187 citations
- Montanuniversität LeobenAT10 papers
- KTH Royal Institute of TechnologySE8 papers
- Centre National de la Recherche ScientifiqueFR5 papers
- Graz University of TechnologyAT5 papers
- Centre de Physique ThéoriqueFR4 papers
- École PolytechniqueFR4 papers
- Skolkovo Institute of Science and TechnologyRU4 papers
- University of GenevaCH4 papers
- Collège de FranceFR3 papers
- École Polytechnique Fédérale de LausanneCH3 papers
- FZU ‒ Institute of Physics of the Academy of Sciences of the Czech RepublicCZ3 papers
- Nawi GrazAT3 papers
7 papers · 1 filter
Advantages and developments of Raman spectroscopy for electroceramics
Marco Deluca, Hailong Hu, Maxim N. Popov +2
Despite being applied with success in many fields of materials science, Raman spectroscopy is not yet determinant in the study of electroceramics. Recent experimental and theoretic…
Ab initio framework for deciphering trade-off relationships in multi-component alloys
Franco Moitzi, Lorenz Romaner, Max Hodapp +2
While first-principles methods have been successfully applied to characterize individual properties of multi-principal element alloys (MPEA), their use to search for optimal trade-…
Automated atomistic simulations of dissociated dislocations with ab initio accuracy
Laura Mismetti, Max Hodapp
In (M Hodapp and A Shapeev 2020 Mach. Learn.: Sci. Technol. 1 045005), we have proposed an algorithm that fully automatically trains machine-learning interatomic potentials (MLIPs)…
Highly Conductive RuO Thin Films from Novel Facile Aqueous Chemical Solution Deposition
Martina Angermann, Georg Jakopic, Christine Prietl +3
Ruthenium dioxide (RuO) thin films were synthesized by Chemical Solution Deposition (CSD) on silicon substrates using only water and acetic acid as solvents. The microstructure…
Equivariant Tensor Network Potentials
Max Hodapp, Alexander Shapeev
Machine-learning interatomic potentials (MLIPs) have made a significant contribution to the recent progress in the fields of computational materials and chemistry due to the MLIPs'…
Evaluation of Data Augmentation and Loss Functions in Semantic Image Segmentation for Drilling Tool Wear Detection
Elke Schlager, Andreas Windisch, Lukas Hanna +3
Tool wear monitoring is crucial for quality control and cost reduction in manufacturing processes, of which drilling applications are one example. In this paper, we present a U-Net…