Swaminathan, S.; Spiegel, M.; Rohwerder, M.: Effect of annealing conditions on the selective oxidation of quarternary model alloy. 4th International Conference on Diffusion in Solids and Liquids, Barcelona, Spain (2008)
Swaminathan, S.; Koll, T.; Pohl, M.; Spiegel, M.: Hot-dip galvanizing simulation of model alloys and industrial steel grades: Correlation between surface chemistry and wettability. GALVATECH `07, 7th International Conference on Zinc and Zinc Alloy Coated Steel Sheet, Osaka, Japan (2007)
Swaminathan, S.; Spiegel, M.: Effect of alloy composition on the selective oxidation of ternary Fe–Si–Cr, Fe–Mn–Cr model alloys. ECASIA 2007, 12th European Conference on Applications of Surface and Interface Analysis, Brussels-Flggey, Belgium (2007)
Auinger, M.; Swaminathan, S.; Rohwerder, M.: The Influence of Oxide Formation on the Diffusion Properties in Iron Alloys - The Thermogravimetric Behaviour in Early Stages of Oxidation. Gordon-Kenan Research Seminar on High Temperature Corrosion and Gordon-Research Conference on High Temperature Corrosion, New London, NH, USA (2011)
Vogel, D.; Swaminathan, S.; Rohwerder, M.; Renner, F. U.: Possibilities for high-temperature corrosion at MPIE. International Symposium on High-temperature Oxidation and Corrosion, Zushi, Japan (2010)
Vogel, A.; Swaminathan, S.; Vogel, D.; Rohwerder, M.: Novel Setup for Metal/Gas Reactions at High Temperature. 6th International Conference on Diffusion in Solids and Liquids: Mass Transfer, Heat Transfer and Microstructure and Properties, Paris, France (2010)
Swaminathan, S.: Selective surface oxidation and segregation upon short term annealing of model alloys and industrial steel grades. Dissertation, Ruhr-Universität, Fakultät für Physik und Astronomie, Bochum, Germany (2007)
Scientists of the Max-Planck-Institut für Eisenforschung pioneer new machine learning model for corrosion-resistant alloy design. Their results are now published in the journal Science Advances
Statistical significance in materials science is a challenge that has been trying to overcome by miniaturization. However, this process is still limited to 4-5 tests per parameter variance, i.e. Size, orientation, grain size, composition, etc. as the process of fabricating pillars and testing has to be done one by one. With this project, we aim to…
Atom probe tomography (APT) provides three dimensional(3D) chemical mapping of materials at sub nanometer spatial resolution. In this project, we develop machine-learning tools to facilitate the microstructure analysis of APT data sets in a well-controlled way.
Atom probe tomography (APT) is one of the MPIE’s key experiments for understanding the interplay of chemical composition in very complex microstructures down to the level of individual atoms. In APT, a needle-shaped specimen (tip diameter ≈100nm) is prepared from the material of interest and subjected to a high voltage. Additional voltage or laser…
Recent developments in experimental techniques and computer simulations provided the basis to achieve many of the breakthroughs in understanding materials down to the atomic scale. While extremely powerful, these techniques produce more and more complex data, forcing all departments to develop advanced data management and analysis tools as well as…