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Kinetics, Markovian stochastic

An exhaustive statistical description of living copolymers is provided in the literature [25]. There, proceeding from kinetic equations of the ideal model, the type of stochastic process which describes the probability measure on the set of macromolecules has been rigorously established. To the state Sa(x) of this process monomeric unit Ma corresponds formed at the instant r by addition of monomer Ma to the macroradical. To the statistical ensemble of macromolecules marked by the label x there corresponds a Markovian stochastic process with discrete time but with the set of transient states Sa(x) constituting continuum. Here the fundamental distinction from the Markov chain (where the number of states is discrete) is quite evident. The role of the probability transition matrix in characterizing this chain is now played by the integral operator kernel ... [Pg.185]

Shushin, A.I. Kinetics of subdiflusion-assisted reactions non-Markovian stochastic liou-... [Pg.443]

Several methods for simulating the stochastic evolution of chemical systems have been employed in recent years (Ref. 21 and references therein). Of particular interest is a stochastic simulation algorithm developed from the Markovian stochastic formulation of chemical kinetics (, 21 ). Within this framework the transition probabilities for various kinetic processes take the general form... [Pg.252]

Turning now to the reaction probability function P(t,u) defined earlier, we can write an exact expression based on the Markovian stochastic theory applied to chemical kinetics (20, 21)... [Pg.252]

Stochastic equation (A8.7) is linear over SP and contains the operators La and V.co of differentiation over time-independent variables Q and co. Therefore, if we assume that the time fluctuations of the liquid cage axis orientation Z(t) are Markovian, then the method used in Chapter 7 yields a kinetic equation for the partially averaged distribution function P(Q, co, t, E). The latter allows us to calculate the searched averaged distribution function... [Pg.274]

This is the simplest of the models where violation of the Flory principle is permitted. The assumption behind this model stipulates that the reactivity of a polymer radical is predetermined by the type of bothjts ultimate and penultimate units [23]. Here, the pairs of terminal units MaM act, along with monomers M, as kinetically independent elements, so that there are m3 constants of the rate of elementary reactions of chain propagation ka ]r The stochastic process of conventional movement along macromolecules formed at fixed x will be Markovian, provided that monomeric units are differentiated by the type of preceding unit. In this case the number of transient states Sa of the extended Markov chain is m2 in accordance with the number of pairs of monomeric units. No special problems presents writing down the elements of the matrix of the transitions Q of such a chain [ 1,10,34,39] and deriving by means of the mathematical apparatus of the Markov chains the expressions for the instantaneous statistical characteristics of copolymers. By way of illustration this matrix will be presented for the case of binary copolymerization ... [Pg.180]

Both deterministic and stochastic models can be defined to describe the kinetics of chemical reactions macroscopically. (Microscopic models are out of the scope of this book.) The usual deterministic model is a subclass of systems of polynomial differential equations. Qualitative dynamic behaviour of the model can be analysed knowing the structure of the reaction network. Exotic phenomena such as oscillatory, multistationary and chaotic behaviour in chemical systems have been studied very extensively in the last fifteen years. These studies certainly have modified the attitude of chemists, and exotic begins to become common . Stochastic models describe both internal and external fluctuations. In general, they are a subclass of Markovian jump processes. Two main areas are particularly emphasised, which prove the importance of stochastic aspects. First, kinetic information may be extracted from noise measurements based upon the fluctuation-dissipation theorem of chemical kinetics second, noise may change the qualitative behaviour of systems, particularly in the vicinity of instability points. [Pg.273]

The general solution of the model can be obtained using kinetic Monte Carlo (kMC) simulations. This stochastic method has been successfully applied in the field of heterogeneous catalysis on nanosized catalyst particles (Zhdanov and Kasemo, 2000,2003). It describes the temporal evolution of the system as a Markovian random walk through configuration space. This approach reflects the probabilistic nature of many-particle effects on the catalyst surface. Since these simulations permit atomistic... [Pg.187]


See other pages where Kinetics, Markovian stochastic is mentioned: [Pg.165]    [Pg.241]    [Pg.251]    [Pg.164]    [Pg.174]    [Pg.527]    [Pg.170]    [Pg.180]    [Pg.181]    [Pg.527]    [Pg.204]    [Pg.17]    [Pg.161]    [Pg.171]    [Pg.597]    [Pg.685]    [Pg.199]    [Pg.54]   


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