Mandal, S.; Pradeep, K. G.; Zaefferer, S.; Raabe, D.: A novel approach to measure grain boundary segregation in bulk polycrystalline materials in dependence of the boundaries’ five rotational degrees of freedom. Scripta Materialia 81, pp. 16 - 19 (2014)
Pradeep, K. G.; Herzer, G.; Choi, P.; Raabe, D.: Atom probe tomography study of ultrahigh nanocrystallization rates in FeSiNbBCu soft magnetic amorphous alloys on rapid annealing. Acta Materialia 68, pp. 295 - 309 (2014)
Yao, M.; Pradeep, K. G.; Tasan, C. C.; Raabe, D.: A novel, single phase, non-equiatomic FeMnNiCoCr high-entropy alloy with exceptional phase stability and tensile ductility. Scripta Materialia 72–73, pp. 5 - 8 (2014)
Pradeep, K. G.: Atomic scale investigation of clustering and nanocrystallization in FeSiNbB(Cu) soft magnetic amorphous alloys. Dissertation, RWTH-Aachen, Aachen, Germany (2014)
New machine learning framework makes metal recycling more sustainable without compromising on mechanical properties. Results now published in journal Science Advances.
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…