507 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of FreiburgDE49 papers
- Karlsruhe Institute of TechnologyDE19 papers
- Forschungszentrum JülichDE5 papers
- Johns Hopkins UniversityUS4 papers
- Technische Universität DarmstadtDE4 papers
- University of CambridgeGB4 papers
- Fraunhofer Institute for Industrial MathematicsDE3 papers
- RWTH Aachen UniversityDE3 papers
- University of RegensburgDE3 papers
- Arizona State UniversityUS2 papers
- Fraunhofer Institute for Applied Solid State PhysicsDE2 papers
- Innovation Cluster (Canada)CA2 papers
5 papers · 1 filter
Compressive Behavior and Failure Mechanisms of Freestanding and Composite 3D Graphitic Foams
Kenichi Nakanishi, Adrianus I. Aria, Matthew Berwind +4
Open-cell graphitic foams were fabricated by chemical vapor deposition using nickel templates and their compressive responses were measured over a range of relative densities. The…
{110} planar faults in strained bcc metals: Origins and implications of a commonly observed artifact of classical potentials
Johannes J. Möller, Matous Mrovec, Ivan Bleskov +6
Large-scale atomistic simulations with classical potentials can provide valuable insights into microscopic deformation mechanisms and defect-defect interactions in materials. Unfor…
Ab-initio wave-length dependent Raman spectra: Placzek approximation and beyond
Michael Walter, Michael Moseler
We analyze how to obtain non-resonant and resonant Raman spectra within the Placzek as well as the Albrecht approximation. Both approximations are derived from the matrix element f…
Charge transfer excitations with range separated functionals using improved virtual orbitals
Rolf Würdemann, Michael Walter
We present an implementation of range separated functionals utilizing the Slater-function on grids in real space in the projector augmented waves method. The screened Poisson equat…
Compositional optimization of hard-magnetic phases with machine-learning models
Johannes J. Möller, Wolfgang Körner, Georg Krugel +2
Machine Learning (ML) plays an increasingly important role in the discovery and design of new materials. In this paper, we demonstrate the potential of ML for materials research us…