Abu-Farsakh, H.; Neugebauer, J.: Enhancing nitrogen solubility in GaAs and InAs by surface kinetics: An ab initio study. Physical Review B 79, 155311, pp. 155311 - 155323 (2009)
Abu-Farsakh, H.; Neugebauer, J.: Exploring the unusual diffusion of N adatoms on GaAs(001) using first principles calculations. DPG Frühjahrstagung 2010, Regensburg, Germany (2010)
Abu-Farsakh, H.; Neugebauer, J.: Exploring the unusual diffusion of N adatoms at GaAs(001) surface. Computational Materials Science on Complex Energy Landscapes Workshop, Imst, Austria (2010)
Abu-Farsakh, H.; Neugebauer, J.: Enhancing N solubility in diluted nitrides by surface kinetics: An ab-initio study. Spring meeting of the German Physical Society (DPG), Berlin, Germany (2008)
Abu-Farsakh, H.; Neugebauer, J.: Ab-initio study of the thermodynamics and kinetics of N at GaAs(001) surface. PAW workshop 2007, Goslar, Germany (2007)
Abu-Farsakh, H.; Neugebauer, J.: In-N anti-correlation in InGaAsN alloys: The delicate interplay between adatom thermodynamics and kinetics. Spring meeting of the German Physical Society (DPG), Regensburg, Germany (2007)
Abu-Farsakh, H.; Neugebauer, J.: Tailoring the N-solubility in InGaAs-alloys by surface engineering: Applications and limits. 1. Harzer Ab initio Workshop, Clausthal, Germany (2006)
Abu-Farsakh, H.; Neugebauer, J.: Incorporation of N at GaAs and InAs surfaces: An ab-initio study. Technische Universität Berlin, Berlin, Germany (2006)
Abu-Farsakh, H.; Dick, A.; Neugebauer, J.: Incorporation of N at GaAs and InAs surfaces. Deutsche Physikalische Gesellschaft Spring Meeting of the Division Condensed Matter, Dresden, Germany (2006)
Abu-Farsakh, H.; Neugebauer, J.: Combined ab-initio and Monte Carlo calculations to explore the surface thermodynamics and kinetics of dilute nitrides. 8th International Conference on Nitride Semiconductors (ICNS-8), Jeju Island, South Korea (2009)
Abu-Farsakh, H.; Neugebauer, J.: The role of surface kinetics in achieving high non-equilibrium N concentrations in bulk GaAs. DPG Spring Meeting 2009, Dresden, Germany (2009)
Abu-Farsakh, H.; Neugebauer, J.; Albrecht, M.: Ab-initio study of compositional anti-correlation of In and N in InGaAsN alloys. The 7th International Conference of Nitride Semiconductors (ICNS-7), Las Vegas, NV, USA (2007)
Abu-Farsakh, H.; Neugebauer, J.: Enhancing the solubility of N in GaAs and InAs by surface kinetics. 28th International Conference on the Physics of Semiconductors, Vienna, Austria (2006)
Abu-Farsakh, H.; Neugebauer, J.: Enhancing bulk solubility by surface engineering: An ab-initio study. Workshop: Ab initio Description of Iron and Steel, Status and future challenges, Ringberg Castle, Germany (2006)
Abu-Farsakh, H.: Understanding the interplay between thermodynamics and surface kinetics in the growth of dilute nitride alloys from first principles. Dissertation, University of Paderborn, Paderborn, Germany (2010)
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.
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…
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.