Forschung
Publikationen

Publikationen im Rahmen des Exzellenzclusters PhoenixD

Die Forschungsleistung des Exzellenzclusters PhoenixD zeigt sich in den zahlreichen Publikationen, die seit 2019 veröffentlicht wurden. Eine kontinuierlich aktualisierte Übersicht finden Sie auf dieser Seite. In externen Publikationsportalen können Sie nach Veröffentlichungen mit der Identifikationsnummer (Project-ID) 390833453 und dem Kürzel EXC-2122 suchen.


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2022


Appiarius, Y., Gliese, P. J., Segler, S. A. W., Rusch, P., Zhang, J., Gates, P. J., Pal, R., Malaspina, L. A., Sugimoto, K., Neudecker, T., Bigall, N. C., Grabowsky, S., Bakulin, A. A., & Staubitz, A. (2022). BN-Substitution in Dithienylpyrenes Prevents Excimer Formation in Solution and in the Solid State. Journal of Physical Chemistry C, 126(9), 4563-4576. doi.org/10.1021/acs.jpcc.1c08812

Babushkin, I., Galán, Á. J., de Andrade, J. R. C., Husakou, A., Morales, F., Kretschmar, M., Nagy, T., Vaičaitis, V., Shi, L., Zuber, D., Bergé, L., Skupin, S., Nikolaeva, I. A., Panov, N. A., Shipilo, D. E., Kosareva, O. G., Pfeiffer, A. N., Demircan, A., Vrakking, M. J. J., ... Ivanov, M. (2022). All-optical attoclock for imaging tunnelling wavepackets. Nature physics, 18(4), 417-422. doi.org/10.48550/arXiv.1803.04187, doi.org/10.1038/s41567-022-01505-2

Babushkin, I., Demircan, A., Kues, M., & Morgner, U. (2022). Wave-Shape-Tolerant Photonic Quantum Gates. Physical Review Letters, 128(9), [090502]. doi.org/10.1103/PhysRevLett.128.090502

Brunotte, W., Nagel, L., Schneider, K., & Klünder, J. A-C. (2022). How to Identify Changing Contexts of Use with Creativity Workshops: An Experience Report. in C. Ardito, R. Lanzilotti, A. Malizia, M. Larusdottir, L. D. Spano, J. Campos, M. Hertzum, T. Mentler, J. Abdelnour Nocera, L. Piccolo, S. Sauer, & G. van der Veer (Hrsg.), Sense, Feel, Design: INTERACT 2021 IFIP TC 13 Workshops, Revised Selected Papers (S. 88-97). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 13198 LNCS). Springer Nature Switzerland AG. doi.org/10.1007/978-3-030-98388-8_9

Brunotte, W., Chazette, L., Klös, V., & Speith, T. (2022). Quo Vadis, Explainability? A Research Roadmap for Explainability Engineering. in V. Gervasi, & A. Vogelsang (Hrsg.), Requirements Engineering: Foundation for Software Quality : 28th International Working Conference, REFSQ 2022, Birmingham, UK, March 21–24, 2022, Proceedings (S. 26-32). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 13216 LNCS). Springer Nature Switzerland AG. doi.org/10.1007/978-3-030-98464-9_3

Brunotte, W., Chazette, L., Köhler, L., Klünder, J. A-C., & Schneider, K. (2022). What About My Privacy? Helping Users Understand Online Privacy Policies. in Proceedings - 2022 IEEE/ACM Joint 16th International Conferenceon Software and System Processes and 17th ACM/IEEE International Conference on Global Software Engineering, ICSSP/ICGSE 2022: ICSSP'22 (S. 56–65). (ACM International Conference Proceeding Series). ACM DL. doi.org/10.1145/3529320.3529327

He, L., Guo, HW., Jin, Y., Zhuang, XY., Rabczuk, T., & Li, Y. (2022). Machine-learning-driven on-demand design of phononic beams. Science China: Physics, Mechanics and Astronomy, 65(1), [214612]. doi.org/10.1007/s11433-021-1787-x

Heinemann, D., Zabic, M., Terakawa, M., & Boch, J. (2022). Laser-based molecular delivery and its applications in plant science. Plant Methods, 18(1), [82]. doi.org/10.1186/s13007-022-00908-9

Herrmann, T., Schierz, A. K., Prediger, M., Reifenrath, J., Meißner, J., Wurz, M. C., & Behrens, P. (2022). Effect of PEG functionalization on the saturation magnetization of magnetic nanoporous core-shell nanoparticles. International Journal on Magnetic Particle Imaging, 8(1), [2203009]. doi.org/10.18416/ijmpi.2022.2203009

Jin, Y., He, L., Wen, Z., Mortazavi, B., Guo, HW., Torrent, D., Djafari-Rouhani, B., Rabczuk, T., Zhuang, XY., & Li, Y. (2022). Intelligent on-demand design of phononic metamaterials. Nanophotonics, 11(3), 439-460. doi.org/10.1515/nanoph-2021-0639

Keppler, N. C., Josephine Hindricks, K. D., & Behrens, P. (2022). Large refractive index changes in ZIF-8 thin films of optical quality. RSC Advances, 12(10), 5807-5815. doi.org/10.1039/d1ra08531j

Klepzig, L. F., Biesterfeld, L., Romain, M., Niebur, A., Schlosser, A., Hübner, J., & Lauth, J. (2022). Colloidal 2D PbSe nanoplatelets with efficient emission reaching the telecom O-, E- and S-band. Nanoscale Advances, 4(2), 590-599. doi.org/10.1039/d1na00704a

Leffers, L., Roth, B., & Overmeyer, L. (2022). Polymer optical Bend Sensor based on eccentric Fiber Bragg Gratings for 3D Shape Detection. in W. M. Shensky, I. Rau, & O. Sugihara (Hrsg.), Organic Photonic Materials and Devices XXIV [1199808] (Proceedings of SPIE - The International Society for Optical Engineering; Band 11998). SPIE. doi.org/10.1117/12.2609764

Liu, B., Vu-Bac, N., Fu, X., Zhuang, X., & Rabczuk, T. (2022). Stochastic full-range multiscale modeling of thermal conductivity of Polymeric carbon nanotubes composites: A machine learning approach. Composite structures, 289, [115393]. doi.org/10.1016/j.compstruct.2022.115393

Malek, T., Winkler, M., Denkena, B., & Wichmann, M. (2022). Energieeffiziente Prozessplanung. VDI-Z Integrierte Produktion, 164(4), 38-41. doi.org/10.37544/0042-1766-2022-04-38

Melchert, O., & Demircan, A. (2022). py-fmas: A python package for ultrashort optical pulse propagation in terms of forward models for the analytic signal. Computer Physics Communications, 273, [108257]. doi.org/10.1016/j.cpc.2021.108257

Mortazavi, B., Shojaei, F., Shapeev, A. V., & Zhuang, X. (2022). A combined first-principles and machine-learning investigation on the stability, electronic, optical, and mechanical properties of novel C6N7-based nanoporous carbon nitrides. CARBON, 194, 230-239. doi.org/10.1016/j.carbon.2022.03.068

Mortazavi, B., Shahrokhi, M., Shojaei, F., Rabczuk, T., Zhuang, X., & Shapeev, A. V. (2022). A first-principles and machine-learning investigation on the electronic, photocatalytic, mechanical and heat conduction properties of nanoporous C5N monolayers. NANOSCALE, 14(11), 4324-4333. doi.org/10.1039/d1nr06449e

Mortazavi, B., Novikov, I. S., & Shapeev, A. V. (2022). A machine-learning-based investigation on the mechanical/failure response and thermal conductivity of semiconducting BC2N monolayers. CARBON, 188, 431-441. doi.org/10.1016/j.carbon.2021.12.039

Mortazavi, B., Rajabpour, A., Zhuang, XY., Rabczuk, T., & Shapeev, AV. (2022). Exploring thermal expansion of carbon-based nanosheets by machine-learning interatomic potentials. CARBON, 186, 501-508. doi.org/10.1016/j.carbon.2021.10.059


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