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Rafał Topolnicki

Showing results (1-10 of 4) with videos related to

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Scientific Reports|June 18, 2026
Physics-informed convolutional neural networks for fluid flow through porous mediaRafał Topolnicki, Paweł Dłotko, Maciej Matyka
Journal of Chemical Theory and Computation|September 22, 2020
Deciphering High-Order Structural Correlations within Fluxional Molecules from Classical and Quantum Configurational EntropyRafał Topolnicki, Fabien Brieuc, Christoph Schran, et al.
Scientific Reports|September 28, 2023
Superconductivity in high-entropy alloy system containing ThPiotr Sobota, Rafał Topolnicki, Tomasz Ossowski, et al.
Materials (Basel, Switzerland)|September 9, 2023
Enhanced Superconducting Critical Parameters in a New High-Entropy Alloy Nb<sub>0.34</sub>Ti<sub>0.33</sub>Zr<sub>0.14</sub>Ta<sub>0.11</sub>Hf<sub>0.08</sub>Rafał Idczak, Wojciech Nowak, Bartosz Rusin, et al.
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Showing results (1-10 of 4) with videos related to

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Pageof 1
Scientific Reports|June 18, 2026
Physics-informed convolutional neural networks for fluid flow through porous mediaRafał Topolnicki, Paweł Dłotko, Maciej Matyka
Journal of Chemical Theory and Computation|September 22, 2020
Deciphering High-Order Structural Correlations within Fluxional Molecules from Classical and Quantum Configurational EntropyRafał Topolnicki, Fabien Brieuc, Christoph Schran, et al.
Scientific Reports|September 28, 2023
Superconductivity in high-entropy alloy system containing ThPiotr Sobota, Rafał Topolnicki, Tomasz Ossowski, et al.
Materials (Basel, Switzerland)|September 9, 2023
Enhanced Superconducting Critical Parameters in a New High-Entropy Alloy Nb<sub>0.34</sub>Ti<sub>0.33</sub>Zr<sub>0.14</sub>Ta<sub>0.11</sub>Hf<sub>0.08</sub>Rafał Idczak, Wojciech Nowak, Bartosz Rusin, et al.
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