![[Translate to English:] Best-Paper-Award MDPI-Lubricants Max Marian](/typo3temp/assets/_processed_/d/0/csm_0ca71e7411164f4b148e25d295f6fc68c8264e57-fp-16-9-0-0_134608b395.png)
![[Translate to English:] Best-Paper-Award MDPI-Lubricants Max Marian](/typo3temp/assets/_processed_/d/0/csm_0ca71e7411164f4b148e25d295f6fc68c8264e57-fp-16-9-0-0_321bc69328.png)
![[Translate to English:] Best-Paper-Award MDPI-Lubricants Max Marian](/typo3temp/assets/_processed_/d/0/csm_0ca71e7411164f4b148e25d295f6fc68c8264e57-fp-16-9-0-0_8771d5a93c.png)
The article “Physics-Informed Machine Learning—An Emerging Trend in Tribology,” authored by IMKT professor Max Marian together with Prof. Dr.-Ing. Stephan Tremmel (Chair of Engineering Design and CAD, University of Bayreuth), has been awarded the prestigious Best Paper Award by the journal MDPI Lubricants:
www.mdpi.com/journal/lubricants/awards/3099
This award recognizes outstanding scientific quality, innovation, and broad relevance in tribology research. The winning review article highlights the potential of physics-informed machine learning for addressing complex challenges related to friction, wear, and lubrication. By combining physical models with state-of-the-art AI methods, this approach opens up entirely new avenues for the analysis and optimization of tribological systems.
We would like to extend our sincere thanks to the award committee and to everyone involved!
Link to the publication:
