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arxiv: 1203.3905 · v1 · pith:ET3CMIZYnew · submitted 2012-03-17 · ❄️ cond-mat.stat-mech

Driven Brownian coagulation of polymers

classification ❄️ cond-mat.stat-mech
keywords distributionclustersizestationaryclustersstatetimebehavior
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We present an analysis of the mean-field kinetics of Brownian coagulation of droplets and polymers driven by input of monomers which aims to characterize the long time behavior of the cluster size distribution as a function of the inverse fractal dimension, $a$, of the aggregates. We find that two types of long time behavior are possible. For $0\leq a < 1/2$ the size distribution reaches a stationary state with a power law distribution of cluster sizes having exponent 3/2. The amplitude of this stationary state is determined exactly as a function of $a$. For $1/2 < a \leq 1$, the cluster size distribution never reaches a stationary state. Instead a bimodal distribution is formed in which a narrow population of small clusters near the monomer scale is separated by a gap (where the cluster size distribution is effectively zero) from a population of large clusters which continue to grow for all time by absorbing small clusters. The marginal case, $a=1/2$, is difficult to analyze definitively, but we argue that the cluster size distribution becomes stationary and there is a logarithmic correction to the algebraic tail.

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