multi-dimensional and correlative characterization of particles - central service project

颗粒的多维和相关表征 - 中心服务项目

• 批准号: 313858392
• 负责人: Professor Dr.-Ing. Urs Peuker
• 金额: --
• 依托单位: Institut für Mechanische Verfahrenstechnik und Aufbereitungstechnik
• 依托单位国家: 德国
• 项目类别: Priority Programmes
• 财政年份: 2017
• 资助国家: 德国
• 起止时间: 2016-12-31 至 2023-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/313858392?language=en
• 关键词: multi; dimensional; correlative; characterization; particles

The quantification of separation processes is strongly connected to the availability of distinguishable distributed particle properties. The three-dimensional correlative characterization is the key for a sufficiently detailed description of multidimensional property distributions (e.g. size, morphology).The analytical central project creates discrete particle-datasets in different measuring ranges starting from the lower micro- to the lower nanometer-range, which is a fundamental requirement for the quantification of multidimensional particle properties. Here, the focus is on the development of particle preparation methods, on the enhancement of image based multi-dimensional characterization methods and on the reasonable connection with lower dimensional supplementary analysis methods. The collaboration within the priority program bases on these fundamental datasets resulting in the development of particle and microstructure models. The requirements concerning characterization during the first project phase resulting from projects in all project areas can be categorized into two different main groups: (1) particles that participate as primary particle in the separation process and (2) particles, which are interacting as part of a larger structure (agglomerate). Algorithms and methods from the first project phase will be used for the service measurements. Additionally, tailored measurements offer the chance to expand and supplement these methods. The network approach of the central project within the priority program allows to analyze a variety of particle samples and so it is able to give a complete picture of relevant tasks in separation processes. The particular opportunity is to connect the discrete particle-datasets (metadata) holistically with experimental parameters (from the separation process), measurement and analysis parameters (e.g. image processing). The resulting database of real and virtual discrete particle data (based on the model parameters) will be made available to the international scientific community during and also after the end of the priority program.

分离过程的量化与可区分的分布式颗粒特性的可用性密切相关。三维相关表征是充分详细描述多维属性分布（例如尺寸、形态）的关键。分析中心项目创建从较低微米到较低纳米范围的不同测量范围内的离散颗粒数据集，这是多维颗粒属性量化的基本要求。在这里，重点是颗粒制备方法的发展，基于图像的多维表征方法的增强以及与低维补充分析方法的合理联系。优先计划内的合作基于这些基础数据集，从而开发颗粒和微观结构模型。所有项目领域的项目在第一个项目阶段产生的关于特性鉴定的要求可分为两个不同的主要类别：（1）作为初级颗粒参与分离过程的颗粒和（2）作为较大结构（团聚体）的一部分相互作用的颗粒。第一个项目阶段的算法和方法将用于服务测量。此外，量身定制的测量提供了扩展和补充这些方法的机会。优先计划中的中心项目的网络方法允许分析各种颗粒样品，因此能够全面了解分离过程中的相关任务。具体的机会是将离散的颗粒数据集（元数据）与实验参数（来自分离过程）、测量和分析参数（例如图像处理）整体连接。由此产生的真实的和虚拟离散颗粒数据库（基于模型参数）将在优先方案期间和结束后提供给国际科学界。