Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Lars J.S. Johnson"'
Autor:
Henrik Levämäki, Florian Bock, Davide G. Sangiovanni, Lars J.S. Johnson, Ferenc Tasnádi, Rickard Armiento, Igor A. Abrikosov
Data-driven approaches are becoming increasingly valuable for modern science, and they are making their way into industrial research and development (R&D). Supervised machine learning of statistical models can utilize databases of materials parameter
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::44aa43eaaeca5fa6f4e147675eca0497
http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-191645
http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-191645
Autor:
Maiara Moreno, Jon M. Andersson, Rachid M'Saoubi, Vyacheslav Kryzhanivskyy, Mats P. Johansson-Jöesaar, Lars J.S. Johnson, Magnus Odén, Lina Rogström
Publikováno v:
Wear. :204838
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::121d792b16c28b21b963321b1c4f7409
https://doi.org/10.1016/j.wear.2023.204838
https://doi.org/10.1016/j.wear.2023.204838
Autor:
Maiara Moreno, Jon M. Andersson, Mats P. Johansson-Jöesaar, Birgit E. Friedrich, Robert Boyd, Isabella C. Schramm, Lars J.S. Johnson, Magnus Odén, Lina Rogström
This study investigates the wear of W- and Mo-alloyed Ti1-x-yAlxMeyN coatings (Me = W, Mo) with x asymptotic to 0.55 and y asymptotic to 0.10 during high-speed turning of stainless steel 316L. A difference in the crater wear rate was observed between
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d0b0a6f61303464be921783ff102c5c7
http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-188414
http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-188414