Oliver T. Hofmann

Simulation-Driven Material Discovery Group

The mission of the Hofmann group is the computational discovery of novel materials and material combinations from first principles. We focus on thin film and interfaces, that are of technilogical relevance for nanotechnology applications, such as organic solar cells and OLED displays. We focus on organic thin films, which often assume particular polymorphs and exhibit properties superior to that of the bulk.

To achieve this mission, my group and I pursue two complementary avenues. One part applies density functional theory (DFT) to pertinent surface science problems at inorganic/organic interfaces, with the goal to identify and push back the limits of the state-of-the-art methodology. The second part of my group develops the machine-learning algorithm "SAMPLE" to predict the structure and the properties of thin film polymorphs. 

Members of the group 2024

Research Interests

• 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

Methods

• Density Functional Theory (semilocal and hybrid functionals)
• Band Structure Calculations
• Machine Learning (Gaussian Process Regression)
• Ab-initio Thermodynamics