Fluctuations in discrete fragmentation processes studied by stochastic simulations

Thorn, Matthias; Broide, Michael L.; Seeßelberg, M.

doi:10.1103/physreve.51.4089

Cited by 13 publications

(10 citation statements)

References 19 publications

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“…Stochastic simulation techniques have been widely employed to study colloidal aggregation kinetics. [21][22][23][24] Colloidal aggregation resembles protein self-assembly closely in terms of the governing rate equations. The characteristic feature of a lag phase present in nucleated self-assembly has also been found in computational studies of reversible colloidal aggregation.…”

Section: Introductionmentioning

confidence: 99%

Stochastic lag time in nucleated linear self-assembly

Tiwari

Schoot

2016

The Journal of Chemical Physics

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Protein aggregation is of great importance in biology, e.g., in amyloid fibrillation. The aggregation processes that occur at the cellular scale must be highly stochastic in nature because of the statistical number fluctuations that arise on account of the small system size at the cellular scale. We study the nucleated reversible self-assembly of monomeric building blocks into polymer-like aggregates using the method of kinetic Monte Carlo. Kinetic Monte Carlo, being inherently stochastic, allows us to study the impact of fluctuations on the polymerisation reactions. One of the most important characteristic features in this kind of problem is the existence of a lag phase before self-assembly takes off, which is what we focus attention on. We study the associated lag time as a function of the system size and kinetic pathway. We find that the leading order stochastic contribution to the lag time before polymerisation commences is inversely proportional to the system volume for large-enough system size for all nine reaction pathways tested. Finite-size corrections to this do depend on the kinetic pathway.

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Section: Introductionmentioning

confidence: 99%

Stochastic lag time in nucleated linear self-assembly

Tiwari

Schoot

2016

The Journal of Chemical Physics

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“…Thus much better statistics can be achieved and the simulations can reach much longer times than those of the CCA model. Also, if necessary, other processes such as fragmentation can be incorporated in the simulations [7]. Therefore the stochastic method is of great practical use.…”

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confidence: 99%

Thorn and Seesselberg Reply

Thorn

Seeßelberg

1995

Phys. Rev. Lett.

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“…During the final fourth stage, the cluster size distribution and bond population reach a dynamic equilibrium and fluctuate around the corresponding mean values. Hence, the curves shown in Figures 7b and 8a stop once the equilibrium state is established and the data points for large times scatter around horizontal lines in the fluctuation interval of the final average cluster size n w ) [22,30].…”

Section: Unbreakable Primary Bonds and Breakablementioning

confidence: 90%

Simulated Reversible Aggregation Processes for Different Interparticle Potentials: The Cluster Aging Phenomenon

et al. 2003

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The kinetics of reversible 3D aggregation processes was studied for different interparticle potentials by means of simulations. In previous work (Phys. ReV. E 2002, 65, 031405), 1 freely diffusing particles were considered that aggregate whenever a collision occurs but disintegrate only with a single given breakup probability. The DLVO theory, however, predicts also interparticle potentials showing two minima of different depths separated by an energetic barrier. Hence, two different kind of bonds, primary and secondary ones, can be formed and should be treated separately. In the present work, this behavior was implemented by considering bonds with different breakup probabilities. The data obtained from simulations were compared with the stochastic solutions of the corresponding master equation. For this purpose, the Brownian kernel was employed together with novel fragmentation kernels. The agreement between the simulations and the kinetic description was found to be quite satisfactory. Moreover, studying the time evolution of the bond population showed that cluster aging appears as a natural consequence of the employed model.

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Fluctuations in discrete fragmentation processes studied by stochastic simulations

Cited by 13 publications

References 19 publications

Stochastic lag time in nucleated linear self-assembly

Stochastic lag time in nucleated linear self-assembly

Thorn and Seesselberg Reply

Simulated Reversible Aggregation Processes for Different Interparticle Potentials: The Cluster Aging Phenomenon

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