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用多尺度计算和沉浸式可视化挑战教条
Mesostructure-performance relationships in batteries and fuel cells : challenging the dogma with multiscale computations and immersive visualization |
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| 课程网址: |
https://videolectures.net/preglov_franco_immersive_visualization/
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| 主讲教师: |
Alejandro A. Franco
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| 开课单位: |
Preglov kolokvij会议
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| 开课时间: |
2016-12-19
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| 课程语种: |
英语
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| 中文简介: |
用于电池和燃料电池的复合电极的优化设计被认为是至关重要的，特别是在性能提高和成本降低方面达到汽车应用的预期。这种电极目前由活性材料或催化剂、添加剂和粘合剂制成，并且所得的复杂多孔结构包含电解质。已经开发了几张概念图，试图捕捉这些复合电极结构特性对整体细胞反应的影响：包括构建捕捉实际电极主要特征的人工结构的方法和基于电极结构计算机辅助重建的方法。这两种方法在理解电池和燃料电池操作方面取得了进展，但对它们的结构特征（例如粘合剂的确切位置）以及三维结构各向异性对从孔隙和/或颗粒到渗滤聚集体和/或团聚体的多个尺度的有效输运特性的影响仍然缺乏了解。为复合电极定义适当的结构图片对于正确解释实验特征以及优化全电池至关重要。在本次讲座中，我讨论了一种新的计算建模方法，该方法描述了多个空间尺度上电化学过程和传输过程之间的相互作用。我们的方法在建立和优化电极细观结构性能关系方面的预测能力是在三个应用实例的背景下提出的：（1）LiO2电池中的放电和充电机制；（2） 锂硫电池的可循环性；（3） PEM燃料电池中的膜降解和碳腐蚀。最后，根据我们最近在伊拉斯谟硕士课程M.E.S.C的讲座中整合这些方面的经验，讨论了这些模型与用于数据分析的三维沉浸式虚拟现实软件相结合所带来的巨大机遇。
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| 课程简介: |
Optimized design of composite electrodes for batteries and fuel cells is recognized to be of crucial importance, in particular to reach automotive application expectations in terms of performance gain and cost reduction. Such electrodes are currently made of active material or catalysts, additives and binder and the resulting complex porous structure contains an electrolyte. Several conceptual pictures have been developed attempting to capture the influence of these composite electrodes structural properties on the overall cell response: approaches consisting of building up artificial structures capturing the main features of the actual electrodes and approaches based on computer-aided reconstruction of the electrode structure. These two approaches have provided progress on the understanding of batteries and fuel cells operation, but there is still a significant lack of understanding of their structural features (e.g. exact location of the binder) and the impact of the three-dimensional structural anisotropies on the effective transport properties at multiple scales, from the pore and/or particle to the percolated aggregates and/or agglomerates. Defining an appropriate structural picture for the composite electrodes is crucial for a correct interpretation of experimental characterizations but also for optimizing the full cells. In this lecture I discuss a novel computational modelling approach describing the interplays between electrochemical and transport processes at multiple spatial scales. The predictive capabilities of our approach on establishing and optimizing electrode mesostructure-performance relationships are presented within the context of three application examples: (1) discharge and charge mechanisms in LiO2 batteries; (2) cyclability of Li-S batteries; (3) membrane degradation and carbon corrosion in PEM Fuel Cells. Finally, the tremendous opportunities opened by the combination of these models with threedimensional immersive Virtual Reality software for data analysis are discussed on the basis of a recent experience by us on integrating these aspects in our lectures within the Erasmus Master Programme M.E.S.C.
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| 关 键 词: |
燃料电池中; 尺度结构; 性能关系; 多尺度计算
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| 课程来源: |
视频讲座网
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| 数据采集: |
2024-04-25：liyq
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| 最后编审: |
2024-04-25：liyq
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| 阅读次数: |
8
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