Budáč Daniel, Miloš Vojtěch, Carda Michal, Paidar Martin, Bouzek Karel, Fuhrmann Jürgen
Department of Inorganic Technology, Faculty of Chemical Technology, University of Chemistry and Technology Prague, Technická 5, Prague 6 - Dejvice 166 28, Czech Republic.
Mathematical Institute, Faculty of Mathematics and Physics, Charles University, Sokolovská 49/83, Prague 8 186 75, Czech Republic.
ACS Appl Mater Interfaces. 2024 Nov 13;16(45):62292-62300. doi: 10.1021/acsami.4c08287. Epub 2024 Nov 5.
Porous ceramic composites play an important role in several applications. This is due to their unique properties resulting from a combination of various materials. Determination of the composite properties and structure is crucial for their further development and optimization. However, composite analysis often requires complex, expensive, and time-demanding experimental work. Mathematical modeling represents an effective tool to substitute experimental approach. The present study employs a Monte Carlo 3D equivalent electronic circuit network model developed to analyze a highly porous composite on the basis of minimum easily obtainable input parameters. Solid oxide cell electrodes were used as a model example, and this study focuses primarily on materials with a porosity of 55% and higher, characterized by deviation of behavior from those of lower void fraction share. This task is approached by adding to the original Monte Carlo model an additional parameter defining the void phase coalescence phenomenon. The enhanced model accurately simulates electrical conductivity for experimental samples of up to 75% porosity. Using sample composition, single-phase properties, and experimentally determined conductivity, this model allows us to estimate data of the internal structure of the material. This approach offers a rapid and cost-effective method to study material microstructure, providing insights into properties, such as electrical conductivity and heat conductivity. The present research thus contributes to advancing predictive capabilities in understanding and optimizing the performance of composite materials with potential in various technological applications.
多孔陶瓷复合材料在多种应用中发挥着重要作用。这归因于它们由多种材料组合而成的独特性能。确定复合材料的性能和结构对于其进一步发展和优化至关重要。然而，复合材料分析通常需要复杂、昂贵且耗时的实验工作。数学建模是替代实验方法的有效工具。本研究采用了一种蒙特卡洛三维等效电子电路网络模型，该模型基于最少的易于获取的输入参数来分析高度多孔的复合材料。固体氧化物电池电极被用作模型示例，本研究主要关注孔隙率为55%及以上的材料，其行为特征与较低孔隙率份额的材料有所不同。通过在原始蒙特卡洛模型中添加一个定义孔隙相聚并现象的附加参数来解决此任务。增强后的模型能够准确模拟孔隙率高达75%的实验样品的电导率。利用样品组成、单相性能和实验测定的电导率，该模型使我们能够估计材料内部结构的数据。这种方法提供了一种快速且经济高效的研究材料微观结构的方法，有助于深入了解诸如电导率和热导率等性能。因此，本研究有助于提高预测能力，以理解和优化在各种技术应用中具有潜力的复合材料的性能。
