Materials Information Discovery (Topic 5)

Topic 5 pursues the further development of unique methods that are available in the research infrastructures of the participating centres (KNMFi, ER-C), validates these in applications and applies data science to improve the data-to-knowledge flow in materials characterization. These methods will be combined in a unified digital materials characterization platform (Model and Data Driven Material Characterization, MDMC), and further support materials development.

Scientists from both KIT and Forschungszentrum Jülich collaborate closely within this topic which has four major focal points:

  1. To develop and optimise selected characterization methods (high-resolution TEM, spectroscopy, NMR, X-rays and light optics with respect to spatial and temporal resolution, sensitivity, automation and in situ and operando characterization. A correlative approach spanning multiple (macro, micro, nano) scales will be developed for combinations of methods to provide a holistic characterization methodology.
    Read more:
    INT – Nanomaterials by Information-Guided Design
    IMT – Imaging and Spectroscopy
    IFG – ToF-SIMS
  2. We are driving the development of NMR instrumentation and methodology, achieving enhanced sensitivity and combining spectroscopic and imaging modalities to extend the capabilities of this versatile technique. We span atomic to macro scales with considerable agility, addressing the entire chemical spectrum from in vitro and in vivo biochemistry, over the liquid state, to solid state chemistry and probing the quantum state of matter. The recent expansion with High through-put screening enhances the potential of combining NMR developments with the well-established microfluidics research at KIT with a view to application in medical diagnostics and drug discovery.
    Read more:
    IMT – Microsystems for Life Science
    IMT – Magnetic Resonance Microscopy and Related Topics
    IOC / IBG-4 – Magnetic Resonance
  3. To apply a correlative, data-driven approach to tackle materials science and solid-state physics problems. The aim is to generate knowledge to both understand and improve the functionalities of materials in fields such as IT, quantum computing, energy storage and conversion and catalysis. Data will be made available for the generation of digital twins, and thus provide input for the virtual materials design of new materials.
    Read more:
    IBG-4 – The Meier Lab
    IMT – Spin & Photon Applications (SPA) Laboratory
    INT – Electron Microscopy and Spectroscopy Laboratory
  4. Rapidly developing data science approaches will accelerate the generation of new materials. Our aim, in close collaboration with other Topics and in alignment with the overarching activities in the Joint Lab MDMC, is to develop computational approaches that are applicable to large datasets, and to derive material models from the experimental data. Massively parallel and high speed data acquisition and semantic analysis will be assisted by the use of intelligent algorithms to recognize and correlate features in real time.
    Read more:
    IOC – The Compounds Platform ComPlat
    IAM – Kadi4Mat
    IAM – Reliability and Probabilistics
    IMT – Microstructures and Process Sensors

Topic 5 collaborates with all other topics and is linked with Joint Labs and Research Infrastructures: