Master- and Bachelor Theses: Development of OPV Cells with High Throughput Methods

The Helmholtz Institute Erlangen-Nürnberg for Renewable Energy (HI ERN), part of the Forschungszentrum Jülich, researches and develops material- and process-based solutions for climate-neutral, sustainable and cost-effective utilization of renewable energies.

In the OPV group we are using an automated high-throughput device fabrication line to optimize and investigate organic solar cells. Furthermore, we are using machine-learning to analyze the data and optimizing devices in a closed-loop approach.

Master- and Bachelor Theses: Development of OPV Cells with High Throughput Methods

Our group specializes in:

  • Combinatorial materials research
  • High-throughput film deposition and characterization
  • Machine learning and closed-loop optimization
  • Stability investigation

for the development of organic solar cells.

We offer the opportunity for Master and Bachelor theses in Organic Photovoltaic cell manufacturing, characterization and optimization, and Machine Learning.


  • Student of Material Science, Nanotechnology, Energy Technology, Physics or comparable require an examiner from their department.
  • Keen interest in material development, in robotics and machine learning
  • Self-driven and reliable
  • Knowledge in data analysis (Python knowledge desirable)

Note: Students of MTW, NT, Energy Technology, MAP can be directly examined. Students from other disciplines require an examiner from their department.

Osterrieder et al., Autonomous optimization of an organic solar cell in a 4-dimensional parameter space, EES (2023),

Du et al., Elucidating the Full Potential of OPV Materials Utilizing a High-Throughput Robot-Based Platform and Machine Learning, Joule (2020)
Wagner, J. et al. The evolution of Materials Acceleration Platforms - towards the laboratory of the future with AMANDA (2021) arXiv:2104.07455


Building HIERN-Immerwahrstr /
Room 1.12
+49 9131-12538323

Last Modified: 04.07.2024