated reaction. They note that, in the reaction system, trace amounts of oxidize Fe(II), which form in situ suspended iron oxide... 

The sharp iron profiles in Fig. 38 are thought to be due to deposits from rust and scale, not to organometallic compounds. Their removal likely occurs by a sieving process and thus delineates the edge of the pellet. The Ni and V internal maxima cannot be predicted by simple first- or second-order reaction kinetics. Rather, these profiles are a consequence of the consecutive HDM mechanism involving metal deposition from an intermediate not originally in the oil. This mechanism has been demonstrated in model oil systems (Section IV, A, 4) and now has evidence with real oils. 

A general kinetic model should accommodate all chemical processes known to affect the dechlorination process. These include (1) reductive dechlorination takes place on the iron surface, rather than in the aqueous phase, so adsorption must occur (2) other components in the system may affect the dechlorination reaction by competing for the reaction sites (3) surface sites for reduction and for sorption may not be the same, as for the system with PCE and TCE where dechlorination takes place on the reactive sites, but most of the adsorption is clearly on the nonreactive sites (Burris et al., 1995). In the following section we will first discuss a single-site model similar to the one used by Johnson et al. (1998), which has accounted for the first two observations, then develop a two-site model that will also take the third observation into consideration. We aim to illustrate how coadsorbates in the iron system will affect adsorption and reduction of chlorinated solvents. TCE will be used as an example since relevant adsorption and reduction data are available, from which the required parameters for simulation could be estimated. 

Synthetic iron porphyrin complexes such as Fe(TPP) (tetraphenylporphyrin = TPP), Fe(TMP) (Tetramesitylporphyrin = TMP), and Fe(TDCPP) (tetrakis (dichlorophenyl)porphyrin = TDCPP) (Fig. 9) have been used as models for P450 and peroxidase (9, 50-54). Early pioneering work showed that epoxida-tion catalyzed by Feln(TPP) was successfully carried out by the use of iodosylbenzene (Ph—1=0) as an oxidant (50). A very interesting feature of this model epoxidation is that the cis olefin is readily oxidized while the trans olefin is hardly oxidized (e.g., d.v-stylbene can be oxidized in 80% yield, but fraws-stylbene gave only a trace amount of the epoxide under the same conditions) (50, 55). Most of the model reactions are carried out in homogeneous organic solvents such as chloroform, dichloromethane, and acetonitrile, thus, the c/.v-epoxidation is expected to be a kinetically favorable process over the trans-epoxidation. 

BIOPLUME III is a public domain transport code that is based on the MOC (and, therefore, is 2-D). The code was developed to simulate the natural attenuation of a hydrocarbon contaminant under both aerobic and anaerobic conditions. Hydrocarbon degradation is assumed due to biologically mediated redox reactions, with the hydrocarbon as the electron donor, and oxygen, nitrate, ferric iron, sulfate, and carbon dioxide, sequentially, as the electron acceptors. Biodegradation kinetics can be modeled as either a first-order, instantaneous, or Monod process. Like the MOC upon which it is based, BIOPLUME III also models advection, dispersion, and linear equilibrium sorption [67]. 

An autocatalytic process is thus established in which the rate of dissolution is found to increase with time. Litter et al. [131] examined this autocatalytic process in more detail using maghemite (y-Fe203)-EDTA systems and developed a kinetic model of the process which satisfactorily described the results obtained. Consistent with the proposed process, addition of soluble ferric iron increased dissolution rates. 

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