TY  - JOUR
AU  - Martinović, Sanja
AU  - Alil, Ana
AU  - Milićević, Sonja
AU  - Živojinović, Dragana
AU  - Volkov Husović, Tatjana
PY  - 2023
UR  - http://TechnoRep.tmf.bg.ac.rs/handle/123456789/6355
AB  - The pattern recognition approach, explored by this study, applies the principal component analysis (PCA) as the most widely used statistical method with the aim of assessing the initiation and propagation of the cracks and defects that appear on the surface of material exposed to the cavitation. The experiment was performed in four stages: (a) synthesis of two ceramic materials (cordierite and zircon); (b) subjecting the samples to the cavitation; (c) using image analysis software for collecting the data about morphological characteristics that describe defects; (d) principal component analysis as a pattern recognition tool in order to characterize the defects at the material surface. Besides that, according to standard, cavitation erosion was monitored by determining material mass loss during the cavitation. Large experimental datasets collected from morphological descriptors by image analysis are multivariate and difficult to interpret, thus are processed by principal component analysis as the most informative technique for extracting possible differences. The performed approach proved that this method has a great potential for better assessment of induced defects by proper distinguishing among them at different levels and that can be considered a very efficient and cost-effective one.
PB  - Elsevier Ltd
T2  - Engineering Failure Analysis
T1  - Morphological assessment of cavitation caused damage of cordierite and zircon based materials using principal component analysis
SP  - 107224
VL  - 148
DO  - 10.1016/j.engfailanal.2023.107224
ER  - 

@article{
author = "Martinović, Sanja and Alil, Ana and Milićević, Sonja and Živojinović, Dragana and Volkov Husović, Tatjana",
year = "2023",
abstract = "The pattern recognition approach, explored by this study, applies the principal component analysis (PCA) as the most widely used statistical method with the aim of assessing the initiation and propagation of the cracks and defects that appear on the surface of material exposed to the cavitation. The experiment was performed in four stages: (a) synthesis of two ceramic materials (cordierite and zircon); (b) subjecting the samples to the cavitation; (c) using image analysis software for collecting the data about morphological characteristics that describe defects; (d) principal component analysis as a pattern recognition tool in order to characterize the defects at the material surface. Besides that, according to standard, cavitation erosion was monitored by determining material mass loss during the cavitation. Large experimental datasets collected from morphological descriptors by image analysis are multivariate and difficult to interpret, thus are processed by principal component analysis as the most informative technique for extracting possible differences. The performed approach proved that this method has a great potential for better assessment of induced defects by proper distinguishing among them at different levels and that can be considered a very efficient and cost-effective one.",
publisher = "Elsevier Ltd",
journal = "Engineering Failure Analysis",
title = "Morphological assessment of cavitation caused damage of cordierite and zircon based materials using principal component analysis",
pages = "107224",
volume = "148",
doi = "10.1016/j.engfailanal.2023.107224"
}

Martinović, S., Alil, A., Milićević, S., Živojinović, D.,& Volkov Husović, T.. (2023). Morphological assessment of cavitation caused damage of cordierite and zircon based materials using principal component analysis. in Engineering Failure Analysis
Elsevier Ltd., 148, 107224.
https://doi.org/10.1016/j.engfailanal.2023.107224

Martinović S, Alil A, Milićević S, Živojinović D, Volkov Husović T. Morphological assessment of cavitation caused damage of cordierite and zircon based materials using principal component analysis. in Engineering Failure Analysis. 2023;148:107224.
doi:10.1016/j.engfailanal.2023.107224 .

Martinović, Sanja, Alil, Ana, Milićević, Sonja, Živojinović, Dragana, Volkov Husović, Tatjana, "Morphological assessment of cavitation caused damage of cordierite and zircon based materials using principal component analysis" in Engineering Failure Analysis, 148 (2023):107224,
https://doi.org/10.1016/j.engfailanal.2023.107224 . .

TY  - JOUR
AU  - Mališić, Vanja Z.
AU  - Pezo, Milada L.
AU  - Jelić, Aleksandra N.
AU  - Patarić, Aleksandra S.
AU  - Putić, Slaviša S.
PY  - 2023
UR  - http://TechnoRep.tmf.bg.ac.rs/handle/123456789/7040
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-aminopropil-trimetoksilanom  (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-Fletcher-Goldfarb-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  zapredviđanje  toplotne provodljivosti materijala koji se koriste u stomatologiji za izradu proteza i koji su izloženi temperaturnim promenama tokom primene.
PB  - Savez hemijskih inženjera Srbije
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
EP  - 302
IS  - 4
SP  - 293
VL  - 77
DO  - 10.2298/HEMIND230119029M
ER  - 

@article{
author = "Mališić, Vanja Z. and Pezo, Milada L. and Jelić, Aleksandra N. and Patarić, Aleksandra S. and Putić, Slaviša S.",
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-aminopropil-trimetoksilanom  (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-Fletcher-Goldfarb-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  zapredviđanje  toplotne provodljivosti materijala koji se koriste u stomatologiji za izradu proteza i koji su izloženi temperaturnim promenama tokom primene.",
publisher = "Savez hemijskih inženjera Srbije",
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",
pages = "302-293",
number = "4",
volume = "77",
doi = "10.2298/HEMIND230119029M"
}

Mališić, V. Z., Pezo, M. L., Jelić, A. N., Patarić, A. S.,& Putić, S. S.. (2023). Prediction of thermal and mechanical properties of acrylate-based composites using artificial neural network modeling. in Hemijska industrija
Savez hemijskih inženjera Srbije., 77(4), 293-302.
https://doi.org/10.2298/HEMIND230119029M

Mališić VZ, Pezo ML, Jelić AN, Patarić AS, Putić SS. Prediction of thermal and mechanical properties of acrylate-based composites using artificial neural network modeling. in Hemijska industrija. 2023;77(4):293-302.
doi:10.2298/HEMIND230119029M .

Mališić, Vanja Z., Pezo, Milada L., Jelić, Aleksandra N., Patarić, Aleksandra S., Putić, Slaviša S., "Prediction of thermal and mechanical properties of acrylate-based composites using artificial neural network modeling" in Hemijska industrija, 77, no. 4 (2023):293-302,
https://doi.org/10.2298/HEMIND230119029M . .