29 citations · 39 across the 4 of their papers we have counts for
4 papers
High- and medium-entropy nitride coatings from the Cr-Hf-Mo-Ta-W-N system: properties and high-temperature stability
Pavel Souček, Stanislava Debnárová, Šárka Zuzjaková +9
High- and medium-entropy nitride coatings from the Cr-Hf-Mo-Ta-W-N system were studied using ab initio calculations and experiments to clarify the role of entropy and individual el…
Machine-learning potentials for structurally and chemically complex MAB phases: strain hardening and ripplocation-mediated plasticity
Nikola Koutná, Shuyao Lin, Lars Hultman +2
Though offering unprecedented pathways to molecular dynamics (MD) simulations of technologically-relevant materials and conditions, machine-learning interatomic potentials (MLIPs)…
Machine-Learning Potentials Predict Orientation- and Mode-Dependent Fracture in Refractory Diborides
Shuyao Lin, Zhuo Chen, Rebecca Janknecht +5
Fracture toughness () and fracture strength () are key criteria in the selection and design of reliable ceramics. However, their experimental character…
Machine-learning potentials for nanoscale simulations of deformation and fracture: example of TiB ceramic
Shuyao Lin, Luis Casillas-Trujillo, Ferenc Tasnádi +4
Machine-learning interatomic potentials (MLIPs) offer a powerful avenue for simulations beyond length and timescales of ab initio methods. Their development for investigation of me…