TY  - JOUR
AU  - Mališić, Vanja
AU  - Pezo, Milada
AU  - Jelić, Aleksandra
AU  - Patarić, Aleksandra
AU  - Putić, Slaviša
PY  - 2023
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/12281
AB  - Poly(methyl methacrylate) (PMMA) has a broad spectrum of uses, especially in medical applications. The role of fine-grained alumina particles of PMMA composites was investigated in this study. The composites were based on PMMA modified with dimethyl itaconate (DMI) as a matrix and alumina particles (Al2O3) and alumina doped with iron (Al2O3-Fe) modified with 3-aminopropyl-trimethoxysilane (AM) and flax oil fatty acid methyl esters (biodiesel) as reinforcements. Three particle sizes were measured (~0.4, ~0.6 and ~1.2 μm). The highest thermal conductivity values were measured for the composite 5 wt.% Al2O3-Fe-AM. With the addition of 3 wt.% Al2O3-AM to the PMMA/DMI matrix, mechanical properties were improved (tensile strength, strain, and modulus of elasticity). An artificial neural network model based on the Broyden-Fletcher-Goldfarb-Shanno iterative algorithm was investigated for prediction of thermal conductivity and mechanical properties of the composites showing satisfactory results. This is relevant for applications for optimization of dental materials to produce dentures, which were exposed to variations in temperature during the application.
AB  - Poli (metil metakrilata) (PMMA) ima široku upotrebu, posebno u stomatologiji i medicini. Kompoziti su napravljeni od PMMA modifikovanog dimetil itakonatom (DMI) kao matrice. Kao pojačanje korišćene su čestice glinice (Al2O3) i glinice dopirane oksidom gvožđa (Al2O3-Fe) modifikovanim sa 3-aminopropiltrimetoksilanom (AM) i metil estrima masnih kiselina lanenog ulja (biodizel – BD). Prema merenjima toplotne provodljivosti, najveće vrednosti toplotne provodljivosti imao je kompozit sa česticama glinice 5 wt.% Al2O3-Fe-AM. Dodatkom modifikovanih čestica glinice u PMMA/DMI matricu, poboljšane su mehaničke osobine (zatezna čvrstoća, deformacija i modul elastičnosti). Razvijen je model veštačke neuronske mreže zasnovan na iterativnom algoritmu predloženom u literaturi (Broiden-FletcherGoldfarb-Shanno), za predviđanje toplotne provodljivosti i mehaničkih svojstava kompozita na bazi akrilata u kombinaciji sa česticama na bazi glinice, u zavisnosti od masenog udela čestica, i dodatka oksida gvožđa i modifikatora. Pokazano je da ovi matematički modeli mogu predvideti mehanička i termička svojstva kompozitnih materijala. Ovo je posebno relevantno za predviđanje toplotne provodljivosti materijala koji se koriste u stomatologiji za izradu proteza i koji su izloženi temperaturnim promenama tokom primene.
T2  - Hemijska industrija
T1  - Prediction of thermal and mechanical properties of acrylate-based composites using artificial neural network modeling
T1  - Predviđanje termičkih i mehaničkih svojstava kompozita na bazi akrilata korišćenjem modela veštačke neuronske mreže
VL  - 77
IS  - 4
SP  - 293
EP  - 300
DO  - 10.2298/HEMIND230119029M
ER  - 

@article{
author = "Mališić, Vanja and Pezo, Milada and Jelić, Aleksandra and Patarić, Aleksandra and Putić, Slaviša",
year = "2023",
abstract = "Poly(methyl methacrylate) (PMMA) has a broad spectrum of uses, especially in medical applications. The role of fine-grained alumina particles of PMMA composites was investigated in this study. The composites were based on PMMA modified with dimethyl itaconate (DMI) as a matrix and alumina particles (Al2O3) and alumina doped with iron (Al2O3-Fe) modified with 3-aminopropyl-trimethoxysilane (AM) and flax oil fatty acid methyl esters (biodiesel) as reinforcements. Three particle sizes were measured (~0.4, ~0.6 and ~1.2 μm). The highest thermal conductivity values were measured for the composite 5 wt.% Al2O3-Fe-AM. With the addition of 3 wt.% Al2O3-AM to the PMMA/DMI matrix, mechanical properties were improved (tensile strength, strain, and modulus of elasticity). An artificial neural network model based on the Broyden-Fletcher-Goldfarb-Shanno iterative algorithm was investigated for prediction of thermal conductivity and mechanical properties of the composites showing satisfactory results. This is relevant for applications for optimization of dental materials to produce dentures, which were exposed to variations in temperature during the application., Poli (metil metakrilata) (PMMA) ima široku upotrebu, posebno u stomatologiji i medicini. Kompoziti su napravljeni od PMMA modifikovanog dimetil itakonatom (DMI) kao matrice. Kao pojačanje korišćene su čestice glinice (Al2O3) i glinice dopirane oksidom gvožđa (Al2O3-Fe) modifikovanim sa 3-aminopropiltrimetoksilanom (AM) i metil estrima masnih kiselina lanenog ulja (biodizel – BD). Prema merenjima toplotne provodljivosti, najveće vrednosti toplotne provodljivosti imao je kompozit sa česticama glinice 5 wt.% Al2O3-Fe-AM. Dodatkom modifikovanih čestica glinice u PMMA/DMI matricu, poboljšane su mehaničke osobine (zatezna čvrstoća, deformacija i modul elastičnosti). Razvijen je model veštačke neuronske mreže zasnovan na iterativnom algoritmu predloženom u literaturi (Broiden-FletcherGoldfarb-Shanno), za predviđanje toplotne provodljivosti i mehaničkih svojstava kompozita na bazi akrilata u kombinaciji sa česticama na bazi glinice, u zavisnosti od masenog udela čestica, i dodatka oksida gvožđa i modifikatora. Pokazano je da ovi matematički modeli mogu predvideti mehanička i termička svojstva kompozitnih materijala. Ovo je posebno relevantno za predviđanje toplotne provodljivosti materijala koji se koriste u stomatologiji za izradu proteza i koji su izloženi temperaturnim promenama tokom primene.",
journal = "Hemijska industrija",
title = "Prediction of thermal and mechanical properties of acrylate-based composites using artificial neural network modeling, Predviđanje termičkih i mehaničkih svojstava kompozita na bazi akrilata korišćenjem modela veštačke neuronske mreže",
volume = "77",
number = "4",
pages = "293-300",
doi = "10.2298/HEMIND230119029M"
}

Mališić, V., Pezo, M., Jelić, A., Patarić, A.,& Putić, S.. (2023). Prediction of thermal and mechanical properties of acrylate-based composites using artificial neural network modeling. in Hemijska industrija, 77(4), 293-300.
https://doi.org/10.2298/HEMIND230119029M

Mališić V, Pezo M, Jelić A, Patarić A, Putić S. Prediction of thermal and mechanical properties of acrylate-based composites using artificial neural network modeling. in Hemijska industrija. 2023;77(4):293-300.
doi:10.2298/HEMIND230119029M .

Mališić, Vanja, Pezo, Milada, Jelić, Aleksandra, Patarić, Aleksandra, Putić, Slaviša, "Prediction of thermal and mechanical properties of acrylate-based composites using artificial neural network modeling" in Hemijska industrija, 77, no. 4 (2023):293-300,
https://doi.org/10.2298/HEMIND230119029M . .