Marquardt, O.; Hickel, T.; Neugebauer, J.; Gambaryan, K. M.; Aroutiounian, V. M.: Growth process, characterization, and modeling of electronic properties of coupled InAsSbP nanostructures. Journal of Applied Physics 110 (4), pp. 043708-1 - 043708-6 (2011)
Young, T. D.; Marquardt, O.: Influence of strain and polarization on electronic properties of a GaN/AlN quantum dot. Physica Status Solidi C C6 (S2), pp. S557 - S560 (2009)
Marquardt, O.; Gambaryan, K. M.; Aroutiounian, V. M.; Hickel, T.; Neugebauer, J.: Growth process, characterization and optoelectronic properties of InAsSbP dot-pit cooperative nanostructures. VCIAN 2010, Santorini, Greece (2010)
Marquardt, O.; Hickel, T.; Neugebauer, J.: Polarization-induced charge carrier separation in realistic polar and nonpolar GaN quantum dots. Computational Materials Science on Complex Energy Landscapes Workshop, Imst, Austria (2010)
Marquardt, O.; Hickel, T.; Neugebauer, J.: Polarization-induced charge carrier separation in realistic polar and nonpolar grown GaN quantum dots. Collaborative Conference on Interacting Nanostructures CCIN'09, San Diego, CA, USA (2009)
Marquardt, O.; Hickel, T.; Neugebauer, J.: Application of an eight-band k.p model to study III-nitride semiconductor. DPG Spring Meeting 2009, Dresden, Germany (2009)
Marquardt, O.; Hickel, T.; Neugebauer, J.: Investigation of group III-nitride semiconductor nanostructures using an eight-band k.p formalism. APS March meeting, Pittsburgh, PA, USA (2009)
Marquardt, O.; Hickel, T.; Neugebauer, J.: Modeling of electronic and optical properties of GaN/AlN quantum dots by using the k.p-method. Bremen DFG Forschergruppe: Workshop in Riezlern, Riezlern, Austria (2008)
Marquardt, O.; Hickel, T.; Neugebauer, J.: Effect of strain and polarization on the electronic properties of 2-, 1- and 0-dimensional semiconductor nanostructures. Computational Materials Science Workshop, Ebernburg Castle, Germany (2008)
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
Crystal Plasticity (CP) modeling [1] is a powerful and well established computational materials science tool to investigate mechanical structure–property relations in crystalline materials. It has been successfully applied to study diverse micromechanical phenomena ranging from strain hardening in single crystals to texture evolution in…
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.