Institute of Solid State Physics

DE


 Computational Material Design with DFT and Machine Learning

The Hofmann group is a small, dynamic computational group that studies the structural and physical properties of inorganic/organic hybrid interfaces. Located at the Institute of Solid State Physics, the activities of the group are between that of a pure theory and that of an experimental group: We engage in method development and implementation (both into our own machine-learning algorithm, SAMPLE, and into the widespread DFT code FHI-aims) as well as in “computer experiments”, where we apply state-of-the-art methods to realistic, technologically relevant interfaces. Thereby, we support – and are in turn supported – by numerous renowned theoretical and experimental groups in Europe and around the globe. Our research interests include


  • Structure Determination and Prediction
  • Polymorphism and Metastable Phases
  • Phase Diagrams and Phase Transformations
  • Charge and Energy Transfer Across Interfaces
  • Adsorption Processes of Organic Molecules
  • Defects in Organic Monolayers
  • Spontaneous Symmetry Breaking in Adsorbate Layers
  • Doping and Long-Range Band-Bending in Semiconductors

which we study (mostly) with the these techniques:

    Density Functional Theory (semilocal and hybrid functionals)
  • Band Structure Calculations
  • Machine Learning (mostly Gaussian Process Regression)
  • Ab-initio Thermodynamics
  • Charge-Reservoir Electrostatic Sheet Technique (a QM/MM approach)


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