Winning, M.; Brahme, A.; Raabe, D.: Prediction of cold rolling textures of steels using an artificial neural network. Computational Materials Science 46, pp. 800 - 804 (2009)
Winning, M.; Raabe, D.; Brahme, A.: A texture component model for predicting recrystallization textures. Materials Science Forum 558 / 559, pp. 1035 - 1042 (2007)
Brahme, A.; Winning, M.; Raabe, D.: Texture Component Model for Predicting Recrystallization Textures. 15th International Conference on the Texture of Materials (ICOTOM 15), Pittsburgh, PA, USA (2008)
Brahme, A.: Brief Introduction to Cellular Automaton and Monte Carlo Method. MPIE inter-departmental tutorial day(s) 2008, MPI für Eisenforschung GmbH, Düsseldorf, Germany (2008)
Winning, M.; Raabe, D.; Brahme, A.: A texture component model for predicting recrystallization textures. The Third International Conference on Recrystallization and Grain Growth, Jeju Island, South Korea (2007)
Efficient harvesting of sunlight and (photo-)electrochemical conversion into solar fuels is an emerging energy technology with enormous promise. Such emerging technologies depend critically on materials systems, in which the integration of dissimilar components and the internal interfaces that arise between them determine the functionality.
Enabling a ‘hydrogen economy’ requires developing fuel cells satisfying economic constraints, reasonable operating costs and long-term stability. The fuel cell is an electrochemical device that converts chemical energy into electricity by recombining water from H2 and O2, allowing to generate environmentally-friendly power for e.g. cars or houses…