Dsouza, R.; Huber, L.; Grabowski, B.; Neugebauer, J.: Approximating the impact of nuclear quantum effects on thermodynamic properties of crystalline solids by temperature remapping. Physical Review B 105 (18), 184111 (2022)
Mendive-Tapia, E.; Neugebauer, J.; Hickel, T.: Ab initio calculation of the magnetic Gibbs free energy of materials using magnetically constrained supercells. Physical Review B 105 (16), 064425 (2022)
Sreekala, L.; Dey, P.; Hickel, T.; Neugebauer, J.: Unveiling nonmonotonic chemical trends in the solubility of H in complex Fe–Cr–Mn carbides by means of ab initio based approaches. Physical Review Materials 6 (1), 014403 (2022)
Freysoldt, C.; Neugebauer, J.; Tan, A. M. Z.; Hennig, R. G.: Limitations of empirical supercell extrapolation for calculations of point defects in bulk, at surfaces, and in two-dimensional materials. Physical Review B 105 (1), 014103 (2022)
Alam, M.; Lymperakis, L.; Groh, S.; Neugebauer, J.: MEAM interatomic potentials of Ni, Re, and Ni–Re alloys for atomistic fracture simulations. Modelling and Simulation in Materials Science and Engineering 30 (1), 015002 (2021)
Wang, N.; Freysoldt, C.; Zhang, S.; Liebscher, C.; Neugebauer, J.: Segmentation of Static and Dynamic Atomic-Resolution Microscopy Data Sets with Unsupervised Machine Learning Using Local Symmetry Descriptors. Microscopy and Microanalysis 27 (6), pp. 1454 - 1464 (2021)
Surendralal, S.; Todorova, M.; Neugebauer, J.: Impact of Water Coadsorption on the Electrode Potential of H–Pt(1 1 1)-Liquid Water Interfaces. Physical Review Letters 126 (16), 166802 (2021)
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
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…
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…
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…
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…
Statistical significance in materials science is a challenge that has been trying to overcome by miniaturization. However, this process is still limited to 4-5 tests per parameter variance, i.e. Size, orientation, grain size, composition, etc. as the process of fabricating pillars and testing has to be done one by one. With this project, we aim to…