MENON, Sarath, LYSOGORSKIY, Yury, KNOLL, Alexander L. M., LEIMEROTH, Niklas, POUL, Marvin, QAMAR, Minaam, JANSSEN, Jan, MROVEC, Matous, ROHRER, Jochen, ALBE, Karsten, BEHLER, Jörg, DRAUTZ, Ralf und NEUGEBAUER, Jörg, 2024. From electrons to phase diagrams with machine learning potentials using pyiron based automated workflows. npj computational materials. 2024. No. Band 10 (2024), Artikel-ID: 261, p. , Artikel-ID: 261. DOI 10.1038/s41524-024-01441-0.
Elsevier - Harvard (with titles)Menon, S., Lysogorskiy, Y., Knoll, A.L.M., Leimeroth, N., Poul, M., Qamar, M., Janssen, J., Mrovec, M., Rohrer, J., Albe, K., Behler, J., Drautz, R., Neugebauer, J., 2024. From electrons to phase diagrams with machine learning potentials using pyiron based automated workflows. npj computational materials , Artikel-ID: 261. https://doi.org/10.1038/s41524-024-01441-0
American Psychological Association 7th editionMenon, S., Lysogorskiy, Y., Knoll, A. L. M., Leimeroth, N., Poul, M., Qamar, M., Janssen, J., Mrovec, M., Rohrer, J., Albe, K., Behler, J., Drautz, R., & Neugebauer, J. (ca. 2024). From electrons to phase diagrams with machine learning potentials using pyiron based automated workflows [Electronic]. npj computational materials, Band 10 (2024), Artikel-ID: 261, , Artikel-ID: 261. https://doi.org/10.1038/s41524-024-01441-0
Springer - Basic (author-date)Menon S, Lysogorskiy Y, Knoll ALM, Leimeroth N, Poul M, Qamar M, Janssen J, Mrovec M, Rohrer J, Albe K, Behler J, Drautz R, Neugebauer J (2024) From electrons to phase diagrams with machine learning potentials using pyiron based automated workflows. npj computational materials , Artikel-ID: 261. https://doi.org/10.1038/s41524-024-01441-0
Juristische Zitierweise (Stüber) (Deutsch)Menon, Sarath/ Lysogorskiy, Yury/ Knoll, Alexander L. M./ Leimeroth, Niklas/ Poul, Marvin/ Qamar, Minaam/ Janssen, Jan/ Mrovec, Matous/ Rohrer, Jochen/ Albe, Karsten/ Behler, Jörg/ Drautz, Ralf/ Neugebauer, Jörg, From electrons to phase diagrams with machine learning potentials using pyiron based automated workflows, npj computational materials 2024, , Artikel-ID: 261.