Reaction-diffusion dynamics

This example involves the same diffusion-reaction situation as in the previous example, ENZSPLIT, except that here a dynamic solution is obtained, using the method of finite differencing. The substrate concentration profile in the porous biocatalyst is shown in Fig. 5.252. 

We focus on the effects of crowding on small molecule reactive dynamics and consider again the irreversible catalytic reaction A + C B + C asin the previous subsection, except now a volume fraction < )0 of the total volume is occupied by obstacles (see Fig. 20). The A and B particles diffuse in this crowded environment before encountering the catalytic sphere where reaction takes place. Crowding influences both the diffusion and reaction dynamics, leading to nontrivial volume fraction dependence of the rate coefficient fy (4>) for a single catalytic sphere. This dependence is shown in Fig. 21a. The rate constant has the form discussed earlier,... 

K. Tucci and R. Kapral, Mesoscopic model for diffusion-influenced reaction dynamics, J. Chem. Phys. 120, 8262 (2004). 

The iGLE also presents a novel approach for studying the reaction dynamics of polymers in which the chemistry is driven by a macroscopic force that is representative of the macroscopic polymerization process itself The model relies on a redefined potential of mean force depending on a coordinate R which corresponds locally to the reaction-path coordinate between an n-mer and an (n -t 1 )-mer for R = nl. The reaction is quenched not by a kinetic termination step, but through an (R(t))-dependent friction kernel which effects a turnover from energy-diffusion-limited to spatial-diffusion-Iimited dynamics. The iGLE model for polymerization has been shown to exhibit the anticipated qualitative dynamical behavior It is an activated process, it is autocatalytic, and it quenches... 

As an attempt to connect the first discussion, which was concerned with diffusion-reaction coupling, with Dr. Williams presentation of enzymes as dynamic systems, I wanted to direct attention to a number of specific systems. These are the energy-transducing proteins that couple scalar chemical reactions to vectorial flow processes. For example, I am thinking of active transport (Na-K ATPase), muscular contraction (actomyosin ATPase), and the light-driven proton pump of the well-known purple... 

J. B. Keller, Liesegang rings and theory of fast reaction and slow diffusion, in Dynamics and Modelling of Reactive Systems, W. E. Stewart, W. H. Ray and C. C. Couley, eds., Academic Press, New York, 1980. 

The enzyme is immobilized on a nylon mesh, which also acts as a diffuse reflector for the light. The dynamic range of this sensor is between 1(T5 and 10 3M. Although the primary process that determines the steady-state concentration of the p-nitrophenoxide ion is the diffusion-reaction mechanism (which is governed by concentrations of all participating species), the detection of its concentration is again subject to the limitations of optical sensing of ionic species (Section 9.4.1). There are many similar optical enzyme biosensor schemes that utilize detection of... 

Han P, Bartels DM (1994) Encounters of H and D atoms with 02 in water relative diffusion and reaction rates. In Gauduel Y, Rossky P (eds) AIP conference proceedings 298. "Ultrafast reaction dynamics and solvent effects." AIP Press, New York, 72 pp Hasegawa K, Patterson LK (1978) Pulse radiolysis studies in model lipid systems formation and behavior of peroxy radicals in fatty acids. Photochem Photobiol 28 817-823 Herdener M, Heigold S, Saran M, Bauer G (2000) Target cell-derived superoxide anions cause efficiency and selectivity of intercellular induction of apoptosis. Free Rad Biol Med 29 1260-1271 Hildenbrand K, Schulte-Frohlinde D (1997) Time-resolved EPR studies on the reaction rates of peroxyl radicals of polyfacrylic acid) and of calf thymus DNA with glutathione. Re-examination of a rate constant for DNA. Int J Radiat Biol 71 377-385 Howard JA (1978) Self-reactions of alkylperoxy radicals in solution (1). In Pryor WA(ed) Organic free radicals. ACS Symp Ser 69 413-432... 

Figure 15. Chemical reaction dynamics of methanol oxidation to formaldehyde one of the C-H bonds of the methyl group becomes elongated (top left) and eventually breaks (top right). The adsorbed hydroxymethyl group stabilized by forming a hydrogen bonded complex to a water molecule (bottom left) and dissociates rapidly into adsorbed formaldehyde and a hydronium ion (bottom right) which further stabilized by undergoing structural diffusion steps to form Zundel ions H50+.123,125 Reprinted from Chemical Physics, Vol. 319, C. Hartnig and E. Spohr, The role of water in the initial steps of methanol oxidation on Pt(l 1 1), p. 108, Copyright (2005), with permission from Elsevier.

The mechanisms of reactions that occur in condensed phases involve the participation of solvent degrees of freedom. In some cases, such as in certain ion association reactions involving solvent-separated ion pairs, even the very existence of reactant or product states depends on the presence of the solvent. Traditionally the solvent is described in a continuum approximation by reaction-diffusion equations. Kapral s group is interested in microscopic theories that, by treating the solvent at a molecular level, allow one to investigate the origin and range of validity of conventional continuum theories and to understand in a detailed way how solvent motions influence reaction dynamics. 

A detailed study of model (16) for CO oxidation on polycrystalline platinum was carried out by Makhotkin et al. [139]. Numerical experiments revealed that the bulk diffusion effect on the character of reaction dynamics is rather different and controlled by the following factors (1) the initial composition of catalyst surface and bulk, (2) the steady state of its surface and bulk, and (3) the position of the region for slow relaxations of kinetic origin (see ref. 139). As a rule, diffusion retards the establishment of steady states, but the case in which the attainment of this state is accelerated by diffusion is possible. 

Spatiotemporal pattern formation at the electrode electrolyte interface is described by equations that belong in a wider sense to the class of reaction-diffusion (RD) systems. In this type of coupled partial differential equations, any sustained spatial structure comes about owing to the interplay of the homogeneous dynamics or reaction dynamics and spatial transport processes. Therefore, the evolution of each variable, such as the concentration of a reacting species, can be separated into two parts the reaction part , which depends only on the values of the other variables at one particular location, and another part accounting for transport processes that are induced by spatial variations in the variables. These latter processes constitute a spatial coupling among different locations. 

Diffusion 127 -, anomalous 39, 42-43, 65 Diffusion-reaction model 141 Diffusivity, thermal 149 Diglycidylether of bisphenol-A (DGEBA) 141 Disordered structure 12 Dispersion 9-10,30,32,36,48 Dynamic plowing lithography 153... 

A related expression for energy transfer appears when one studies the underdamped (energy diffusion) limit of chemical reaction dynamics in liquids. See, for example, Reference 11. 

At the other extreme, it may be argued that the traditional low-dimensional models of reactors (such as the CSTR, PFR, etc.) should be abandoned in favor of the detailed models of these systems and numerical solution of the full convection-diffusion reaction (CDR) equations using computational fluid dynamics (CFD). While this approach is certainly feasible (at least for singlephase systems) due to the recent availability of computational power and tools, it may be computationally prohibitive, especially for multi-phase systems with complex chemistry. It is also not practical when design, control and optimization of the reactor or the process is of main interest. The two main drawbacks/criticisms of this approach are (i) It leads to discrete models of very high dimension that are difficult to incorporate into design and control schemes. 

Experiments aimed at probing solvent dynamical effects in electrochemical kinetics, as in homogeneous electron transfer, are only of very recent origin, fueled in part by a renaissance of theoretical activity in condensed-phase reaction dynamics [47] (Sect. 3.3.1). It has been noted that solvent-dependent rate constants can sometimes be correlated with the medium viscosity, t] [101]. While such behavior may also signal the onset of diffusion-rather than electron-transfer control, if the latter circumstances prevail this finding suggests that the frequency factor is controlled by solvent dynamics since td and hence rL [eqn. (23), Sect. 3.3.1] is often roughly proportional to... 

Nonlinear resonances are important factors in reaction processes of systems with many degrees of freedom. The contributions of Konishi and of Honjo and Kaneko discuss this problem. Konishi analyzes, by elaborate numerical calculations, the so-called Arnold diffusion, a slow movement along a single resonance under the influence of other resonances. Here, he casts doubt on the usage of the term diffusion. In other words, Arnold diffusion is a dynamics completely different from random behavior in fully chaotic regions where most of the invariant structures are lost. Hence, understanding Arnold diffusion is essential when we go beyond the conventional statistical theory of reaction dynamics. The contribution of Honjo and Kaneko discusses dynamics on the network of nonlinear resonances (i.e., the Arnold web), and stresses the importance of resonance intersections since they play the role of the hub there. 

All these different mechanisms of mass transport through a porous medium can be studied experimentally and theoretically through classical models (Darcy s law, Knudsen diffusion, molecular dynamics, Stefan-Maxwell equations, dusty-gas model etc.) which can be coupled or not with the interactions or even reactions between the solid structure and the fluid elements. Another method for the analysis of the species motion inside a porous structure can be based on the observation that the motion occurs as a result of two or more elementary evolutions that are randomly connected. This is the stochastic way for the analysis of species motion inside a porous body. Some examples that will be analysed here by the stochastic method are the result of the particularisations of the cases presented with the development of stochastic models in Sections 4.4 and 4.5. 

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