Tillack, N.; Hickel, T.; Raabe, D.; Neugebauer, J.: Kinetic Monte Carlo simulations and ab initio studies of nano-precipitation in ferritic steels. Computational Materials Science on Complex Energy Landscapes Workshop, Imst, Austria (2010)
Tillack, N.; Yates, J. R.; Roberts, S. G.; Hickel, T.; Drautz, R.; Neugebauer, J.: First-Principles Investigations of ODS Steels. Ab initio Description of Iron and Steel: Thermodynamics and Kinetics, Tegernsee, Germany (2012)
Tillack, N.; Hickel, T.; Raabe, D.; Neugebauer, J.: Ab initio study of nano-precipitate nucleation and growth in ferritic steels. Psi-k/CECAM/CCP9 Biennial Graduate School in Electronic-Structure Methods, Oxford, UK (2011)
Tillack, N.; Hickel, T.; Raabe, D.; Neugebauer, J.: Ab initio study of nano-precipitate nucleation and growth in ferritic steels. Materials Discovery by Scale-Bridging High-Throughput Experimentation and Modelling, Ruhr-Universität Bochum, Bochum, Germany (2010)
Tillack, N.; Hickel, T.; Raabe, D.; Neugebauer, J.: Ab initio and kinetic Monte-Carlo study of nano-precipitate nucleation and growth in ferritic steels. Materials Discovery by Scale-Bridging High-Throughput Experimentation and Modelling, Bochum, Germany (2010)
Tillack, N.; Hickel, T.; Raabe, D.; Neugebauer, J.: Kinetic Monte Carlo and ab initio study of nano-precipitates and growth in ferritic steels. Ab Initio Description of Iron and Steel: Mechanical Properties, Tegernsee, Germany (2010)
Tillack, N.; Hickel, T.; Raabe, D.; Neugebauer, J.: Combined ab initio studies and kinetic Monte Carlo simulations of nano-precipitation in ferritic steels. Summer School: Computational Materials Science, San Sebastian, Spain (2010)
Tillack, N.: Chemical Trends in the Yttrium-Oxide Precipitates in Oxide Dispersion Strengthened Steels: A First-Principles Investigation. Master, Ruhr-Universität Bochum, Bochum, Germany (2012)
Max Planck scientists design a process that merges metal extraction, alloying and processing into one single, eco-friendly step. Their results are now published in the journal Nature.
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
This project will aim at developing MEMS based nanoforce sensors with capacitive sensing capabilities. The nanoforce sensors will be further incorporated with in situ SEM and TEM small scale testing systems, for allowing simultaneous visualization of the deformation process during mechanical tests
The utilization of Kelvin Probe (KP) techniques for spatially resolved high sensitivity measurement of hydrogen has been a major break-through for our work on hydrogen in materials. A relatively straight forward approach was hydrogen mapping for supporting research on hydrogen embrittlement that was successfully applied on different materials, and…
It is very challenging to simulate electron-transfer reactions under potential control within high-level electronic structure theory, e. g. to study electrochemical and electrocatalytic reaction mechanisms. We develop a novel method to sample the canonical NVTΦ or NpTΦ ensemble at constant electrode potential in ab initio molecular dynamics…
Photovoltaic materials have seen rapid development in the past decades, propelling the global transition towards a sustainable and CO2-free economy. Storing the day-time energy for night-time usage has become a major challenge to integrate sizeable solar farms into the electrical grid. Developing technologies to convert solar energy directly into…
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…