Zhou, Xuyang, Wei, Ye, Kühbach, Markus, Zhao, Huan, Vogel, Florian, Darvishi Kamachali, Reza, Thompson, Gregory B., Raabe, Dierk, and Gault, Baptiste. Revealing in-plane grain boundary composition features through machine learning from atom probe tomography data. Retrieved from https://par.nsf.gov/biblio/10378949. Acta Materialia 226.C Web. doi:10.1016/j.actamat.2022.117633.

Zhou, Xuyang, Wei, Ye, Kühbach, Markus, Zhao, Huan, Vogel, Florian, Darvishi Kamachali, Reza, Thompson, Gregory B., Raabe, Dierk, & Gault, Baptiste. Revealing in-plane grain boundary composition features through machine learning from atom probe tomography data. Acta Materialia, 226 (C). Retrieved from https://par.nsf.gov/biblio/10378949. https://doi.org/10.1016/j.actamat.2022.117633

Zhou, Xuyang, Wei, Ye, Kühbach, Markus, Zhao, Huan, Vogel, Florian, Darvishi Kamachali, Reza, Thompson, Gregory B., Raabe, Dierk, and Gault, Baptiste. "Revealing in-plane grain boundary composition features through machine learning from atom probe tomography data". Acta Materialia 226 (C). Country unknown/Code not available. https://doi.org/10.1016/j.actamat.2022.117633. https://par.nsf.gov/biblio/10378949.

@article{osti_10378949,
place = {Country unknown/Code not available}, title = {Revealing in-plane grain boundary composition features through machine learning from atom probe tomography data}, url = {https://par.nsf.gov/biblio/10378949}, DOI = {10.1016/j.actamat.2022.117633}, abstractNote = {}, journal = {Acta Materialia}, volume = {226}, number = {C}, author = {Zhou, Xuyang and Wei, Ye and Kühbach, Markus and Zhao, Huan and Vogel, Florian and Darvishi Kamachali, Reza and Thompson, Gregory B. and Raabe, Dierk and Gault, Baptiste}, }