Literature DB >> 12786130

Kinetics of random aggregation-fragmentation processes with multiple components.

I J Laurenzi1, S L Diamond.   

Abstract

A computationally efficient algorithm is presented for exact simulation of the stochastic time evolution of spatially homogeneous aggregation-fragmentation processes featuring multiple components or conservation laws. The algorithm can predict the average size and composition distributions of aggregating particles as well as their fluctuations, regardless of the functional form (e.g., composition dependence) of the aggregation or fragmentation kernels. Furthermore, it accurately predicts the complete time evolutions of all moments of the size and composition distributions, even for systems that exhibit gel transitions. We demonstrate the robustness and utility of the algorithm in case studies of linear and branched polymerization processes, the last of which is a two-component process. These simulation results provide the stochastic description of these processes and give new insights into their gel transitions, fluctuations, and long-time behavior when deterministic approaches to aggregation kinetics may not be reliable.

Year:  2003        PMID: 12786130     DOI: 10.1103/PhysRevE.67.051103

Source DB:  PubMed          Journal:  Phys Rev E Stat Nonlin Soft Matter Phys        ISSN: 1539-3755


  3 in total

1.  Lattice kinetic Monte Carlo simulations of convective-diffusive systems.

Authors:  Matthew H Flamm; Scott L Diamond; Talid Sinno
Journal:  J Chem Phys       Date:  2009-03-07       Impact factor: 3.488

2.  Simulation of aggregating particles in complex flows by the lattice kinetic Monte Carlo method.

Authors:  Matthew H Flamm; Talid Sinno; Scott L Diamond
Journal:  J Chem Phys       Date:  2011-01-21       Impact factor: 3.488

3.  Quantitative dynamics of reversible platelet aggregation: mathematical modelling and experiments.

Authors:  Aleksandra A Filkova; Alexey A Martyanov; Andrei K Garzon Dasgupta; Mikhail A Panteleev; Anastasia N Sveshnikova
Journal:  Sci Rep       Date:  2019-04-17       Impact factor: 4.379

  3 in total

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