Ramana, E. V.; Durairajan, A.; Kavitha, D.; Tobaldi, D. M.; Zavašnik, J.; Bdikin, I.; Valente, M. A.: Enhanced magnetoelectric and energy storage performance of strain-modified PVDF-Ba0.7Ca0.3TiO3-Co0.6Zn0.4Fe2O4nanocomposites. Journal of energy storage 87, 111454 (2024)
Öcal, E. B.; Sajadifa, S. V.; Sellner, E. P. K.; Vollmer, M.; Heidarzadeh, A.; Zavašnik, J.; Niendorf, T.; Groche, P.: Functionally Graded AA7075 Components Produced via Hot Stamping: A Novel Process Design Inspired from Analysis of Microstructure and Mechanical Properties. Advanced Engineering Materials - Special Issue: Structural Materials 25 (15), 2201879 (2023)
Sajadifar, S. V.; Suckow, T.; Chandra, C. K.; Heider, B.; Heidarzadeh, A.; Zavašnik, J.; Reitz, R.; Oechsner, M.; Groche, P.; Niendorf, T.: Assessment of the impact of process parameters on the final material properties in forming of EN AW 7075 employing a simulated forming process. Journal of Manufacturing Processes 86, pp. 336 - 353 (2023)
Entezari, H.; Kashi, M. A.; Alikhanzadeh-Arani, S.; Montazer, A.H.; Zavašnik, J.: In situ precipitation synthesis of FeNi/ZnO nanocomposites with high microwave absorption properties. Materials Chemistry and Physics 266, 124508 (2021)
Žerjav, G.; Teržan, J.; Djinović, P.; Barbieriková, Z.; Hajdu, T.; Brezová, V.; Zavašnik, J.; Kovač, J.; Pintar, A.: TiO2–β–Bi2O3 junction as a leverage for the visible-light activity of TiO2 based catalyst used for environmental applications. Catalysis Today 361, pp. 165 - 175 (2021)
Djinović, P.; Zavašnik, J.; Teržan, J.; Jerman, I.: Role of CO2 During Oxidative Dehydrogenation of Propane Over Bulk and Activated-Carbon Supported Cerium and Vanadium Based Catalysts. Catalysis Letters 151 (10), pp. 2816 - 2832 (2021)
Taherzadeh Mousavian, R.; Zavašnik, J.; Heidarzadeh, A.; Bahramyan, M.; Vijayaraghavan, R. K.; McCarthy, É.; Clarkin, O. M.; McNally, P. J.; Brabazon, D.: Development of BMG-B2 nanocomposite structure in HAZ during laser surface processing of ZrCuNiAlTi bulk metallic glasses. Applied Surface Science 505, 144535 (2020)
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
Complex simulation protocols combine distinctly different computer codes and have to run on heterogeneous computer architectures. To enable these complex simulation protocols, the CM department has developed pyiron.
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…