Steingrimsson, B, Fan, X, Adam, BM, and Liaw, PK. Physics-assisted machine-learning approach for modeling the temperature-dependent ultimate strengths of superalloys, with comparison to medium- and high-entropy alloys. Retrieved from https://par.nsf.gov/biblio/10649419. Materials Chemistry and Physics 340.C Web. doi:10.1016/j.matchemphys.2025.130618.

Steingrimsson, B, Fan, X, Adam, BM, & Liaw, PK. Physics-assisted machine-learning approach for modeling the temperature-dependent ultimate strengths of superalloys, with comparison to medium- and high-entropy alloys. Materials Chemistry and Physics, 340 (C). Retrieved from https://par.nsf.gov/biblio/10649419. https://doi.org/10.1016/j.matchemphys.2025.130618

Steingrimsson, B, Fan, X, Adam, BM, and Liaw, PK. "Physics-assisted machine-learning approach for modeling the temperature-dependent ultimate strengths of superalloys, with comparison to medium- and high-entropy alloys". Materials Chemistry and Physics 340 (C). Country unknown/Code not available: Elsevier. https://doi.org/10.1016/j.matchemphys.2025.130618. https://par.nsf.gov/biblio/10649419.

@article{osti_10649419,
place = {Country unknown/Code not available}, title = {Physics-assisted machine-learning approach for modeling the temperature-dependent ultimate strengths of superalloys, with comparison to medium- and high-entropy alloys}, url = {https://par.nsf.gov/biblio/10649419}, DOI = {10.1016/j.matchemphys.2025.130618}, abstractNote = {Not Available}, journal = {Materials Chemistry and Physics}, volume = {340}, number = {C}, publisher = {Elsevier}, author = {Steingrimsson, B and Fan, X and Adam, BM and Liaw, PK}, }