2013
DOI: 10.1103/physreve.87.022132
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Exact solutions of kinetic equations in an autocatalytic growth model

Abstract: Kinetic equations are introduced for the transition-metal nanocluster nucleation and growth mechanism, as proposed by Watzky and Finke. Equations of this type take the form of Smoluchowski coagulation equations supplemented with the terms responsible for the chemical reactions. In the absence of coagulation, we find complete analytical solutions of the model equations for the autocatalytic rate constant both proportional to the cluster mass, and the mass-independent one. In the former case, ξ k = s k (ξ1) ∝ ξ … Show more

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Cited by 4 publications
(20 citation statements)
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“…The remaining (apart from B i ) products of reactions (1) and (2) are collectively denoted X 1 and X 2 . In contrast to our previous treatment [19] of the WF mechanism in its original formulation [20][21][22][23], here the presence of the reducing agent has been explicitly taken into account in both (1) and (2). Usually, as an excess of the reducing agent is used, we may assume that its concentration is time-independent.…”
Section: Modelmentioning
confidence: 99%
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“…The remaining (apart from B i ) products of reactions (1) and (2) are collectively denoted X 1 and X 2 . In contrast to our previous treatment [19] of the WF mechanism in its original formulation [20][21][22][23], here the presence of the reducing agent has been explicitly taken into account in both (1) and (2). Usually, as an excess of the reducing agent is used, we may assume that its concentration is time-independent.…”
Section: Modelmentioning
confidence: 99%
“…[21]. In addition, although chemical reactions (1) and (2) are assumed to be irreversible due to the presence of large amount of the reducing agent, this does not need to be the case for the physical processes, and (3) is generalized to include fragmentation [19]. Various extensions of the original WF scheme (1)-(3) are possible, and frequently required, depending on the experimental situation at hand.…”
Section: Modelmentioning
confidence: 99%
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