Mozafari, E.; Alling, B.; Belov, M. P.; Abrikosov, I. A.: Effect of the lattice dynamics on the electronic structure of paramagnetic NiO within the disordered local moment picture. Physical Review B 97 (3), 035152 (2018)
Mozafari, E.; Shulumba, N.; Steneteg, P.; Alling, B.; Abrikosov, I. A.: Finite-temperature elastic constants of paramagnetic materials within the disordered local moment picture from ab initio molecular dynamics calculations. Physical Review B 94 (5), 054111 (2016)
Sangiovanni, D. G.; Hellman, O.; Alling, B.; Abrikosov, I. A.: Efficient and accurate determination of lattice-vacancy diffusion coefficients via non equilibrium ab initio molecular dynamics. Physical Review B 93 (9), 094305 (2016)
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
Atom probe tomography (APT) provides three dimensional(3D) chemical mapping of materials at sub nanometer spatial resolution. In this project, we develop machine-learning tools to facilitate the microstructure analysis of APT data sets in a well-controlled way.