Sintering is a key processing step for manufacturing powder metallurgy-based products used in innumerable applications, including devices for upcoming sustainable energy scenarios as fuel cells, solar cells and electrolyser cell, and also for traditional ceramics such as cements and tiles.
Sintering at high heating rates is based on a fast formation of a dense outer layer, which controls the further flux of heat to the interior of the compact. Thereby, the amount of energy available for sintering is enhanced and densification without extensive grain growth becomes easier. The economic and environmental benefit of fast sintering is related to lower quantity of demanded energy and produced emissions. Nevertheless, the influence of composition, heat transfer and sintering atmosphere is still to be fully understood. Thus, modelling and simulation of powder materials subjected to fast sintering can clarify the effects of phase evolution, sample size and geometry on the densification of ceramic bodies.
Modeling and simulation of sintering generally refers to different approaches not only including distortion calculations, morphology issues or stress distribution in the sintering body but also simulating microstructural evolution, mainly densification. However, the current models for densification during sintering do not follow strictly the experimental data. Moreover, available sintering data, even for the same material, are just useful for the very specific experimental settings. Hence, the common practice is to determine experimentally the appropriate conditions to meet the requirements. Thus, there is a lack of a practical model able to predict densification of powder-based materials from sintering data of widely used ceramic materials.
The focus of the current work is to develop models and calculation approaches for modeling the densification step of ceramic powder sintering, particularly at high heating rates and short treatment times, predicting microstructure evolution and defects. Moreover, this project aims to validate the model by designing ceramic materials by fast sintering associated with selected literature experimental data in order to verify the domain of the model in forecasting the behaviour of widely used ceramics.
Modeling particles rearrangement and densification will be performed using Discrete Element Model (DEM) which will be coupled to grid-based model for calculation of liquid transport, as it is schematically shown in Fig. 1. In the first step of an algorithm the multicomponent packing consisting of spherical particles will be generated (stage 1). The information about spatial particle distribution will be directly obtained from the compaction model. Afterwards, depending on the interparticulate contacts a network of liquid bridges will be generated in stage 2. The bridges will be generated and initially will have infinite small volume. These bridges will be treated in DEM as separate entities and will be acting on particles as additional capillary and viscous force. In the second stage the grid-based transport model will be initialized. This model will represent the whole three-dimensional simulation domain discretized with equidistant Cartesian grid. Each of the grid cells will contain information about solid, liquid and gas content. In the third stage, according to the amount of the liquid phase in the cells, the old liquid bonds will be removed and new will be generated between neighboring solid particles. The transport will be calculated in the grid-based model and will be calculated based on the concentration gradient. Moreover, grid-based model will consider solid flow caused due to the particle movement over the cell boundaries.
In order to validate model and to adjust unknown parameters a set of experiments with spatially distributed components will be performed. Ceramic green body samples will be designed using high pure raw materials and shaped by isostatic pressing. Following, the green bodies will be consolidated by fast sintering. Afterwards, using SEM the spatial distribution of component within the sample will be analyzed and compared to the numerical results. Special emphasis will be given to analyze the crack path in the microstructure (inter-, intraganular, debonding, etc.). Additionally, crack resistance as function of crack length (R-Curve behaviour) will be investigated on selected samples.
 Dosta M., Skorych V. (2020). MUSEN: An open-source framework for GPU-accelerated DEM simulations. SoftwareX 12.
 Dosta M., Furlan K., Skorych V., Heinrich S., Janssen R. (2020). Influence of pores arrangement on stability of photonic structures during sintering. JECR 40.
This research is funding by Collaborative Research Initiative Program (PIPC – Programa de Iniciativa de Pesquisa Colaborativa) from CAPES –DFG (Brazil – Germany), edict number 12/2018.
- Institute of Advanced Ceramics, Hamburg University of Technology, Germany (Prof. Rolf Janssen)
- Laboratory of Ceramic Processing (PROCER), Federal University of Santa Catarina, Brazil (Prof. Dachamir Hotza, Prof. Sergio Yesid Gómez González and Prof. Agenor de Noni Jr.)
- Laboratories of Materials (LABMAT), Federal University of Santa Catarina, Brazil (Prof. João Batista Rodrigues Neto)