4 papers
An Ontology for Machine Learning Interatomic Potentials
Daniel Hernández, Jong Hyun Jung, Yuji Ikeda +11
Machine learning interatomic potentials (MLIPs) approximate quantum-mechanical energies and forces---conventionally computed by density functional theory (DFT) or wave-function met…
Temperature dependence of the Gibbs energies of formation of point defects in B2 MoTa from ab initio calculations
Xiang Xu, Fritz Körmann, Sergiy Divinski +2
Using B2 MoTa, the strongest B2 former among group V/VI refractory binaries, as a model system, we compute temperature-dependent Gibbs energies of formation of vacancies and antisi…
Lattice distortions and non-sluggish diffusion in BCC refractory high entropy alloys
Jingfeng Zhang, Xiang Xu, Fritz Körmann +10
Refractory high-entropy alloys (RHEAs) have emerged as promising candidates for extreme high-temperature applications, for example, in next-generation turbines and nuclear reactors…
Accurate complex-stacking-fault Gibbs energy in Ni3Al at high temperatures
Xiang Xu, Xi Zhang, Andrei Ruban +2
To gain a deeper insight into the anomalous yield behavior of Ni3Al, it is essential to obtain temperature-dependent formation Gibbs energies of the relevant planar defects. Here,…