Abstract:
A comprehensive theoretical and experimental study of the photostructural transformations of acrylic epoxidized soybean oil under the action of ultraviolet light has been carried out. The photopolymerization process is controlled by a free radical mechanism that starts under the influence of light quanta and leads to heating of the material due to the formation of new bonds of the polymer network. In an electric field, a dielectric relaxation process is additionally observed, which is caused by orientational defects in the local structural components of the polymer. Their contribution is estimated by analyzing the entropy
of the dielectric constant time series, and the energy and structural properties are modeled using modern tools of computer materials science –machine learning interatomic potentials.
This work was supported in part by the Ministry of Education and Science of Ukraine (projects Nos. 0122U000850, 0122U000874, and 0122U001694), National Research Foundation of Ukraine (project No. 2020.02/0100), Slovak Grant Agency VEGA (project No. 2/0134/21), and Slovak Research and Development Agency (project No. APVV-21-0335). This work has also received funding through the MSCA4Ukraine project (grant No. 1128327), which is funded by the European Union, and the EURIZON project (grant No. 3022), which is funded by the European Union (EURIZON H2020 project) under grant agreement No. 871072. The authors would also like to thank the Armed Forces of Ukraine for providing security to perform this work. This work has become possible only because of the resilience and courage of the Ukrainian Army.
Description:
1. Romanini M. Dielectric Spectroscopy Studies of Conformational Relaxation Dynamics in Molecular Glass-Forming Liquids / M. Romanini, R. Macovez, S. Valenti, W. Noor, J.L. Tamarit // Int. J. Mol. Sci., 2023. №24. P. 17189. https://doi.org/10.3390/ijms242417189
2. Moon Y.I. Observation of the relaxation process in fluoroelastomers by dielectric relaxation spectroscopy / Y.I. Moon, J.K. Jung, G.H. Kim, K.S. Chung // Physica B, 2021. №608. P. 412870. https://doi.org/10.1016/j.physb.2021.412870
3. Kiv A. Complex Network Methods for Plastic Deformation Dynamics in Metals / A. Kiv, A. Bryukhanov, V. Soloviev, A. Bielinskyi, T. Kavetskyy, D. Dyachok, I. Donchev, V. Lukashin // Dynamics, 2023. №3. P. 34–59. https://doi.org/10.3390/dynamics3010004
4. Kiv, A. et al. (2023). Irreversibility of Plastic Deformation Processes in Metals. In: Faure, E., Danchenko, O., Bondarenko, M., Tryus, Y., Bazilo, C., Zaspa, G. (eds) Information Technology for Education, Science, and Technics. ITEST 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 178. Springer, Cham. https://doi.org/10.1007/978-3-031-35467-0_26
5. Královič D.P. Effect of Aromatic Rings in AESO-VDM Biopolymers on the Local Free Volume and Diffusion Properties of Polymer Matrix / D.P. Královič, K. Cifraničová, H. Švajdlenková, et al. // J Polym Environ, 2023. https://doi.org/10.1007/s10924-023-03097-1
6. Chong S.S. Advances of machine learning in materials science: Ideas and techniques / S.S. Chong, Y.S. Ng, H.-Q. Wang, J.-C. Zheng // Front. Phys, 2024. №19. P. 13501. https://doi.org/10.1007/s11467-023-1325-z
7. Bielinskyi A. Irreversibility of financial time series: a case of crisis / A.O. Bielinskyi, S.V. Hushko, A.V. Matviychuk, O.A. Serdyuk, S.O. Semerikov, V.N. Soloviev // Machine Learning for Prediction of Emergent Economy Dynamics, 2021. vol. 3048. ISSN 1613-0073. p. 134-150.
8. Shannon C. A mathematical theory of communication / C. Shannon // The Bell system technical journal, 1948, №27(3). P. 379-423. https://doi.org/10.1002/j.1538-7305.1948.tb01338.x
9. Grassberger P. Measuring the strangeness of strange attractors / P. Grassberger, I. Procaccia // Physica D: nonlinear phenomena, 1983, №9(1-2). P. 189-208. https://doi.org/10.1016/0167-2789(83)90298-1