@misc{indiciae035bb4e95431,
  title = {Application-specific machine-learned interatomic potentials: exploring the trade-off between DFT convergence, MLIP expressivity, and computational cost},
  author = {Baghishov, Ilgar Intizam Oglu [Los Alamos National Laboratory (LANL), Los Alamos, NM (United States); Univ. of Texas, Austin, TX (United States)] (ORCID:000000024802842X) and Janssen, Jan [Los Alamos National Laboratory (LANL), Los Alamos, NM (United States); Max Planck Institute for Sustainable Materials (Germany)] (ORCID:0000000199487119) and Henkelman, Graeme [Univ. of Texas, Austin, TX (United States)] (ORCID:0000000203367153) and Perez, Danny [Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)] (ORCID:0000000330285249)},
  year = {2025},
  doi = {10.1039/d5dd00294j},
  url = {https://www.osti.gov/biblio/3015170},
  note = {Source identifier: 3015170}
}