How can we recover as many valuable raw materials as possible, such as lithium, from melt-down electronic scrap? This question is being examined by a priority programme of the German Research Foundation (DFG) dedicated to the production of tailor-made artificial minerals through metallurgical recycling, in which mathematicians from the Institute of Stochastics at Ulm University are participating. They calculate how different parameters, such as the cooling process or the crushing process, affect the recycled material. Through this work, mathematicians are helping to optimise the process – reducing costs by reducing the need for expensive experiments.
Used car batteries, capacitors or sensors often still contain valuable raw materials such as lithium. This type of electronic waste can be recycled in two ways: either the individual components are separated using mechanical processes, or all parts are melted down. The latter technique has an advantage over mechanical separation processes in that even valuable, low-concentration metals that would otherwise be lost in the recycling stream can be recovered. In the crucible, the metal sinks to the bottom, while all the materials that should be separated from the metal, the slag, are collected in the upper layer. For a long time, this slag was treated like waste – but it contains valuable raw materials that crystallise into so-called artificial minerals in a specially adapted cooling process. How these can be recovered is the subject of research by a team of mathematicians from Ulm led by Dr. Orkun Furat and Professor Volker Schmidt as part of the DFG priority programme SPP 2315 "Engineered Artificial Minerals (EnAM) - a geometallurgical tool for recycling critical elements from waste streams". The research network, with its approximately 25 individual projects, has existed since 2022. Funding has just been extended for another three years, with around 268,000 euros going to Ulm. The SPP 2315 is coordinated by Professor Urs Peuker at the TU Bergakademie Freiberg.
As large as possible, with a high proportion of recyclable materials and easy to break down: these are the characteristics of the perfect minerals that the researchers hope to produce in the slag so that they can then be easily recovered. In order to predict the conditions under which the artificial minerals are optimally formed, researchers from the Institute of Stochastics at Ulm University are working hand in hand with process engineers and metallurgists who carry out standardised melting experiments and mechanical recycling processes and provide the mathematicians with a wide range of real measured data. In particular, this includes image data, i.e. microscopic images of the slag structure at various points in the process chain. The job of the Ulm mathematicians is to understand the process, develop mathematical models and simulate different scenarios on the computer in order to optimise the process. It would take far too long and be far too expensive to carry out thousands of experiments in the laboratory. Stochastic analyses, on the other hand, can be created as often as required – and much more economically.
Recyclable materials should be as pure as possible and have desirable properties
The way in which the desired artificial minerals form can be influenced primarily by the cooling process after melting. "If the slag cools more slowly, the atoms and ions move back and forth and have time to form crystals. This results in larger minerals with different structures," explains Dr Furat. "More compact crystals can then be more easily broken out of the cooled slag." In principle, the entire process can be optimised: from melting and cooling to crushing and separating the valuable materials. "We want to adjust these three steps so that they are cost-effective and the resulting recyclables are as pure as possible and have desirable properties," adds Professor Volker Schmidt, also from the Institute of Stochastics. "An optimised recycling process is definitely less expensive than importing raw materials from South America," Schmidt is convinced.
The Ulm researchers are modelling the behaviour of the materials using 3D microscopy images taken before and after the recycling process. The data provides information about the internal structure of the slag and is the working basis for the mathematicians. "We can look at this in a multidimensional way in the stochastic model and see, for example, that the larger the artificial minerals get, the more different their shapes are," says Orkun Furat. The mathematicians in Ulm also have the task of reducing the complex data sets to a comprehensible representation. Professor Schmidt summarises: "We can make the optimisation of battery recycling more efficient using mathematical methods – that is the power of mathematics."
Further information:
Dr. Orkun Furat, Institute of Stochastics, E-mail: orkun.furat(at)uni-ulm.de
Text and media contact: Christine Liebhardt