Can unsupervised machine learning boost the on-site analysis of in situ synchrotron diffraction data?

Strohmann, T. (Corresponding author); Barriobero-Vila, P.; Gussone, J.; Melching, D.; Stark, A.; Schell, N.; Requena, Guillermo

Amsterdam [u.a.] : Elsevier Science (2022, 2023)
Journal Article

In: Scripta materialia
Volume: 226
Page(s)/Article-Nr.: 115238

Institutions

• Division of Materials Science and Engineering [520000]
• Metallic Structures and Material Systems for Aviation and Astronautics Teaching and Research Area [521420]