Todorova, M.: Stability and reactivity of solid/liquid interfaces from ab initio calculations. International Workshop on Computational Electrochemistry, Aalto University, Helsinki, Finland (2018)
Todorova, M.: Insights into electrochemical problems from the perspective of semiconductor defect chemistry. International Workshop on Computational Electrochemistry, Aalto University, Helsinki, Finland (2018)
Todorova, M.: Atomistic insights into surface stability and reactivity at solid/liquid interfaces from first principles calculations. Technical University Vienna, Vienna, Austria (2018)
Todorova, M.: Selective stabilization of polar oxide surfaces in electrochemical environment. Workshop: The Electrode Potential in Electrochemistry - A Challenge for Electronic Structure Theory Calculations, Schloß Reisensburg, Günzburg, Germany (2017)
Todorova, M.: Free energy sampling for electrochemical systems. Workshop II: Stochastic Sampling and Accelerated Time Dynamics on Multidimensional Surfaces, IPAM, UCLA, Los Angeles, CA, USA (2017)
Todorova, M.: Ab-initio modelling of electrochemical processes: Challenges and insights. Workshop: Fundamental Electrochemistry: Theory Meets Experiment, Leiden, The Netherlands (2017)
Todorova, M.: From semiconductor defect chemistry to electrochemistry: Insight into corrosion mechanisms from ab initio concepts. 57 Sanibel Symposium, St. Simon Island, GA, USA (2017)
Todorova, M.: From semiconductor defect chemistry to electrochemistry: Gaining new insights from computational physics tools. ICCP10 Conference , Macao, China (2017)
Todorova, M.: Oxide stability and defect chemistry in an electrochemical environment: an ab initio perspective. Workshop 2016 der DFG-Forschergruppe 1376 “Elementary reaction steps in electrocatalysis: Theory meets experiment“, Reisensburg, Günzburg, Germany (2016)
Surendralal, S.; Todorova, M.; Neugebauer, J.: Automated calculations for charged point defects in MgO and α-Fe2O3. DPG-Frühjahrstagung 2016, Regensburg, Germany (2016)
Vatti, A. K.; Todorova, M.; Neugebauer, J.: Ab initio Determination of Formation Energies and Charge Transfer Levels of Charged Ions in Water. APS 2016, Baltimore, MD, USA (2016)
Vatti, A. K.; Todorova, M.; Neugebauer, J.: Formation Energy of Ions in Water using ab-initio Molecular Dynamics. DPG Frühjahrstagung 2016, Regensburg, Germany (2016)
Todorova, M.: Electrochemistry from the perspective of semiconductor defect chemistry: New tools and insights. Psi-k Conference, San Sebastian, Spain (2015)
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
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…
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…