Publikationen von Ye Wei

Liu, C.; Rao, J.; Sun, Z.; Lu, W.; Best, J. P.; Li, X.; Xia, W.; Gong, Y.; Wei, Y.; Zhang, B. et al.; Ding, J.; Wu, G.; Ma, E.: Near-theoretical strength and deformation stabilization achieved via grain boundary segregation and nano-clustering of solutes. Nature Communications 15, 9283 (2024)

Li, Y.; Wei, Y.; Wang, Z.; Liu, X.; Colnaghi, T.; Han, L.; Rao, Z.; Zhou, X.; Huber, L.; Dsouza, R. et al.; Gong, Y.; Neugebauer, J.; Marek, A.; Rampp, M.; Bauer, S.; Li, H.; Baker, I.; Stephenson, L.; Gault, B.: Quantitative three-dimensional imaging of chemical short-range order via machine learning enhanced atom probe tomography. Nature Communications 14 (1), 7410 (2023)

Rao, Z.; Tung, P.-Y.; Xie, R.; Wei, Y.; Zhang, H.; Ferrari, A.; Klaver, T. P. C.; Körmann, F.; Prithiv, T. S.; Kwiatkowski da Silva, A. et al.; Chen, Y.; Li, Z.; Ponge, D.; Neugebauer, J.; Gutfleisch, O.; Bauer, S.; Raabe, D.: Machine learning–enabled high-entropy alloy discovery. Science 378 (6615), S. 78 - 85 (2022)

Zhou, X.; Wei, Y.; Kühbach, M. T.; Zhao, H.; Vogel, F.; Kamachali, R. D.; Thompson, G. B.; Raabe, D.; Gault, B.: Revealing in-plane grain boundary composition features through machine learning from atom probe tomography data. Acta Materialia 226, 117633 (2022)

Han, L.; Maccari, F.; Souza Filho, I. R.; Peter, N. J.; Wei, Y.; Gault, B.; Gutfleisch, O.; Li, Z.; Raabe, D.: A mechanically strong and ductile soft magnet with extremely low coercivity. Nature 608, S. 310 - 316 (2022)

Han, L.; Rao, Z.; Souza Filho, I. R.; Maccari, F.; Wei, Y.; Wu, G.; Ahmadian, A.; Zhou, X.; Gutfleisch, O.; Ponge, D. et al.; Raabe, D.; Li, Z.: Ultrastrong and Ductile Soft Magnetic High-Entropy Alloys via Coherent Ordered Nanoprecipitates. Advanced Materials 33 (37), 2102139 (2021)

Wei, Y.; Varanasi, R. S.; Schwarz, T.; Gomell, L.; Zhao, H.; Larson, D. J.; Sun, B.; Liu, G.; Chen, H.; Raabe, D. et al.; Gault, B.: Machine-learning-enhanced time-of-flight mass spectrometry analysis. Patterns 2 (2), 100192 (2021)

Li, Y.; Zhou, X.; Colnaghi, T.; Wei, Y.; Marek, A.; Li, H.; Bauer, S.; Rampp, M.; Stephenson, L.: Convolutional neural network-assisted recognition of nanoscale L1₂ ordered structures in face-centred cubic alloys. npj Computational Materials 7 (1), 8 (2021)

Wu, G.; Balachandran, S.; Gault, B.; Xia, W.; Liu, C.; Rao, Z.; Wei, Y.; Liu, S.; Lu, J.; Herbig, M. et al.; Lu, W.; Dehm, G.; Li, Z.; Raabe, D.: Crystal–Glass High-Entropy Nanocomposites with Near Theoretical Compressive Strength and Large Deformability. Advanced Materials, 2002619 (2020)

Wei, Y.; Peng, Z.; Kühbach, M.; Breen, A. J.; Legros, M.; Larranaga, M.; Mompiou, F.; Gault, B.: 3D nanostructural characterisation of grain boundaries in atom probe data utilising machine learning methods. PLoS One 14 (11), e0225041 (2019)

Wei, Y.; Gault, B.; Varanasi, R. S.; Raabe, D.; Herbig, M.; Breen, A. J.: Machine-learning-based atom probe crystallographic analysis. Ultramicroscopy 194, S. 15 - 24 (2018)

Rao, Z.; Wei, Y.; Tung, P.-Y.; Xie, R.; Zhang, H.; Bauer, S.; Raabe, D.: Machine learning-enabled high-entropy Invar alloy discovery. Accelerated Discovery of new materials, 787 WE-Heraeus-Seminar, Physikzentrum Bad Honnef, Germany (2023)

Rao, Z.; Tung, P.-Y.; Xie, R.; Zhang, H.; Wei, Y.; Li, Z.; Gutfleisch, O.; Bauer, S.; Raabe, D.: Machine learning-enabled fast high-entropy alloy discovery - a case study on novel Invar alloys. DGM workshop:Functional High Entropy Alloys / Hochentropiefunktionswerkstoffe, Bochum, Germany (2022)

Zhou, X.; Wei, Y.; Zhao, H.; Vogel, F.; Darvishi Kamachali, R.; Thompson, G. B.; Raabe, D.; Gault, B.: Revealing in-plane grain boundary composition features through machine learning from atom probe tomography. DPG Conference 2021, Online, Germany (2021)

Wei, Y.: Machine learning methods in data-driven nanostructure analysis of materials. Dissertation, RWTH Aachen University (2021)