Neural networks determination of material elastic constants and structures in nematic complex fluids

Zaplotnik, Jaka (avtor), Pišljar, Jaka (avtor), Škarabot, Miha (avtor), Ravnik, Miha (avtor)

Supervised machine learning and artificial neural network approaches can allow for the determination of selected material parameters or structures from a measurable signal without knowing the exact mathematical relationship between them. Here, we demonstrate that material nematic elastic constants and the initial structural material configuration can be found using sequential neural networks applied to the transmmited time-dependent light intensity through the nematic liquid crystal (NLC) sample under crossed polarizers. Specifically, we simulate multiple times the relaxation of the NLC from a random (qeunched) initial state to the equilibrium for random values of elastic constants and, simultaneously, the transmittance of the sample for monochromatic polarized light. The obtained time-dependent light transmittances and the corresponding elastic constants form a training data set on which the neural network is trained, which allows for the determination of the elastic constants, as well as the initial state of the director. Finally, we demonstrate that the neural network trained on numerically generated examples can also be used to determine elastic constants from experimentally measured data, finding good agreement between experiments and neural network predictions.

• Jezik: Angleški jezik
• Ključne besede: condensed-matter physics, nematic liquid crystals, neural networks, characterization and analytical techniques, liquid crystals, structure of solids and liquids
• Vrsta gradiva: Članek v reviji
• Tipologija: 1.01 - Izvirni znanstveni članek
• Organizacija: FMF - Fakulteta za matematiko in fiziko
• Status publikacije: Objavljeno
• Različica publikacije: Objavljena publikacija
• Leto izida: 2023
• Št. strani: 12 str.
• Številčenje: Vol. 13, art. 6028
• PID: 20.500.12556/RUL-154023
• UDK: 538.9
• ISSN pri članku: 2045-2322
• DOI: 10.1038/s41598-023-33134-x
• COBISS.SI-ID: 149325827
• Datum objave v RUL: 19.01.2024

Gradivo je del revije

• Naslov: Scientific reports
• Skrajšan naslov: Sci. rep.
• Založnik: Nature Publishing Group
• ISSN: 2045-2322
• COBISS.SI-ID: 18727432

Licence

• Licenca: CC BY 4.0, Creative Commons Priznanje avtorstva 4.0 Mednarodna
• Povezava: http://creativecommons.org/licenses/by/4.0/deed.sl
• Opis: To je standardna licenca Creative Commons, ki daje uporabnikom največ možnosti za nadaljnjo uporabo dela, pri čemer morajo navesti avtorja.

Sekundarni jezik

• Jezik: Slovenski jezik
• Ključne besede: fizika kondenzirane snovi, nematski tekoči kristali, nevronske mreže