M. Steffen. Dataset, (2023)Related to: Maier, S.: Simulation of a Novel Restraint Safety Concept for Motorcycles, Dissertation, University of Stuttgart, Shaker Verlag, Aachen, tbd.
M. Takamoto, T. Praditia, R. Leiteritz, D. MacKinlay, F. Alesiani, D. Pflüger, and M. Niepert. Dataset, (2022)Related to: Takamoto, M., Praditia, T., Leiteritz, R., MacKinlay, D., Alesiani, F., Pflüger, D. and Niepert, M.: PDEBench: An Extensive Benchmark for Scientific Machine Learning. submitted to the 36th Conference on Neural Information Processing Systems (NeurIPS 2022) Track on Datasets and Benchmarks. arXiv: 2210.07182.
M. Takamoto, T. Praditia, R. Leiteritz, D. MacKinlay, F. Alesiani, D. Pflüger, and M. Niepert. Dataset, (2022)Related to: Takamoto, M., Praditia, T., Leiteritz, R., MacKinlay, D., Alesiani, F., Pflüger, D. and Niepert, M.: PDEBench: An Extensive Benchmark for Scientific Machine Learning. submitted to the 36th Conference on Neural Information Processing Systems (NeurIPS 2022) Track on Datasets and Benchmarks.
I. Tischler, C. Holm, and A. Schlaich. Software, (2022)Related to: Tischler, I., Schlaich, A., Holm, C., The Presence of a Wall Enhances the Probability for Ring-Closing Metathesis: Insights from Classical Polymer Theory and Atomistic Simulations. Macromol. Theory Simul. 2021, 30, 2000076. doi: 10.1002/mats.202000076.
I. Tischler, A. Schlaich, and C. Holm. Software, (2023)Related to: Ingo Tischler, Alexander Schlaich, Christian Holm. Disentanglement of Surface and Confinement Effects for Diene Metathesis in Mesoporous Confinement. ACS Omega 2023. doi: 10.1021/acsomega.3c06195.
G. Tkachev. Software, (2021)Related to: G. Tkachev, S. Frey and T. Ertl, "S4: Self-Supervised learning of Spatiotemporal Similarity," in IEEE Transactions on Visualization and Computer Graphics. doi: 10.1109/TVCG.2021.3101418.
S. Vahid Dastjerdi, N. Karadimitriou, and H. Steeb. Dataset, (2022)Related to: Vahid Dastjerdi, S.; Karadimitriou, N.; Hassanizadeh, S. M. & Steeb, H.: Experimental evaluation of fluid connectivity in two-phase flow in porous media. Advances in Water Resources 172 (2023), 104378. doi: 10.1016/j.advwatres.2023.104378.
S. Vahid Dastjerdi, H. Steeb, M. Ruf, D. Lee, F. Weinhardt, N. Karadimitriou, and H. Class. Dataset, (2021)Related to: Weinhart, F., Class, H., Vahid Dastjerdi, S., Karadimitriou, N., Lee, D., & Steeb, H. (2021). Experimental Methods and Imaging for Enzymatically Induced Calcite Precipitation in a microfluidic cell. Water Resources Research, Technical Reports: Methods. doi: 10.1029/2020WR029361.
J. Wachlmayr, G. Fläschner, K. Pluhackova, W. Sandtner, C. Siligan, and A. Horner. Dataset, (2023)Related to: Wachlmayr, Johann; Fläschner, Gotthold; Pluhackova, Kristyna; Sandtner, Walter, Siliga, Christine; Horner, Andreas, "Entropic barrier of water permeation through single-file channels" Comms. Chem. 2023,. doi: 10.1038/s42004-023-00919-0.
F. Weinhardt, H. Class, S. Vahid Dastjerdi, N. Karadimitriou, D. Lee, and H. Steeb. Dataset, (2021)Related to: Weinhardt, F.; Class, H.; Vahid Dastjerdi, S.; Karadimitriou, N.; Lee, D.; Steeb, H.(2021). Experimental Methods and Imaging for Enzymatically Induced Calcite Precipitation in a microfluidic cell. Accepted in Water Resources Research. doi: 10.1029/2020WR029361.
F. Weinhardt, J. Deng, H. Steeb, and H. Class. Dataset, (2022)Related to: Weinhardt, F.; Deng, J.; Hommel, J.; Vahid Dastjerdi, S.; Gerlach, R.; Steeb, H.; Class, H. (2022). Spatiotemporal Distribution of Precipitates and Mineral Phase Transition During Biomineralization Affect Porosity–Permeability Relationships. Transport in Porous Media 143, 527–549 (2022). doi: 10.1007/s11242-022-01782-8.
L. Werneck, E. Yildiz, M. Han, M. Keip, M. Sitti, and M. Ortiz. Software, (2023)Related to: Werneck, L., Han, M., Yildiz, E., Keip, M.-A., Sitti, M., & Ortiz, M. (2023). A Simple Quantitative Model of Neuromodulation, Part I: Ion Flow Through Neural Ion Channels. Journal of the Mechanics and Physics of Solids, 182:105457. doi: 10.1016/j.jmps.2023.105457.
I. Wochner, and S. Schmitt. Software, (2022)Related to: Wochner, I., Schumacher, P., Martius, G., Büchler, D., Schmitt, S., & Haeufle, D. F. (2022). Learning with Muscles: Benefits for Data-Efficiency and Robustness in Anthropomorphic Tasks. Conference on Robot Learning (CoRL) 2022. url: https://openreview.net/forum?id=Xo3eOibXCQ8.
X. Xu. Dataset, (2023)Related to: Xu, Xiang, Xi Zhang, Andrei Ruban, Siegfried Schmauder, and Blazej Grabowski. "Strong impact of spin fluctuations on the antiphase boundaries of weak itinerant ferromagnetic Ni3Al." Acta Materialia 255 (2023): 118986. doi: 10.1016/j.actamat.2023.118986.
J. Yang, S. Kondrat, C. Lian, H. Liu, A. Schlaich, and C. Holm. Dataset, (2023)Related to: J. Yang, S. Kondrat, C. Lian, H. Liu, A. Schlaich, und C. Holm, „Solvent Effects on Structure and Screening in Confined Electrolytes“, Phys. Rev. Lett., Bd. 131, Nr. 11, 118201, Sep. 2023. doi: 10.1103/PhysRevLett.131.118201.
V. Zaverkin, D. Holzmüller, L. Bonfirraro, and J. Kästner. Dataset, (2023)Related to: Viktor Zaverkin, David Holzmüller, Luca Bonfirraro, Johannes Kästner. Transfer learning for chemically accurate interatomic neural network potentials, Phys. Chem. Chem. Phys., 2023, 25, 5383-5396. doi: 10.1039/D2CP05793J.
V. Zaverkin, D. Holzmüller, I. Steinwart, and J. Kästner. Software, (2021)Related to: V. Zaverkin, D. Holzmüller, I. Steinwart, and J. Kästner, “Fast and Sample-Efficient Interatomic Neural Network Potentials for Molecules and Materials Based on Gaussian Moments,” J. Chem. Theory Comput. 17, 6658–6670 (2021). doi: 10.1021/acs.jctc.1c00527.