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
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…
The project’s goal is to synergize experimental phase transformations dynamics, observed via scanning transmission electron microscopy, with phase-field models that will enable us to learn the continuum description of complex material systems directly from experiment.
In order to prepare raw data from scanning transmission electron microscopy for analysis, pattern detection algorithms are developed that allow to identify automatically higher-order feature such as crystalline grains, lattice defects, etc. from atomically resolved measurements.
The general success of large language models (LLM) raises the question if they could be applied to accelerate materials science research and to discover novel sustainable materials. Especially, interdisciplinary research fields including materials science benefit from the LLMs capability to construct a tokenized vector representation of a large…