Dutta, B.; Hickel, T.; Neugebauer, J.: Finite temperature excitation mechanisms and their coupling in magnetic shape memory alloys. The Materials Research Centre (MRC), Indian Institute of Science (IISc), Bangalore, India (2017)
Neugebauer, J.: From Semiconductors to High-Strength Steels and Back Again. 10 years of the Laboratory for Photovoltaics & Semiconductor Physics, Luxembourg, Luxembourg (2017)
Dutta, B.; Begum, V.; Hickel, T.; Neugebauer, J.: Impact of doping on the magnetic and structural transformations in magnetocaloric materials. DPG Spring Meeting of the Condensed Matter Section, Dresden, Germany (2017)
Dutta, B.; Hickel, T.; Neugebauer, J.: Ab initio modelling of phase diagrams in magnetic Heusler alloys: achievements and future challenges. SUSTech Global Scientists Forum, Shenzhen, China (2017)
Neugebauer, J.: Solvent-controlled single atom dissolution, surface alloying and Wulff shapes of nanoclusters; Electrocatalysis at electrocodes in the dry. Workshop: Research Area III, ZEMOS, Bochum, Germany (2016)
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
Ever since the discovery of electricity, chemical reactions occurring at the interface between a solid electrode and an aqueous solution have aroused great scientific interest, not least by the opportunity to influence and control the reactions by applying a voltage across the interface. Our current textbook knowledge is mostly based on mesoscopic…
Recent developments in experimental techniques and computer simulations provided the basis to achieve many of the breakthroughs in understanding materials down to the atomic scale. While extremely powerful, these techniques produce more and more complex data, forcing all departments to develop advanced data management and analysis tools as well as…
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.
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.