@misc{indiciaeb0f6b5360093,
  title = {Deep Gaussian process-based cost-aware batch Bayesian optimization for complex materials design campaigns},
  author = {Alvi, Sk Md Ahnaf Akif [Texas A \& M Univ., College Station, TX (United States); Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)] and Vela, Brent [Texas A \& M Univ., College Station, TX (United States)] and Attari, Vahid [Texas A \& M Univ., College Station, TX (United States)] and Janssen, Jan [Max Planck Institute for Sustainable Materials, Dusseldorf (Germany)] (ORCID:0000000199487119) and Perez, Danny [Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)] (ORCID:0000000330285249) and Allaire, Douglas [Texas A \& M Univ., College Station, TX (United States)] and Arróyave, Raymundo [Texas A \& M Univ., College Station, TX (United States)]},
  year = {2026},
  doi = {10.1038/s41524-026-01981-7},
  url = {https://www.osti.gov/biblio/3028221},
  note = {Source identifier: 3028221}
}