Oscillating stationary distributions of nanoclusters in an open system

IF 1.8 4区 数学 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Mathematical and Computer Modelling of Dynamical Systems Pub Date : 2020-07-19 DOI:10.1080/13873954.2020.1793786
Sergey A. Matveev, A. Sorokin, A. Smirnov, E. Tyrtyshnikov
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引用次数: 3

Abstract

ABSTRACT Steady-state oscillations of nanoparticle populations in the system of colliding monomers and seed-clusters are observed for the range of the seed-cluster source with diffusion and ballistic collision kernels. The dynamics of nanoparticles in this system is driven by monomer-cluster and cluster-cluster irreversible aggregation and described in terms of the number of primary monomers per nanoparticle based on solving the population balance equations as described by the classical system of Smoluchowski equations. The oscillations of particles’ concentrations arise with growing power of the source of seed-clusters and can remain visible for several orders of magnitute of particle sizes . For the case of constant kinetic coefficients the novel semi-analytial solution of the utilized aggregation model is found and results of numerical simulations with use of up to non-linear kinetic equations agree excellently with proposed theory.
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开放系统中纳米团簇的振荡平稳分布
在具有扩散和弹道碰撞核的粒子簇源范围内,观察了单体和粒子簇碰撞系统中纳米粒子居群的稳态振荡。该体系中纳米颗粒的动力学由单体-团簇和团簇-团簇不可逆聚集驱动,并基于求解经典斯摩鲁霍夫斯基方程组描述的种群平衡方程,用每个纳米颗粒的原生单体数量来描述。粒子浓度的振荡随着种子簇源功率的增加而增加,并且在粒子大小的几个数量级上仍然可见。对于常动力系数的情况,本文建立了新的聚合模型的半解析解,并利用非线性动力学方程进行了数值模拟,结果与所提出的理论非常吻合。
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来源期刊
CiteScore
3.80
自引率
5.30%
发文量
7
审稿时长
>12 weeks
期刊介绍: Mathematical and Computer Modelling of Dynamical Systems (MCMDS) publishes high quality international research that presents new ideas and approaches in the derivation, simplification, and validation of models and sub-models of relevance to complex (real-world) dynamical systems. The journal brings together engineers and scientists working in different areas of application and/or theory where researchers can learn about recent developments across engineering, environmental systems, and biotechnology amongst other fields. As MCMDS covers a wide range of application areas, papers aim to be accessible to readers who are not necessarily experts in the specific area of application. MCMDS welcomes original articles on a range of topics including: -methods of modelling and simulation- automation of modelling- qualitative and modular modelling- data-based and learning-based modelling- uncertainties and the effects of modelling errors on system performance- application of modelling to complex real-world systems.
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