TY  - JOUR
AU  - Đorđević, Katarina Lj.
AU  - Markushev, Dragana K.
AU  - Popović, Marica N.
AU  - Nesić, Mioljub V.
AU  - Galović, Slobodanka
AU  - Lukić, Dragan V.
AU  - Markushev, Dragan D.
PY  - 2023
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/10858
AB  - In this paper, the possibility of determining the thermal, elastic and geometric characteristics of a thin TiO2 film deposited on a silicon substrate, with a thickness of 30 μm, in the frequency range of 20 to 20 kHz with neural networks were analysed. For this purpose, the geometric (thickness), thermal (thermal diffusivity, coefficient of linear expansion) and electronic parameters of substrates were known and constant in the two-layer model, while the following nano-layer thin-film parameters were changed: thickness, expansion and thermal diffusivity. Predictions of these three parameters of the thin-film were analysed separately with three neural networks. All of them together were joined by a fourth neural network. It was shown that the neural network, which analysed all three parameters at the same time, achieved the highest accuracy, so the use of networks that provide predictions for only one parameter is less reliable. The obtained results showed that the application of neural networks in determining the thermoelastic properties of a thin film on a supporting substrate enables the estimation of its characteristics with great accuracy.
T2  - Materials
T1  - Photoacoustic Characterization of TiO2 Thin-Films Deposited on Silicon Substrate Using Neural Networks
VL  - 16
IS  - 7
SP  - 2865
DO  - 10.3390/ma16072865
ER  - 

@article{
author = "Đorđević, Katarina Lj. and Markushev, Dragana K. and Popović, Marica N. and Nesić, Mioljub V. and Galović, Slobodanka and Lukić, Dragan V. and Markushev, Dragan D.",
year = "2023",
abstract = "In this paper, the possibility of determining the thermal, elastic and geometric characteristics of a thin TiO2 film deposited on a silicon substrate, with a thickness of 30 μm, in the frequency range of 20 to 20 kHz with neural networks were analysed. For this purpose, the geometric (thickness), thermal (thermal diffusivity, coefficient of linear expansion) and electronic parameters of substrates were known and constant in the two-layer model, while the following nano-layer thin-film parameters were changed: thickness, expansion and thermal diffusivity. Predictions of these three parameters of the thin-film were analysed separately with three neural networks. All of them together were joined by a fourth neural network. It was shown that the neural network, which analysed all three parameters at the same time, achieved the highest accuracy, so the use of networks that provide predictions for only one parameter is less reliable. The obtained results showed that the application of neural networks in determining the thermoelastic properties of a thin film on a supporting substrate enables the estimation of its characteristics with great accuracy.",
journal = "Materials",
title = "Photoacoustic Characterization of TiO2 Thin-Films Deposited on Silicon Substrate Using Neural Networks",
volume = "16",
number = "7",
pages = "2865",
doi = "10.3390/ma16072865"
}

Đorđević, K. Lj., Markushev, D. K., Popović, M. N., Nesić, M. V., Galović, S., Lukić, D. V.,& Markushev, D. D.. (2023). Photoacoustic Characterization of TiO2 Thin-Films Deposited on Silicon Substrate Using Neural Networks. in Materials, 16(7), 2865.
https://doi.org/10.3390/ma16072865

Đorđević KL, Markushev DK, Popović MN, Nesić MV, Galović S, Lukić DV, Markushev DD. Photoacoustic Characterization of TiO2 Thin-Films Deposited on Silicon Substrate Using Neural Networks. in Materials. 2023;16(7):2865.
doi:10.3390/ma16072865 .

Đorđević, Katarina Lj., Markushev, Dragana K., Popović, Marica N., Nesić, Mioljub V., Galović, Slobodanka, Lukić, Dragan V., Markushev, Dragan D., "Photoacoustic Characterization of TiO2 Thin-Films Deposited on Silicon Substrate Using Neural Networks" in Materials, 16, no. 7 (2023):2865,
https://doi.org/10.3390/ma16072865 . .