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

根据组合测量技术的测量数据计算颗粒的形状和结构参数

基本信息

批准号：
310875572
负责人：
Professor Dr.-Ing. Michael Stintz
金额：
--
依托单位：
Institut für Verfahrenstechnik und Umwelttechnik
依托单位国家：
德国
项目类别：
Research Grants
财政年份：
2016
资助国家：
德国
起止时间：
2015-12-31 至 2019-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/310875572?language=en
关键词：
Computation shape structural parameters particles

项目摘要

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.

该研究项目是德国研究集群“通过创新的在线测量技术（MPaC）对基于颗粒的功能化材料进行多参数表征”的一部分，该项目旨在在线表征工业中的气溶胶过程。目的是同时导出不同的形态参数（即关于尺寸、形状、结构），为此目的，不同的测量原理要被组合。这种方法需要足够的模型来量化颗粒形态对单个颗粒和颗粒系统的光学和空气动力学性质的影响，本研究项目的主题是非球形颗粒的形态参数与其光学和基于迁移率的性质之间的相关性。为了可行性起见，仅考虑几种类型的颗粒形态（结构类别）：球形颗粒的分形状或致密聚集体、棒状颗粒及其聚集体，以及具有限定表面结构的颗粒（例如，球形颗粒和棒状颗粒的聚集体）。G.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：团块尺寸和单个棒的长度）。计算光学和迁移率为基础的属性的定量模型，可以部分地从文献中得出;其他的研究项目内开发。采用这些模型是为了建立传感器模型，这些模型尽可能准确且尽可能简单。重建真实的颗粒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通过数学函数或作为数据库来表示。所有计算的主要目标是导出相关的形态参数（例如，G.分形维数、团聚体孔隙率、纵横比、表面粗糙度）。因此，测量数据的信息内容相对于形态参数将用于各种测量技术及其组合与研究集群。这种信息分析揭示了特定技术的应用限制，甚至可以支持基于模型选择适当的测量技术。