首页|Stress-and process model for dispersing of nanoparticulate suspensions in laminar shear flow

Stress-and process model for dispersing of nanoparticulate suspensions in laminar shear flow

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This work presents a stress model and a process model for dispersing processes in laminar shear flow, which are performed in devices such as kneaders, extruders and three roller mills. Based on deep investigations of two kneaders (lab-and pilot-scale) a methodology is presented, which allows modelling the dispersing process by applying a stress model along with a population balance model to the given task. Stress models describe how often particles are stressed during the process and which energy is transferred to the particles. For dispersing in laminar shear flow, it is crucial to distinguish between dispersing-effective and ineffective stress events based on whether the stress intensity is high enough to overcome the particle strength. Results suggest, that the effective specific energy input determines the dispersing progress independent of the process scale. A process model in form of a population balance was required to obtain otherwise unknown parameters for the stress model. The applied population balance model accounts for the acting working principles during dispersing. For such a mechanistic depiction of the dispersing progress, the trilateral dependency between particle size, resulting viscosity, particle stressing and fragmentation must be modelled. It was found that based on the models, the process behaviour on both scales can be depicted, which offers the perspective of a knowledge-based scale-up of machines and processes, process control and process design based on these results.

Population balance modelDispersingDispersive mixingComposite materialsNanocompositesStress modelKneaderExtruder

Benedikt Finke、Marcel Schrader、Arno Kwade

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Technische Universitat Braunschweig-Institute for Particle Technology, Volkmaroder Strafte 5, 38104 Braunschweig, Germany

2022

Advanced Powder Technology

Advanced Powder Technology

EISCI
ISSN:0921-8831
年,卷(期):2022.33(7)
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