Peng, Z.; Gault, B.; Raabe, D.; Ashton, M. W.; Sinnott, S. B.; Choi, P.-P.; Li, Y.: On the Multiple Event Detection in Atom Probe Tomography. In: MicroscopyMicroanalysis, Vol. 23, pp. 618 - 619. Microscopy & Microanalysis 2017, St. Louis, MO, USA, August 06, 2017 - August 10, 2017. (2017)
Peng, Z.; Meiners, T.; Gault, B.; Liebscher, C.; Raabe, D.; Lu, Y.: A Methodology for Investigation of Grain-Boundary Diffusion and Segregation. In: MicroscopyMicroanalysis, Vol. 23, pp. 656 - 657. Microscopy & Microanalysis 2017, St. Louis, MO, USA, August 06, 2017 - August 10, 2017. (2017)
Peng, Z.; Gault, B.; Raabe, D.: On the Multiple Event Detection in Atom Probe Tomography. Microscopy & Microanalysis 2017 Conference, St. Louis, MO, USA (2017)
Peng, Z.: Investigation of ruthenium effect on the formation of topologically close-packed phases in nickel based superalloys. Master, RWTH Aachen, Aachen, Germany (2014)
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.