Mitra, C.; Lange, B.; Freysoldt, C.: Quasiparticle band offsets of semiconductor heterojunctions from a generalized marker method. Physical Review B 84 (19), 193304, pp. 1 - 4 (2011)
Lange, B.; Freysoldt, C.; Neugebauer, J.: Native and hydrogen-containing point defects in Mg3N2: A density functional theory study. Physical Review B 81, 224109, pp. 1 - 10 (2010)
Lange, B.; Freysoldt, C.; Neugebauer, J.: Point-defect energetics from LDA, PBE, and HSE: Different functionals, different energetics? 1.st Austrian/German Workshop on Computational Materials Design, Kramsach, Tyrol, Austria (2012)
Lange, B.; Freysoldt, C.; Neugebauer, J.: Highly p-doped GaN:Mg! What hinders the thermal drive-out of hydrogen? 2. Klausurtagung des Graduierten Kollegs: Mikro und Nanostrukturen in der Optoelektronik, Bad Karlshafen, Germany (2009)
Lange, B.; Freysoldt, C.; Neugebauer, J.: Role of the parasitic Mg3N2 phase in post-growth activation of p-doped Mg:GaN. DPG Frühjahrstagung, TU Dresden, Germany (2009)
Lange, B.; Freysoldt, C.; Neugebauer, J.: Role of the parasitic Mg3N2 phase in post-groth activation of p-doped Mg:GaN. ICNS-8, Jeju Island, South Korea (2009)
Lange, B.; Freysoldt, C.; Neugebauer, J.: Role of the parasitic Mg3N2 phase in post-growth activation of p-doped Mg:GaN. CECAM Workshop 09: Which Electronic Structure Method for the Study of Defects?, CECAM-HQ-EPFL, Lausanne, Switzerland (2009)
Lange, B.: Limitierungen der p-Dotierbarkeit von Galliumnitrid: Eine Defektstudie von GaN:Mg auf Basis der Dichtefunktionaltheorie. Dissertation, Universität Paderborn, Paderborn, Germany (2012)
Max Planck scientists design a process that merges metal extraction, alloying and processing into one single, eco-friendly step. Their results are now published in the journal Nature.
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
Data-rich experiments such as scanning transmission electron microscopy (STEM) provide large amounts of multi-dimensional raw data that encodes, via correlations or hierarchical patterns, much of the underlying materials physics. With modern instrumentation, data generation tends to be faster than human analysis, and the full information content is…