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Latest additions: 2021-01-07 22:33 PDF PhysRevMaterials.4.103601 Machine learning for metallurgy I. A neural-network potential for Al-Cu Marchand, Daniel John Gilles ; Jain, Abhinav ; Glensk, Albert ; Curtin, William Physical Review Materials, 4 (10), 103601 (2020) 01 October 2020 | Journal Articles | Detailed record - Similar records 2020-12-22 21:01 PDF disl_core_en_ddd_postprint Atomistic dislocation core energies and calibration of non-singular discrete dislocation dynamics Hu, Yi ; Szajewski, B A ; Rodney, D ; Curtin, W A Modelling and Simulation in Materials Science and Engineering, 28 (1), 015005 (2019) 28 November 2019 | Journal Articles | Detailed record - Similar records 2020-12-22 10:11 PDF Prismatic Slip in Magnesium Stricker, Markus Anthony ; Curtin, William Journal of Physical Chemistry C, 124 (49), 27230-27240 (2020) 23 November 2020 | Journal Articles | Detailed record - Similar records 2020-12-07 17:47 PDF 1-s2.0-S1359645420307643-main First principles study of the effect of hydrogen in austenitic stainless steels and high entropy alloys Zhou, Xiao ; Curtin, William Acta Materialia, 200, 932-942 (2020) 28 September 2020 | Journal Articles | Detailed record - Similar records 2020-12-02 02:23 Measurement and prediction of the transformation strain that controls ductility and toughness in advanced steels Maresca, Francesco ; Polatidis, Efthymios ; Smid, Miroslav ; Van Swygenhoven, Helena[...] Acta Materialia, 200, 246-255 (2020) 01 November 2020 | Journal Articles | Detailed record - Similar records 2020-12-02 02:23 Effect of solute-solute interactions on strengthening of random alloys from dilute to high entropy alloys Nag, Shankha ; Curtin, William A. Acta Materialia, 200, 659-673 (2020) 01 November 2020 | Journal Articles | Detailed record - Similar records 2020-11-13 08:50 PDF EPFL_TH7447 Concurrent multiscale modeling and theory of solute-strengthening for dilute and complex concentrated alloys Nag, Shankha ; Curtin, William 2020 | Theses | Detailed record - Similar records 2020-11-05 02:22 PDF StrickerYinMakCurtin_MLMetall2_v5 Machine learning for metallurgy II. A neural-network potential for magnesium Stricker, Markus ; Yin, Binglun ; Mak, Eleanor ; Curtin, W. A. Physical Review Materials, 4 (10), 103602 (2020) 01 October 2020 | Journal Articles | Detailed record - Similar records 2020-10-16 10:25 PDF EPFL_TH8232 Atomic Scale Investigations into the Origins of Ductility in Mg Alloys Ahmad, Rasool ; Curtin, William 2020 | Theses | Detailed record - Similar records 2020-10-11 02:24 Improved thermal stability and fast phase change speed of Y-doped Sb7Se3 thin film for phase change memory applications Liu, Ruirui ; Hu, Anya ; Zhao, Zihan ; Zhou, Haitao[...] Applied Surface Science, 532, 147370 (2020) 01 December 2020 | Journal Articles | Detailed record - Similar records [>> more]