Abstract
This article presents a unified physical mathematical approach to the modelling nanoparticles dynamic used by the Authors as a foundation to develop a software framework for modelling entities and phenomena occurring at mesoscopic length scale in a generic Gas-Phase (GP) nanoparticle synthesis processes (e.g. plasma, hot-wall and flame reactors) and using Gas-Phase parameters extracted from CFD simulation (linking process). The model considers nanoparticles motion, agglomeration and sintering phenomena and is aimed to provide detailed information about nanoparticles fractal dimension and composition, together with species concentration, consumption rates and particles size distribution. We provide a detailed description of the data structures, the numerical methods and the algorithms adopted to implement the simulation software based on this model.
Highlights
Gas Phase Condensation (GPC) synthesis of nanoparticles is an important link in the manufacturing chain of nanomaterials based products
The main issue affecting GPC processes is the difficulty of controlling the precision of the nanoparticles synthesis and to predict which process conditions can lead to products with specific features
Computational Results we report the computational results of the three methods implemented in the framework based on the proposed model: Langevin Dynamics, Population Based Method and Moments Method, simulating a plasma gradient
Summary
Gas Phase Condensation (GPC) synthesis of nanoparticles is an important link in the manufacturing chain of nanomaterials based products. A better understanding of the link between process conditions and nanoparticle characteristics is relevant for estimating and control the environmental impact of processes where nanoparticles are an undesired side effect and not the main product These considerations strongly motivate an increase in theoretical and applied research to understand and predict the mechanisms of nanoparticles and nanostructures formation. Diffusion Limited Agglomeration models (DLA) [1], propose the addition of simple primary particles, in the case of particle-cluster interactions, to a growing cluster via random walk paths The evolution of this approach, the Diffusion Limited Cluster-Cluster Aggregation models (DLCCA), whose intent is to move two cluster via random walk, representing the Brownian motion in a fluid, and make them collide. The simulations based on this model are characterized by the solution of the equation of motion for each single particle, adding two forces: a friction force proportional the velocity with a friction coefficient related to the bath and a Gaussian stochastic term related to the thermal white noise
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
