Computation of shape and structural parameters of particles from measurement data of combined measurement techniques

该研究项目是德国研究集群“通过创新在线测量技术（MPaC）对颗粒基功能化材料进行多参数表征”的一部分，该研究集群旨在在线表征工业中的气溶胶过程。目标是同时得出不同的形态参数（即尺寸，形状，结构），为此需要结合不同的测量原理。这种方法需要足够的模型来量化粒子形态对单个粒子和粒子系统的光学和空气动力学特性的影响。本课题的研究主题是非球形粒子的形态参数与其光学性质和迁移率之间的关系。为了可行性起见，只考虑了几种类型的颗粒形态（结构类别）：球形颗粒的分形或致密团块，棒状颗粒及其团块，以及具有确定表面结构的颗粒（例如惰性颗粒上的催化剂颗粒）。尺寸范围从几纳米到几微米（上限：团聚体尺寸和单个棒的长度）。光学性质和迁移率性质的定量计算模型可以部分地从文献中得到；其他的必须在研究项目中开发。使用这些模型是为了建立尽可能精确和简单的传感器模型。重建真实粒子形态将是获得低计算成本定量模型的核心方法。预期的传感器模型可以用数学函数或数据库表示。所有计算的主要目的是从组合测量的数据集中推导出相关的形态参数（如分形维数、团聚体孔隙度、纵横比、表面粗糙度）。因此，关于形态参数的测量数据的信息内容将被用于各种测量技术及其与研究集群的组合。这样的信息分析揭示了特定于技术的应用限制，甚至可能支持基于模型的适当测量技术的选择。

The research project is part of the German research cluster "Multi-parameter characterisation of particle-based functionalised materials by means of innovative online-measurement technique (MPaC)", which aims at the online characterisation of aerosol processes in industry. The objective is to derive different morphological parameters (i.e. on size, shape, structure) simultaneously for which purpose different measurement principles are to be combined. This approach requires adequate models that quantify the impact of particle morphology on the optical and aerodynamic properties of single particles and particle systems.Subject of this research project is the correlation between the morphological parameters of non-spherical particles and their optical and mobility-based properties. For the sake of feasibility only few types of particle morphology (structure classes) are considered: fractal-like or compact agglomerates of spherical particles, rod-like particles and agglomerates of them, and particles with defined surface structures (e. g. catalyst particles on inert grains). The size range reaches of a few nanometres to several micrometres (upper limit: agglomerate size and length of individual rods). Quantitative models for the calculation of optical and mobility-based properties can be partly elicited from literature; others have to be developed within the research project. These models are employed in order to establish sensor models, which are as accurate as necessary and as simple as possible. Reconstructing the real particle morphology will be the central approach for obtaining quantitative models with low computational costs. The intended sensor models can be expressed by means of mathematical functions or as data-base. The primary objective of all computations is the derivation of relevant morphological parameters (e. g. fractal dimension, agglomerate porosity, aspect ratio, surface roughness) out of data sets of combined measurements. Therefore, the information content of measurement data with respect to morphological parameters will be employed for the various measurement techniques and their combinations used with the research cluster. Such an information analysis reveals technique-specific limits of application and may even support the model-based selection of appropriate measurement techniques.