Freysoldt, C.: Die S/PHI/nX-Klassenbibliothek - HPC-Programmierung für Physiker. Workshop "High-performance computing und datengetriebene Anwendungen in der MPG
, Ringberg, Germany (2014)
Freysoldt, C.; Neugebauer, J.: Point defects in supercells: Correction schemes for the dilute limit. Workshop on Ab-initio description of charged systems and solid/liquid
interfaces
, Santa Barbara, CA, USA (2014)
Freysoldt, C.; Pfanner, G.; Neugebauer, J.: Role of the defect creation strategy for modelling dangling bonds in a-Si:H. MRS Spring Meeting, San Francisco, CA, USA (2014)
Freysoldt, C.; Pfanner, G.; Neugebauer, J.: Defects in amorphous silicon from H insertion. Workshop "Spins as Functional Probes in Solar Energy Research", Berlin, Germany (2013)
Lips, K.; Fehr, M.; Schnegg, A.; Rech, B.; Astakhov, O.; Finger, F.; Pfanner, G.; Freysoldt, C.; Neugebauer, J.; Bittl, R.et al.; Teutloff, C.: The Staebler-Wronski Effect in a-Si:H Revisited with Advanced Electron Paramagnetic Resonance (EPR). MRS Spring Meeting, San Francisco, CA, USA (2012)
Pfanner, G.; Freysoldt, C.; Neugebauer, J.: The Dangling-bond Defect in Crystalline and Amorphous Silicon: Insights from Ab initio Calculations of EPR-parameters. MRS Spring Meeting, San Francisco, CA, USA (2012)
Pfanner, G.; Freysoldt, C.; Neugebauer, J.: The dangling-bond defect in amorphous silicon: Insights from ab initio calculations of EPR parameters. DPG Frühjahrstagung 2012, Berlin, Germany (2012)
Pfanner, G.; Freysoldt, C.; Neugebauer, J.: The dangling-bond defect in amorphous silicon: Insights from ab initio calculations of EPR parameters. 1st Austrian-German workshop on computational materials design, Kramsach, Austria (2012)
Freysoldt, C.: Charge corrections in supercells. Workshop on "Modern developments in the ab initio description of charged systems for semiconductors and electrochemistry, Ringberg, Germany (2012)
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)
Freysoldt, C.; Pfanner, G.; Neugebauer, J.: The dangling-bond defect in amorphous silicon: Insights from theoretical calculations of the EPR parameters. Workshop on Advanced EPR for material and solar energy research, Berlin, Germany (2011)
Freysoldt, C.; Pfanner, G.; Neugebauer, J.: The Dangling-Bond Defect in Amorphous Silicon: Statistical Random Versus Kinetically Driven Defect Geometries. 24th International Conference on Amorphous and Nanocrystalline Semiconductors (ICANS 24), Nara, Japan (2011)
Fehr, M.; Schnegg, A.; Teutloff, C.; Bittl, R.; Astakhov, O.; Finger, F.; Pfanner, G.; Freysoldt, C.; Neugebauer, J.; Rech, B.et al.; Lips, K.: A Detailed Investigation of Native and Light-induced Defects in Hydrogenated Amorphous Silicon by Electron-spin Resonance. MRS Spring Meeting and Exhibit 2011, San Francisco, CA, USA (2011)
Pfanner, G.; Freysoldt, C.; Neugebauer, J.: EPR parameters of the dangling bond defect in crystalline and amorphous silion: A DFT-study. APS march meeting 2011, Dallas, TX, USA (2011)
Pfanner, G.; Freysoldt, C.; Neugebauer, J.: EPR parameters of the dangling bond defect in crystalline and amorphous silion: A DFT-study. DPG spring meeting 2011, Dresden, Germany (2011)
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
Integrated Computational Materials Engineering (ICME) is one of the emerging hot topics in Computational Materials Simulation during the last years. It aims at the integration of simulation tools at different length scales and along the processing chain to predict and optimize final component properties.
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…