Multidimensional separation using magnetic particles

DFG优先计划2045的目标是确定能够同时对几种颗粒特性进行分类的分离技术，因此可以被描述为多维的。为此，申请人研究了磁种子过滤（MSF）作为一种选择性和多维分离方法的应用。在MSF中，首先将磁性辅助颗粒添加到目标悬浮液中，并在这些磁性颗粒和待分类的非磁性颗粒之间诱导选择性团聚。在第二步中，以这种方式形成的团块可以通过简单的磁分离分离。在第一个资助期间，表明该过程依赖于表面性质（分离特性1）和粒度（分离特性2），因此适合多维分类。可以识别和量化各种工艺相关参数的影响。此外，该过程的并行模型计算提供了进一步的，实验上无法获得的信息。此外，新的实验装置的调试允许在未来的研究中对重要的工艺参数进行明确的调整。在第二个资助期，计划在实验方面对多维分类进行广泛的参数研究。在这里，分析技术将首先得到扩展，并进一步测试表面特性的适用性，例如疏水性，作为分离特性。此外，分离步骤后的团聚体破碎被视为第二个资助期的核心目标，它允许回收使用过的磁性辅助颗粒，并对资源节约的过程实施具有决定性作用。在理论方面，在第一个资助期已经提供了宝贵见解的模型计算将被转移并扩展到多维分类案例中。

The goal of the DFG priority program 2045 is to identify separation techniques that are able to classify simultaneously with respect to several particle properties and thus can be described as multidimensional. For this purpose, the applicant investigates the application of magnetic seeded filtration (MSF) as a selective and multidimensional separation method. In MSF, magnetic auxiliary particles are first added to a target suspension and a selective agglomeration is induced between these magnetic particles and the non-magnetic particles that are to be classified. In a second step, the agglomerates formed in this way can be separated by simple magnetic separation. During the first funding period, it was shown that the process is dependent on both the surface properties (separation characteristic 1) and the particle size (separation characteristic 2) and is therefore suitable for multidimensional classification. It was possible to identify and quantify the influences of various process-relevant parameters. In addition, parallel model calculations of the process provided further, experimentally non-accessible information. Furthermore, the commissioning of a new experimental apparatus allows a defined adjustment of important process parameters in future investigations.For the second funding period, extensive parameter studies for multidimensional classification are planned on the experimental side. Here, the analytical techniques will first be extended and the suitability of further surface properties, e.g. hydrophobicity, as separation characteristics will be tested. In addition, the agglomerate breakage after the separation step is regarded as a core objective of the second funding period, which allows the recovery of the used magnetic auxiliary particles and is decisive for a resource-saving implementation of the process. On the theoretical side, the model calculations, which already provided valuable insights in the first funding period, are to be transferred and extended to the multidimensional classification case.