- Degree
- PhD (Dr-Ing or Dr rer nat)
- Doctoral degree or degree awarded by
- Ruhr University Bochum or University Duisburg-Essen
- Course location
- Düsseldorf
- In cooperation with
- Max-Planck-Institut für Kohlenforschung, Mülheim/Ruhr
Ruhr University Bochum
University Duisburg-Essen
- Teaching language
- • English
- Languages
- The doctoral programme is conducted entirely in English.
- Full-time / part-time
- • full-time
- Programme duration
- 6 semesters
- Beginning
- Other
- Additional information on beginning, duration and mode of study
- Beginning is in January each year or individually later.
- Application deadline
- There is one application round in September/October each year.
- Tuition fees per semester in EUR
- None
- Combined Master's degree / PhD programme
- No
- Joint degree / double degree programme
- No
- Description/content
- Our structured, three-year doctoral programme, conducted entirely in English, takes an intensive interdisciplinary approach and brings together scientists from across the globe in the Rhine-Ruhr metropolitan region of Germany.
Metallurgy has provided humankind with materials, tools and the associated progress for more than five millennia. It is not only a huge engineering success story but has also become the biggest single industrial environmental burden of our generation. Disruptive innovations are required for alternative reduction processes that convert mineral ores into metals without today’s carbon-based methods that release huge amounts of CO2. SusMet focuses on the exploration of carbon-free sustainable metallurgy, employing hydrogen as reducing agent, direct electroreduction (electrolysis), and plasma synthesis.
Correlated experimental, ab initio and multi-scale techniques are central to our mission:
• Development and application of advanced simulation techniques to explore and identify the fundamental structures and mechanisms occurring in these materials and their synthesis over all relevant length scales (e.g., cutting-edge ab initio methods, atomistic simulation methods, multi-scale modelling, machine learning)
• High resolution analysis, monitoring of chemistry, structure and transformations at the atomic scale of buried interfaces and defects by correlated experimental techniques in both space and time (e.g., correlated APT, TEM, FIM, EBIC, EBSD, XPS Kelvin probe microscopy, machine learning augmented analysis techniques)
• Experimental and computational analysis of transport and the reaction of surfaces and particles with reducing and oxidising gas-phase species (e.g. laser-based imaging diagnostics, setup of model reactors, modelling of underlying reactions, multi-scale simulation of reactive fluids, computational fluid dynamics)