Publications

Benjamin Uhrich, Nils Pfeifer, Martin Schäfer, Oliver Theile, und Erhard Rahm. Physics-informed deep learning to quantify anomalies for real-time fault mitigation in 3D printing. Applied Intelligence, (54)6:4736--4755, Springer, 2024. [PUMA: topic_physchemistry area_bigdata ep imported]

Benjamin Uhrich, Tim Häntschel, Martin Schäfer, und Erhard Rahm. Neural Diffusion Graph Convolutional Network for Predicting Heat Transfer in Selective Laser Melting. International Workshop on Combinatorial Image Analysis, 150--164, 2024. [PUMA: topic_physchemistry area_bigdata ep imported]

Martin Fränzl, und Frank Cichos. Hydrodynamic manipulation of nano-objects by optically induced thermo-osmotic flows. Nature communications, (13)1:656, Nature Publishing Group UK London, 2022. [PUMA: topic_physchemistry Hydrodynamic flows induced manipulation nano-objects optically thermo-osmotic]

Xiangzun Wang, Pin-Chuan Chen, Klaus Kroy, Viktor Holubec, und Frank Cichos. Spontaneous vortex formation by microswimmers with retarded attractions. Nature Communications, (14)1:56, Nature Publishing Group UK London, 2023. [PUMA: topic_physchemistry Spontaneous attractions formation microswimmers retarded vortex]

Ravi Pradip, und Frank Cichos. Deep reinforcement learning with artificial microswimmers. Emerging Topics in Artificial Intelligence (ETAI) 2022, (12204):104--110, 2022. [PUMA: topic_physchemistry Deep artificial learning microswimmers reinforcement]

Giovanni Volpe, Carolina W�hlby, Lei Tian, Michael Hecht, Artur Yakimovich, Kristina Monakhova, Laura Waller, Ivo F. Sbalzarini, Christopher A. Metzler, Mingyang Xie, Kevin Zhang, Isaac C. D. Lenton, Halina Rubinsztein-Dunlop, Daniel Brunner, Bijie Bai, Aydogan Ozcan, Daniel Midtvedt, Hao Wang, Nata�a Sladoje, Joakim Lindblad, Jason T. Smith, Marien Ochoa, Margarida Barroso, Xavier Intes, Tong Qiu, Li-Yu Yu, Sixian You, Yongtao Liu, Maxim A. Ziatdinov, Sergei V. Kalinin, Arlo Sheridan, Uri Manor, Elias Nehme, Ofri Goldenberg, Yoav Shechtman, Henrik K. Moberg, Christoph Langhammer, Barbora �pa?kov�, Saga Helgadottir, Benjamin Midtvedt, Aykut Argun, Tobias Thalheim, Frank Cichos, Stefano Bo, Lars Hubatsch, Jesus Pineda, Carlo Manzo, Harshith Bachimanchi, Erik Selander, Antoni Homs-Corbera, Martin Fr�nzl, Kevin de Haan, Yair Rivenson, Zofia Korczak, Caroline Beck Adiels, Mite Mijalkov, D�niel Ver�b, Yu-Wei Chang, Joana B. Pereira, Damian Matuszewski, Gustaf Kylberg, Ida-Maria Sintorn, Juan C. Caicedo, Beth A Cimini, Muyinatu A. Lediju Bell, Bruno M. Saraiva, Guillaume Jacquemet, Ricardo Henriques, Wei Ouyang, Trang Le, Estibaliz G�mez de Mariscal, Daniel Sage, Arrate Mu�oz-Barrutia, Ebba Josefson Lindqvist, und Johanna Bergman. Roadmap on Deep Learning for Microscopy. 2023. [PUMA: topic_physchemistry topic_mathfoundation topic_lifescience imported] URL

Frank Cichos, Santiago Mui�os Landin, und Ravi Pradip. Chapter 5 - Artificial intelligence (AI) enhanced nanomotors and active matter. In Yuebing Zheng, und Zilong Wu (Hrsg.), Intelligent Nanotechnology, 113--144, Elsevier, 2023. [PUMA: topic_physchemistry Active Feedback Machine Multi Optical Reinforcement agent control control, learning, particles, reinforcement] URL

Benjamin Uhrich, Martin Schäfer, Oliver Theile, und Erhard Rahm. Using Physics-Informed Machine Learning to Optimize 3D Printing Processes. Progress in Digital and Physical Manufacturing, 2022. [PUMA: area_bigdata topic_physchemistry]

S Nikolov, J Tranchida, K Ramakrishna, M Lokamani, A Cangi, und M A Wood. Dissociating the phononic, magnetic and electronic contributions to thermal conductivity: a computational study in alpha-iron. J. Mater. Sci., (57)23:10535--10548, Springer Science and Business Media LLC, Juni 2022. [PUMA: topic_physchemistry]

Matthew Leinhauser, René Widera, Sergei Bastrakov, Alexander Debus, Michael Bussmann, und Sunita Chandrasekaran. Metrics and design of an instruction roofline model for AMD GPUs. ACM Trans. Parallel Comput., (9)1:1--14, Association for Computing Machinery (ACM), März 2022. [PUMA: topic_physchemistry]

Benjamin Uhrich, Nikolai Hlubek, Tim Häntschel, und Erhard Rahm. Using differential equation inspired machine learning for valve faults prediction. 2023 IEEE 21st International Conference on Industrial Informatics (INDIN), IEEE, Juli 2023. [PUMA: area_bigdata topic_physchemistry]

Markus Bauer, Benjamin Uhrich, Martin Schäfer, Oliver Theile, Christoph Augenstein, und Erhard Rahm. Multi-modal artificial intelligence in additive manufacturing: Combining thermal and camera images for 3D-print quality monitoring. Proceedings of the 25th International Conference on Enterprise Information Systems, SCITEPRESS - Science and Technology Publications, 2023. [PUMA: area_bigdata unit_transfer topic_physchemistry]

Universität Leipzig, Benjamin Uhrich, Shirin Lange, Universität Leipzig, Miriam Louise Carnot, Universität Leipzig, Martin Schäfer, und SIEMENS AG Berlin. Predictive Manufacturing -- Ein Intelligentes Überwachungssystem zur Erkennung von Anomalien im 3D-Druck. Ind. 4 0 Manag., (2023)1:27--31, GITO mbH Verlag, Februar 2023. [PUMA: topic_physchemistry topic_lifescience]