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Predicting grain boundary segregation in magnesium alloys: An atomistically informed machine learning approach2025 Journal of Magnesium and Alloys article Materials Science Magnesium Alloys: Properties and Applications Open access
Zhuocheng Xie, Achraf Atila, Julien Guénolé, Sandra Korte‐Kerzel, Talal Al‐Samman, U. Kerzel
9citations -
Unravelling the Interplay between Degradation and Impedance through Physical Modeling – a White Box Approach2025 ECS Meeting Abstracts conference-abstract Materials Science Advancements in Solid Oxide Fuel Cells
Marisa Knappe, Thomas Kadyk, Andrei A. Kulikovsky, Michael Hermann Eikerling
0citations -
Influence of synthetically generated inclusions on the stress accumulation and concentration in X65 pipeline steel2021 IOP Conference Series Materials Science and Engineering conference-paper Materials Science Machine Learning in Materials Science Open access
Niklas C. Fehlemann, Yannik Sparrer, Felix Pütz, Markus Könemann, Sebastian Münstermann
11citations -
Compression and Ordering of Microgels in Monolayers Formed at Liquid–Liquid Interfaces: Computer Simulation Studies2020 ACS Applied Materials & Interfaces article Materials Science Pickering emulsions and particle stabilization
Nikita V. Bushuev, Rustam A. Gumerov, Steffen Bochenek, Andrij Pich, Walter H. Richtering, Igor I. Potemkin
26citations -
Vertical structure of Sb-intercalated quasifreestanding graphene on SiC(0001)2022 Physical review. B./Physical review. B article Materials Science Graphene research and applications Open access
You-Ron Lin, Susanne Wolff, Philip Schädlich, Mark Hutter, Serguei Soubatch, Tien‐Lin Lee, +4 more
14citations -
Predicting Grain Boundary Segregation in Magnesium Alloys: An Atomistically Informed Machine Learning Approach2024 RWTH Publications (RWTH Aachen) article Materials Science Magnesium Alloys: Properties and Applications Open access
Zhuocheng Xie, Achraf Atila, Julien Guénolé, Sandra Korte‐Kerzel, Talal Al‐Samman, U. Kerzel
2citations
16 results