TY  - CONF
AU  - Ribar, Srđan
AU  - Mitić, Vojislav V.
AU  - Ranđelović, Branislav
AU  - Milošević, Dušan
AU  - Paunović, Vesna
AU  - Fecht, Hans-Jörg
AU  - Vlahović, Branislav
PY  - 2021
UR  - https://dais.sanu.ac.rs/123456789/11909
AB  - Predicting the ceramic materials properties and designing the desired microstructures characteristics are very important objectives in ceramic samples consolidating process. The goal of our research is to calculate the density within consolidated BaTiO3-ceramic samples for different consolidation parameters, like sintering temperature, using obtained experimental data from the material’s surface, by applying back propagation neural network (BP). This method, as a very powerful tool, provides the possibility to calculate the exact values of desired microelectronic parameter at the level of the grains’ coating layers. The artificial neural networks, which have biomimetic similarities with biological neural networks, propagate the input signal forward, unlike the output signal, designated as error, which is propagated backwards spreading throughout the whole network, from output to input neuron layers. Between these two neuron layers, there are usually one or more hidden layers, where the grains of the sintered material are represented by network neurons. Adjustable coefficients, called weights, are forward propagated, like input signals, but they modify the calculated output error, so the neural network training procedure is necessary for reducing the error. Different consolidated samples density values, measured on the bulk, substituted the errors, which are calculated as contribution of all network elements, thus enabling the density calculation of all constituents of ceramic structure presented by neural network. In our future research we plan to increase the number of neurons and hidden layers in order to improve this method to become even more accurate and precise.
PB  - Belgrade : Serbian Ceramic Society
C3  - Program and the Book of abstracts / Serbian Ceramic Society Conference Advanced Ceramics and Application IX : New Frontiers in Multifunctional Material Science and Processing, Serbia, Belgrade, 20-21. September 2021
T1  - The ceramics materials density defined by artificial neural networks
SP  - 42
EP  - 42
UR  - https://hdl.handle.net/21.15107/rcub_dais_11909
ER  - 

@conference{
author = "Ribar, Srđan and Mitić, Vojislav V. and Ranđelović, Branislav and Milošević, Dušan and Paunović, Vesna and Fecht, Hans-Jörg and Vlahović, Branislav",
year = "2021",
abstract = "Predicting the ceramic materials properties and designing the desired microstructures characteristics are very important objectives in ceramic samples consolidating process. The goal of our research is to calculate the density within consolidated BaTiO3-ceramic samples for different consolidation parameters, like sintering temperature, using obtained experimental data from the material’s surface, by applying back propagation neural network (BP). This method, as a very powerful tool, provides the possibility to calculate the exact values of desired microelectronic parameter at the level of the grains’ coating layers. The artificial neural networks, which have biomimetic similarities with biological neural networks, propagate the input signal forward, unlike the output signal, designated as error, which is propagated backwards spreading throughout the whole network, from output to input neuron layers. Between these two neuron layers, there are usually one or more hidden layers, where the grains of the sintered material are represented by network neurons. Adjustable coefficients, called weights, are forward propagated, like input signals, but they modify the calculated output error, so the neural network training procedure is necessary for reducing the error. Different consolidated samples density values, measured on the bulk, substituted the errors, which are calculated as contribution of all network elements, thus enabling the density calculation of all constituents of ceramic structure presented by neural network. In our future research we plan to increase the number of neurons and hidden layers in order to improve this method to become even more accurate and precise.",
publisher = "Belgrade : Serbian Ceramic Society",
journal = "Program and the Book of abstracts / Serbian Ceramic Society Conference Advanced Ceramics and Application IX : New Frontiers in Multifunctional Material Science and Processing, Serbia, Belgrade, 20-21. September 2021",
title = "The ceramics materials density defined by artificial neural networks",
pages = "42-42",
url = "https://hdl.handle.net/21.15107/rcub_dais_11909"
}

Ribar, S., Mitić, V. V., Ranđelović, B., Milošević, D., Paunović, V., Fecht, H.,& Vlahović, B.. (2021). The ceramics materials density defined by artificial neural networks. in Program and the Book of abstracts / Serbian Ceramic Society Conference Advanced Ceramics and Application IX : New Frontiers in Multifunctional Material Science and Processing, Serbia, Belgrade, 20-21. September 2021
Belgrade : Serbian Ceramic Society., 42-42.
https://hdl.handle.net/21.15107/rcub_dais_11909

Ribar S, Mitić VV, Ranđelović B, Milošević D, Paunović V, Fecht H, Vlahović B. The ceramics materials density defined by artificial neural networks. in Program and the Book of abstracts / Serbian Ceramic Society Conference Advanced Ceramics and Application IX : New Frontiers in Multifunctional Material Science and Processing, Serbia, Belgrade, 20-21. September 2021. 2021;:42-42.
https://hdl.handle.net/21.15107/rcub_dais_11909 .

Ribar, Srđan, Mitić, Vojislav V., Ranđelović, Branislav, Milošević, Dušan, Paunović, Vesna, Fecht, Hans-Jörg, Vlahović, Branislav, "The ceramics materials density defined by artificial neural networks" in Program and the Book of abstracts / Serbian Ceramic Society Conference Advanced Ceramics and Application IX : New Frontiers in Multifunctional Material Science and Processing, Serbia, Belgrade, 20-21. September 2021 (2021):42-42,
https://hdl.handle.net/21.15107/rcub_dais_11909 .

TY  - JOUR
AU  - Mitić, Vojislav V.
AU  - Ranđelović, Branislav
AU  - Ilić, Ivana
AU  - Ribar, Srđan
AU  - Chun, An-Lu
AU  - Stajčić, Aleksandar
AU  - Vlahović, Branislav
PY  - 2021
UR  - https://cer.ihtm.bg.ac.rs/handle/123456789/4809
UR  - https://dais.sanu.ac.rs/123456789/11949
AB  - After pioneering attempts for the introduction of graph theory in the field of ceramics and microstructures, where 1D and 2D graphs were used, in this paper we applied 3D graphs for the breakdown voltage calculation in BaTiO3sample with some predefined constraints. We have described the relations between grains in the sample and established a mathematical approach for the calculation of breakdown voltage using experimental results. As a result, we introduced mapping between the property of sample and grain structure, then between the grain structure and mathematical graph, using various crystal structures. The main idea was to apply 3D graph theory for the distribution of electronic parameters between the neighboring grains. With this study, we successfully confirmed the possibilities for applications of graphs as a tool for the determination of properties even at the intergranular level.
PB  - World Scientific Publishing Co
T2  - International Journal of Modern Physics B
T1  - The 3D graph approach for breakdown voltage calculation in BaTiO3ceramics
SP  - 2150103
VL  - 35
IS  - 7
DO  - 10.1142/S0217979221501034
UR  - https://hdl.handle.net/21.15107/rcub_dais_11949
ER  - 

@article{
author = "Mitić, Vojislav V. and Ranđelović, Branislav and Ilić, Ivana and Ribar, Srđan and Chun, An-Lu and Stajčić, Aleksandar and Vlahović, Branislav",
year = "2021",
abstract = "After pioneering attempts for the introduction of graph theory in the field of ceramics and microstructures, where 1D and 2D graphs were used, in this paper we applied 3D graphs for the breakdown voltage calculation in BaTiO3sample with some predefined constraints. We have described the relations between grains in the sample and established a mathematical approach for the calculation of breakdown voltage using experimental results. As a result, we introduced mapping between the property of sample and grain structure, then between the grain structure and mathematical graph, using various crystal structures. The main idea was to apply 3D graph theory for the distribution of electronic parameters between the neighboring grains. With this study, we successfully confirmed the possibilities for applications of graphs as a tool for the determination of properties even at the intergranular level.",
publisher = "World Scientific Publishing Co",
journal = "International Journal of Modern Physics B",
title = "The 3D graph approach for breakdown voltage calculation in BaTiO3ceramics",
pages = "2150103",
volume = "35",
number = "7",
doi = "10.1142/S0217979221501034",
url = "https://hdl.handle.net/21.15107/rcub_dais_11949"
}

Mitić, V. V., Ranđelović, B., Ilić, I., Ribar, S., Chun, A., Stajčić, A.,& Vlahović, B.. (2021). The 3D graph approach for breakdown voltage calculation in BaTiO3ceramics. in International Journal of Modern Physics B
World Scientific Publishing Co., 35(7), 2150103.
https://doi.org/10.1142/S0217979221501034
https://hdl.handle.net/21.15107/rcub_dais_11949

Mitić VV, Ranđelović B, Ilić I, Ribar S, Chun A, Stajčić A, Vlahović B. The 3D graph approach for breakdown voltage calculation in BaTiO3ceramics. in International Journal of Modern Physics B. 2021;35(7):2150103.
doi:10.1142/S0217979221501034
https://hdl.handle.net/21.15107/rcub_dais_11949 .

Mitić, Vojislav V., Ranđelović, Branislav, Ilić, Ivana, Ribar, Srđan, Chun, An-Lu, Stajčić, Aleksandar, Vlahović, Branislav, "The 3D graph approach for breakdown voltage calculation in BaTiO3ceramics" in International Journal of Modern Physics B, 35, no. 7 (2021):2150103,
https://doi.org/10.1142/S0217979221501034 .,
https://hdl.handle.net/21.15107/rcub_dais_11949 .

TY  - JOUR
AU  - Mitić, Vojislav V.
AU  - Ribar, Srđan
AU  - Ranđelović, Branislav M.
AU  - Aleksić, Dejan
AU  - Fecht, Hans
AU  - Vlahovic, Branislav
PY  - 2021
UR  - https://dais.sanu.ac.rs/123456789/12389
AB  - The materials’ consolidation, especially ceramics, is very important in advanced research development and industrial technologies. Science of sintering with all incoming novelties is the base of all these processes. A very important question in all of this is how to get the more precise structure parameters within the morphology of different ceramic materials. In that sense, the advanced procedure in collecting precise data in submicro-processes is also in direction of advanced miniaturization. Our research, based on different electrophysical parameters, like relative capacitance, breakdown voltage, and tgδ, has been used in neural networks and graph theory successful applications. We extended furthermore our neural network back propagation (BP) on sintering parameters’ data. Prognosed mapping we can succeed if we use the coefficients, implemented by the training procedure. In this paper, we continue to apply the novelty from the previous research, where the error is calculated as a difference between the designed and actual network output. So, the weight coefficients contribute in error generation. We used the experimental data of sintered materials’ density, measured and calculated in the bulk, and developed possibility to calculate the materials’ density inside of consolidated structures. The BP procedure here is like a tool to come down between the layers, with much more precise materials’ density, in the points on morphology, which are interesting for different microstructure developments and applications. We practically replaced the errors’ network by density values, from ceramic consolidation. Our neural networks’ application novelty is successfully applied within the experimental ceramic material density ρ=5.4×103 [kg/m3], confirming the direction way to implement this procedure in other density cases. There are many different mathematical tools or tools from the field of artificial intelligence that can be used in such or similar applications. We choose to use artificial neural networks because of their simplicity and their self-improvement process, through BP error control. All of this contributes to the great improvement in the whole research and science of sintering technology, which is important for collecting more efficient and faster results.
PB  - World Scientific Pub Co Pte Ltd
T2  - Modern Physics Letters B
T1  - A new neural network approach to density calculation on ceramic materials
DO  - 10.1142/S0217984921505497
UR  - https://hdl.handle.net/21.15107/rcub_dais_12389
ER  - 

@article{
author = "Mitić, Vojislav V. and Ribar, Srđan and Ranđelović, Branislav M. and Aleksić, Dejan and Fecht, Hans and Vlahovic, Branislav",
year = "2021",
abstract = "The materials’ consolidation, especially ceramics, is very important in advanced research development and industrial technologies. Science of sintering with all incoming novelties is the base of all these processes. A very important question in all of this is how to get the more precise structure parameters within the morphology of different ceramic materials. In that sense, the advanced procedure in collecting precise data in submicro-processes is also in direction of advanced miniaturization. Our research, based on different electrophysical parameters, like relative capacitance, breakdown voltage, and tgδ, has been used in neural networks and graph theory successful applications. We extended furthermore our neural network back propagation (BP) on sintering parameters’ data. Prognosed mapping we can succeed if we use the coefficients, implemented by the training procedure. In this paper, we continue to apply the novelty from the previous research, where the error is calculated as a difference between the designed and actual network output. So, the weight coefficients contribute in error generation. We used the experimental data of sintered materials’ density, measured and calculated in the bulk, and developed possibility to calculate the materials’ density inside of consolidated structures. The BP procedure here is like a tool to come down between the layers, with much more precise materials’ density, in the points on morphology, which are interesting for different microstructure developments and applications. We practically replaced the errors’ network by density values, from ceramic consolidation. Our neural networks’ application novelty is successfully applied within the experimental ceramic material density ρ=5.4×103 [kg/m3], confirming the direction way to implement this procedure in other density cases. There are many different mathematical tools or tools from the field of artificial intelligence that can be used in such or similar applications. We choose to use artificial neural networks because of their simplicity and their self-improvement process, through BP error control. All of this contributes to the great improvement in the whole research and science of sintering technology, which is important for collecting more efficient and faster results.",
publisher = "World Scientific Pub Co Pte Ltd",
journal = "Modern Physics Letters B",
title = "A new neural network approach to density calculation on ceramic materials",
doi = "10.1142/S0217984921505497",
url = "https://hdl.handle.net/21.15107/rcub_dais_12389"
}

Mitić, V. V., Ribar, S., Ranđelović, B. M., Aleksić, D., Fecht, H.,& Vlahovic, B.. (2021). A new neural network approach to density calculation on ceramic materials. in Modern Physics Letters B
World Scientific Pub Co Pte Ltd..
https://doi.org/10.1142/S0217984921505497
https://hdl.handle.net/21.15107/rcub_dais_12389

Mitić VV, Ribar S, Ranđelović BM, Aleksić D, Fecht H, Vlahovic B. A new neural network approach to density calculation on ceramic materials. in Modern Physics Letters B. 2021;.
doi:10.1142/S0217984921505497
https://hdl.handle.net/21.15107/rcub_dais_12389 .

Mitić, Vojislav V., Ribar, Srđan, Ranđelović, Branislav M., Aleksić, Dejan, Fecht, Hans, Vlahovic, Branislav, "A new neural network approach to density calculation on ceramic materials" in Modern Physics Letters B (2021),
https://doi.org/10.1142/S0217984921505497 .,
https://hdl.handle.net/21.15107/rcub_dais_12389 .

TY  - CONF
AU  - Mitić, Vojislav V.
AU  - Ranđelović, Branislav
AU  - Ribar, Srđan
AU  - Milošević, Dušan
AU  - Soković, Marina
AU  - Marković, Bojana
AU  - Fecht, Hans-Jörg
AU  - Vlahović, Branislav
PY  - 2021
UR  - https://dais.sanu.ac.rs/123456789/11908
AB  - There are a lot of recently published research papers regarding representing nanostructures and biomimetic materials, using simple but powerful mathematical methods. In most of them, fractal theory, graph theory and neural networks are used. Having in mind variety of those methods, but in the same time complementarity and compatibility, they became very useful tool, and we named it “Holly Trinity” of mathematical approach in nanostructures. In this research we give an overview on interesting results in modelling nanostructures and their electrochemical and magnetic parameters, using those very actual and “easy to use” methods: fractal theory, graph theory and neural networks. We also compare them, in order to conclude about areas of their most useful applications.
PB  - Belgrade : Serbian Ceramic Society
C3  - Program and the Book of abstracts / Serbian Ceramic Society Conference Advanced Ceramics and Application IX : New Frontiers in Multifunctional Material Science and Processing, Serbia, Belgrade, 20-21. September 2021
T1  - Fractals, Graphs and Neural Networks: The Holly Trinity of Nanostructures - An Overview and Comparison of Methods
SP  - 43
EP  - 43
UR  - https://hdl.handle.net/21.15107/rcub_dais_11908
ER  - 

@conference{
author = "Mitić, Vojislav V. and Ranđelović, Branislav and Ribar, Srđan and Milošević, Dušan and Soković, Marina and Marković, Bojana and Fecht, Hans-Jörg and Vlahović, Branislav",
year = "2021",
abstract = "There are a lot of recently published research papers regarding representing nanostructures and biomimetic materials, using simple but powerful mathematical methods. In most of them, fractal theory, graph theory and neural networks are used. Having in mind variety of those methods, but in the same time complementarity and compatibility, they became very useful tool, and we named it “Holly Trinity” of mathematical approach in nanostructures. In this research we give an overview on interesting results in modelling nanostructures and their electrochemical and magnetic parameters, using those very actual and “easy to use” methods: fractal theory, graph theory and neural networks. We also compare them, in order to conclude about areas of their most useful applications.",
publisher = "Belgrade : Serbian Ceramic Society",
journal = "Program and the Book of abstracts / Serbian Ceramic Society Conference Advanced Ceramics and Application IX : New Frontiers in Multifunctional Material Science and Processing, Serbia, Belgrade, 20-21. September 2021",
title = "Fractals, Graphs and Neural Networks: The Holly Trinity of Nanostructures - An Overview and Comparison of Methods",
pages = "43-43",
url = "https://hdl.handle.net/21.15107/rcub_dais_11908"
}

Mitić, V. V., Ranđelović, B., Ribar, S., Milošević, D., Soković, M., Marković, B., Fecht, H.,& Vlahović, B.. (2021). Fractals, Graphs and Neural Networks: The Holly Trinity of Nanostructures - An Overview and Comparison of Methods. in Program and the Book of abstracts / Serbian Ceramic Society Conference Advanced Ceramics and Application IX : New Frontiers in Multifunctional Material Science and Processing, Serbia, Belgrade, 20-21. September 2021
Belgrade : Serbian Ceramic Society., 43-43.
https://hdl.handle.net/21.15107/rcub_dais_11908

Mitić VV, Ranđelović B, Ribar S, Milošević D, Soković M, Marković B, Fecht H, Vlahović B. Fractals, Graphs and Neural Networks: The Holly Trinity of Nanostructures - An Overview and Comparison of Methods. in Program and the Book of abstracts / Serbian Ceramic Society Conference Advanced Ceramics and Application IX : New Frontiers in Multifunctional Material Science and Processing, Serbia, Belgrade, 20-21. September 2021. 2021;:43-43.
https://hdl.handle.net/21.15107/rcub_dais_11908 .

Mitić, Vojislav V., Ranđelović, Branislav, Ribar, Srđan, Milošević, Dušan, Soković, Marina, Marković, Bojana, Fecht, Hans-Jörg, Vlahović, Branislav, "Fractals, Graphs and Neural Networks: The Holly Trinity of Nanostructures - An Overview and Comparison of Methods" in Program and the Book of abstracts / Serbian Ceramic Society Conference Advanced Ceramics and Application IX : New Frontiers in Multifunctional Material Science and Processing, Serbia, Belgrade, 20-21. September 2021 (2021):43-43,
https://hdl.handle.net/21.15107/rcub_dais_11908 .

TY  - CONF
AU  - Radović, Ivana
AU  - Mitić, Vojislav V.
AU  - Stajčić, Aleksandar
AU  - Serpa, Cristina
AU  - Ribar, Srđan
AU  - Ranđelović, Branislav
AU  - Vlahović, Branislav
PY  - 2021
UR  - https://dais.sanu.ac.rs/123456789/11906
AB  - Polymers offer the possibility of different reinforcement incorporation due to a broad range of chemical structures. Along with this feature, their light weight and processing ease made them a class of materials that have been applied in construction parts, drug delivery agents or electronic devices. Epoxy-based composites have used as insulators in microelectronic devices due to its chemical resistance, good adhesion properties and endurance. As epoxies have low fracture resistance, they are often reinforced with different kinds of fibers. With thorough knowledge of the structure, physical properties can be predicted and included in the processing of future composites, especially that electronic materials minituarization brought micro- and nanoscale level properties at spotlight. Fractal nature analysis is a mathematical method that has proved to be efficient in grain interface properties applied on perovskite ceramic materials. In our study, fiber shape reconstruction and determination of Hausdorff dimension have been achieved with the application of fractal regression model employed in software Fractal Real Finder opening a new path for the prediction of reinforcement shape and size, all with the aim of processing composite materials with desired properties
PB  - Belgrade : Serbian Ceramic Society
C3  - Program and the Book of abstracts / Serbian Ceramic Society Conference Advanced Ceramics and Application IX : New Frontiers in Multifunctional Material Science and Processing, Serbia, Belgrade, 20-21. September 2021
T1  - Fractal reconstruction of fiber-reinforced polymer composites
SP  - 49
EP  - 49
UR  - https://hdl.handle.net/21.15107/rcub_dais_11906
ER  - 

@conference{
author = "Radović, Ivana and Mitić, Vojislav V. and Stajčić, Aleksandar and Serpa, Cristina and Ribar, Srđan and Ranđelović, Branislav and Vlahović, Branislav",
year = "2021",
abstract = "Polymers offer the possibility of different reinforcement incorporation due to a broad range of chemical structures. Along with this feature, their light weight and processing ease made them a class of materials that have been applied in construction parts, drug delivery agents or electronic devices. Epoxy-based composites have used as insulators in microelectronic devices due to its chemical resistance, good adhesion properties and endurance. As epoxies have low fracture resistance, they are often reinforced with different kinds of fibers. With thorough knowledge of the structure, physical properties can be predicted and included in the processing of future composites, especially that electronic materials minituarization brought micro- and nanoscale level properties at spotlight. Fractal nature analysis is a mathematical method that has proved to be efficient in grain interface properties applied on perovskite ceramic materials. In our study, fiber shape reconstruction and determination of Hausdorff dimension have been achieved with the application of fractal regression model employed in software Fractal Real Finder opening a new path for the prediction of reinforcement shape and size, all with the aim of processing composite materials with desired properties",
publisher = "Belgrade : Serbian Ceramic Society",
journal = "Program and the Book of abstracts / Serbian Ceramic Society Conference Advanced Ceramics and Application IX : New Frontiers in Multifunctional Material Science and Processing, Serbia, Belgrade, 20-21. September 2021",
title = "Fractal reconstruction of fiber-reinforced polymer composites",
pages = "49-49",
url = "https://hdl.handle.net/21.15107/rcub_dais_11906"
}

Radović, I., Mitić, V. V., Stajčić, A., Serpa, C., Ribar, S., Ranđelović, B.,& Vlahović, B.. (2021). Fractal reconstruction of fiber-reinforced polymer composites. in Program and the Book of abstracts / Serbian Ceramic Society Conference Advanced Ceramics and Application IX : New Frontiers in Multifunctional Material Science and Processing, Serbia, Belgrade, 20-21. September 2021
Belgrade : Serbian Ceramic Society., 49-49.
https://hdl.handle.net/21.15107/rcub_dais_11906

Radović I, Mitić VV, Stajčić A, Serpa C, Ribar S, Ranđelović B, Vlahović B. Fractal reconstruction of fiber-reinforced polymer composites. in Program and the Book of abstracts / Serbian Ceramic Society Conference Advanced Ceramics and Application IX : New Frontiers in Multifunctional Material Science and Processing, Serbia, Belgrade, 20-21. September 2021. 2021;:49-49.
https://hdl.handle.net/21.15107/rcub_dais_11906 .

Radović, Ivana, Mitić, Vojislav V., Stajčić, Aleksandar, Serpa, Cristina, Ribar, Srđan, Ranđelović, Branislav, Vlahović, Branislav, "Fractal reconstruction of fiber-reinforced polymer composites" in Program and the Book of abstracts / Serbian Ceramic Society Conference Advanced Ceramics and Application IX : New Frontiers in Multifunctional Material Science and Processing, Serbia, Belgrade, 20-21. September 2021 (2021):49-49,
https://hdl.handle.net/21.15107/rcub_dais_11906 .

TY  - CONF
AU  - Mitić, Vojislav V.
AU  - Ranđelović, Branislav
AU  - Ribar, Srđan
AU  - Milošević, Dušan
AU  - Vlahović, Branislav
AU  - Fecht, Hans-Jörg
AU  - Mohr, Marcus
PY  - 2021
UR  - https://dais.sanu.ac.rs/123456789/11900
AB  - Various interesting results have been achieved in calculation of electrochemical parameters in nanomaterials, using neural networks. There appear some error, during those calculations, and it varies depending on number of neurons in layers. In this research we deal with errors, calculated for neural networks with n=1,2…10, neurons in first or second layer. We applied mean square approximation method, in order to get explicite formula for predicton of error,
for other cases.
PB  - Belgrade : Serbian Ceramic Society
C3  - Program and the Book of abstracts / Serbian Ceramic Society Conference Advanced Ceramics and Application IX : New Frontiers in Multifunctional Material Science and Processing, Serbia, Belgrade, 20-21. September 2021
T1  - Approximation and Error Prediction in Electrochemical Parameters Calculation Using Neural Networks
SP  - 61
EP  - 61
UR  - https://hdl.handle.net/21.15107/rcub_dais_11900
ER  - 

@conference{
author = "Mitić, Vojislav V. and Ranđelović, Branislav and Ribar, Srđan and Milošević, Dušan and Vlahović, Branislav and Fecht, Hans-Jörg and Mohr, Marcus",
year = "2021",
abstract = "Various interesting results have been achieved in calculation of electrochemical parameters in nanomaterials, using neural networks. There appear some error, during those calculations, and it varies depending on number of neurons in layers. In this research we deal with errors, calculated for neural networks with n=1,2…10, neurons in first or second layer. We applied mean square approximation method, in order to get explicite formula for predicton of error,
for other cases.",
publisher = "Belgrade : Serbian Ceramic Society",
journal = "Program and the Book of abstracts / Serbian Ceramic Society Conference Advanced Ceramics and Application IX : New Frontiers in Multifunctional Material Science and Processing, Serbia, Belgrade, 20-21. September 2021",
title = "Approximation and Error Prediction in Electrochemical Parameters Calculation Using Neural Networks",
pages = "61-61",
url = "https://hdl.handle.net/21.15107/rcub_dais_11900"
}

Mitić, V. V., Ranđelović, B., Ribar, S., Milošević, D., Vlahović, B., Fecht, H.,& Mohr, M.. (2021). Approximation and Error Prediction in Electrochemical Parameters Calculation Using Neural Networks. in Program and the Book of abstracts / Serbian Ceramic Society Conference Advanced Ceramics and Application IX : New Frontiers in Multifunctional Material Science and Processing, Serbia, Belgrade, 20-21. September 2021
Belgrade : Serbian Ceramic Society., 61-61.
https://hdl.handle.net/21.15107/rcub_dais_11900

Mitić VV, Ranđelović B, Ribar S, Milošević D, Vlahović B, Fecht H, Mohr M. Approximation and Error Prediction in Electrochemical Parameters Calculation Using Neural Networks. in Program and the Book of abstracts / Serbian Ceramic Society Conference Advanced Ceramics and Application IX : New Frontiers in Multifunctional Material Science and Processing, Serbia, Belgrade, 20-21. September 2021. 2021;:61-61.
https://hdl.handle.net/21.15107/rcub_dais_11900 .

Mitić, Vojislav V., Ranđelović, Branislav, Ribar, Srđan, Milošević, Dušan, Vlahović, Branislav, Fecht, Hans-Jörg, Mohr, Marcus, "Approximation and Error Prediction in Electrochemical Parameters Calculation Using Neural Networks" in Program and the Book of abstracts / Serbian Ceramic Society Conference Advanced Ceramics and Application IX : New Frontiers in Multifunctional Material Science and Processing, Serbia, Belgrade, 20-21. September 2021 (2021):61-61,
https://hdl.handle.net/21.15107/rcub_dais_11900 .

TY  - JOUR
AU  - Mitić, Vojislav V.
AU  - Lazović, Goran
AU  - Ribar, Srđan
AU  - Lu, Chun-An
AU  - Radović, Ivana
AU  - Stajčić, Aleksandar
AU  - Fecht, Hans
AU  - Vlahović, Branislav
PY  - 2020
UR  - https://dais.sanu.ac.rs/123456789/9542
AB  - This paper is based on fundamental research to develop the interface structure around the grains and to control the layers between two grains, as a prospective media for high-level electronic parameters integrations. We performed the experiments based on nano-BaTiO3 powders with Y additives. All results on dielectric parameters on submicron level are the part of global values the same measured characteristics at the bulk samples. The original idea is to develop the new computing ways to network electronic parameters in thin layers between the grains on the way to get and to compare the values on the samples. Artificial neural networks are computing tools that map input-output data and could be applied on ceramic electronic parameters. These are developed in the manner signals are processed in biological neural networks. The signals are processed by using elements which represent artificial neurons, which have a simple function to process input signal, as well as adjustable parameter which has an influence to change output signal. The total network output presents the sum of a large number neurons outputs. This important research idea is to connect analysis results and neural networks. There is a great interest to connect all of these microcapacitances by neural network with the goal to compare the results in the standard bulk samples measurements frame and microelectronics parameters. The final result of the study was functional relation definition between consolidation parameters, voltage (U) and relative capacitance change, from the level of the bulk sample down to the grains boundaries.
PB  - Taylor & Francis
T2  - Integrated Ferroelectrics
T1  - The Artificial Neural Networks Applied for Microelectronics Intergranular Relations Determination
SP  - 135
EP  - 146
VL  - 212
IS  - 1
DO  - 10.1080/10584587.2020.1819042
UR  - https://hdl.handle.net/21.15107/rcub_dais_9542
ER  - 

@article{
author = "Mitić, Vojislav V. and Lazović, Goran and Ribar, Srđan and Lu, Chun-An and Radović, Ivana and Stajčić, Aleksandar and Fecht, Hans and Vlahović, Branislav",
year = "2020",
abstract = "This paper is based on fundamental research to develop the interface structure around the grains and to control the layers between two grains, as a prospective media for high-level electronic parameters integrations. We performed the experiments based on nano-BaTiO3 powders with Y additives. All results on dielectric parameters on submicron level are the part of global values the same measured characteristics at the bulk samples. The original idea is to develop the new computing ways to network electronic parameters in thin layers between the grains on the way to get and to compare the values on the samples. Artificial neural networks are computing tools that map input-output data and could be applied on ceramic electronic parameters. These are developed in the manner signals are processed in biological neural networks. The signals are processed by using elements which represent artificial neurons, which have a simple function to process input signal, as well as adjustable parameter which has an influence to change output signal. The total network output presents the sum of a large number neurons outputs. This important research idea is to connect analysis results and neural networks. There is a great interest to connect all of these microcapacitances by neural network with the goal to compare the results in the standard bulk samples measurements frame and microelectronics parameters. The final result of the study was functional relation definition between consolidation parameters, voltage (U) and relative capacitance change, from the level of the bulk sample down to the grains boundaries.",
publisher = "Taylor & Francis",
journal = "Integrated Ferroelectrics",
title = "The Artificial Neural Networks Applied for Microelectronics Intergranular Relations Determination",
pages = "135-146",
volume = "212",
number = "1",
doi = "10.1080/10584587.2020.1819042",
url = "https://hdl.handle.net/21.15107/rcub_dais_9542"
}

Mitić, V. V., Lazović, G., Ribar, S., Lu, C., Radović, I., Stajčić, A., Fecht, H.,& Vlahović, B.. (2020). The Artificial Neural Networks Applied for Microelectronics Intergranular Relations Determination. in Integrated Ferroelectrics
Taylor & Francis., 212(1), 135-146.
https://doi.org/10.1080/10584587.2020.1819042
https://hdl.handle.net/21.15107/rcub_dais_9542

Mitić VV, Lazović G, Ribar S, Lu C, Radović I, Stajčić A, Fecht H, Vlahović B. The Artificial Neural Networks Applied for Microelectronics Intergranular Relations Determination. in Integrated Ferroelectrics. 2020;212(1):135-146.
doi:10.1080/10584587.2020.1819042
https://hdl.handle.net/21.15107/rcub_dais_9542 .

Mitić, Vojislav V., Lazović, Goran, Ribar, Srđan, Lu, Chun-An, Radović, Ivana, Stajčić, Aleksandar, Fecht, Hans, Vlahović, Branislav, "The Artificial Neural Networks Applied for Microelectronics Intergranular Relations Determination" in Integrated Ferroelectrics, 212, no. 1 (2020):135-146,
https://doi.org/10.1080/10584587.2020.1819042 .,
https://hdl.handle.net/21.15107/rcub_dais_9542 .

TY  - JOUR
AU  - Ranđelović, Branislav M.
AU  - Mitić, Vojislav V.
AU  - Ribar, Srđan
AU  - Lu, Chun-An
AU  - Radović, Ivana
AU  - Stajčić, Aleksandar
AU  - Novaković, Igor
AU  - Vlahović, Branislav
PY  - 2020
UR  - https://dais.sanu.ac.rs/123456789/10032
AB  - This research is focused on further developing of application and use of graph theory in order to describe relations between grains and to establish control over layers. We used functionalized BaTiO3 nanoparticles coated with Yttrium-based salt. The capacitance change results on super-microstructure levels are the part of the measured values on the bulk samples. The new idea is graph theory application for determination of electronic parameters distribution at the grain boundary and to compare them with the bulk measured values. We present them with vertices in graph, corresponding with grains, connected with edges. Capacitance change with applied voltage was measured on samples sintered in air and nitrogen, up to 100 V. Using graph theory, it has been shown that capacitance change can be successfully calculated on the layers between grains. Within the idea how to get parameters values at microlevel between the grains and pores, mathematical tool can be developed. Besides previously described 1D case, some original calculations for 2D cases were performed in this study, proving successful graph theory use for the calculation of values at nanolevel, leading to a further minituarization in micropackaging.
PB  - World Scientific Pub Co Pte Lt
T2  - Modern Physics Letters B
T1  - Ceramics, materials, microelectronics and graph theory new frontiers
SP  - 2150159
VL  - 34
DO  - 10.1142/S0217984921501591
UR  - https://hdl.handle.net/21.15107/rcub_dais_10032
ER  - 

@article{
author = "Ranđelović, Branislav M. and Mitić, Vojislav V. and Ribar, Srđan and Lu, Chun-An and Radović, Ivana and Stajčić, Aleksandar and Novaković, Igor and Vlahović, Branislav",
year = "2020",
abstract = "This research is focused on further developing of application and use of graph theory in order to describe relations between grains and to establish control over layers. We used functionalized BaTiO3 nanoparticles coated with Yttrium-based salt. The capacitance change results on super-microstructure levels are the part of the measured values on the bulk samples. The new idea is graph theory application for determination of electronic parameters distribution at the grain boundary and to compare them with the bulk measured values. We present them with vertices in graph, corresponding with grains, connected with edges. Capacitance change with applied voltage was measured on samples sintered in air and nitrogen, up to 100 V. Using graph theory, it has been shown that capacitance change can be successfully calculated on the layers between grains. Within the idea how to get parameters values at microlevel between the grains and pores, mathematical tool can be developed. Besides previously described 1D case, some original calculations for 2D cases were performed in this study, proving successful graph theory use for the calculation of values at nanolevel, leading to a further minituarization in micropackaging.",
publisher = "World Scientific Pub Co Pte Lt",
journal = "Modern Physics Letters B",
title = "Ceramics, materials, microelectronics and graph theory new frontiers",
pages = "2150159",
volume = "34",
doi = "10.1142/S0217984921501591",
url = "https://hdl.handle.net/21.15107/rcub_dais_10032"
}

Ranđelović, B. M., Mitić, V. V., Ribar, S., Lu, C., Radović, I., Stajčić, A., Novaković, I.,& Vlahović, B.. (2020). Ceramics, materials, microelectronics and graph theory new frontiers. in Modern Physics Letters B
World Scientific Pub Co Pte Lt., 34, 2150159.
https://doi.org/10.1142/S0217984921501591
https://hdl.handle.net/21.15107/rcub_dais_10032

Ranđelović BM, Mitić VV, Ribar S, Lu C, Radović I, Stajčić A, Novaković I, Vlahović B. Ceramics, materials, microelectronics and graph theory new frontiers. in Modern Physics Letters B. 2020;34:2150159.
doi:10.1142/S0217984921501591
https://hdl.handle.net/21.15107/rcub_dais_10032 .

Ranđelović, Branislav M., Mitić, Vojislav V., Ribar, Srđan, Lu, Chun-An, Radović, Ivana, Stajčić, Aleksandar, Novaković, Igor, Vlahović, Branislav, "Ceramics, materials, microelectronics and graph theory new frontiers" in Modern Physics Letters B, 34 (2020):2150159,
https://doi.org/10.1142/S0217984921501591 .,
https://hdl.handle.net/21.15107/rcub_dais_10032 .

TY  - JOUR
AU  - Ranđelović, Branislav M.
AU  - Mitić, Vojislav V.
AU  - Ribar, Srđan
AU  - Lu, Chun-An
AU  - Radović, Ivana
AU  - Stajčić, Aleksandar
AU  - Novaković, Igor
AU  - Vlahović, Branislav
PY  - 2020
UR  - https://dais.sanu.ac.rs/123456789/10031
AB  - This research is focused on further developing of application and use of graph theory in order to describe relations between grains and to establish control over layers. We used functionalized BaTiO3 nanoparticles coated with Yttrium-based salt. The capacitance change results on super-microstructure levels are the part of the measured values on the bulk samples. The new idea is graph theory application for determination of electronic parameters distribution at the grain boundary and to compare them with the bulk measured values. We present them with vertices in graph, corresponding with grains, connected with edges. Capacitance change with applied voltage was measured on samples sintered in air and nitrogen, up to 100 V. Using graph theory, it has been shown that capacitance change can be successfully calculated on the layers between grains. Within the idea how to get parameters values at microlevel between the grains and pores, mathematical tool can be developed. Besides previously described 1D case, some original calculations for 2D cases were performed in this study, proving successful graph theory use for the calculation of values at nanolevel, leading to a further minituarization in micropackaging.
PB  - World Scientific Pub Co Pte Lt
T2  - Modern Physics Letters B
T1  - Ceramics, materials, microelectronics and graph theory new frontiers
SP  - 2150159
VL  - 34
DO  - 10.1142/S0217984921501591
UR  - https://hdl.handle.net/21.15107/rcub_dais_10031
ER  - 

@article{
author = "Ranđelović, Branislav M. and Mitić, Vojislav V. and Ribar, Srđan and Lu, Chun-An and Radović, Ivana and Stajčić, Aleksandar and Novaković, Igor and Vlahović, Branislav",
year = "2020",
abstract = "This research is focused on further developing of application and use of graph theory in order to describe relations between grains and to establish control over layers. We used functionalized BaTiO3 nanoparticles coated with Yttrium-based salt. The capacitance change results on super-microstructure levels are the part of the measured values on the bulk samples. The new idea is graph theory application for determination of electronic parameters distribution at the grain boundary and to compare them with the bulk measured values. We present them with vertices in graph, corresponding with grains, connected with edges. Capacitance change with applied voltage was measured on samples sintered in air and nitrogen, up to 100 V. Using graph theory, it has been shown that capacitance change can be successfully calculated on the layers between grains. Within the idea how to get parameters values at microlevel between the grains and pores, mathematical tool can be developed. Besides previously described 1D case, some original calculations for 2D cases were performed in this study, proving successful graph theory use for the calculation of values at nanolevel, leading to a further minituarization in micropackaging.",
publisher = "World Scientific Pub Co Pte Lt",
journal = "Modern Physics Letters B",
title = "Ceramics, materials, microelectronics and graph theory new frontiers",
pages = "2150159",
volume = "34",
doi = "10.1142/S0217984921501591",
url = "https://hdl.handle.net/21.15107/rcub_dais_10031"
}

Ranđelović, B. M., Mitić, V. V., Ribar, S., Lu, C., Radović, I., Stajčić, A., Novaković, I.,& Vlahović, B.. (2020). Ceramics, materials, microelectronics and graph theory new frontiers. in Modern Physics Letters B
World Scientific Pub Co Pte Lt., 34, 2150159.
https://doi.org/10.1142/S0217984921501591
https://hdl.handle.net/21.15107/rcub_dais_10031

Ranđelović BM, Mitić VV, Ribar S, Lu C, Radović I, Stajčić A, Novaković I, Vlahović B. Ceramics, materials, microelectronics and graph theory new frontiers. in Modern Physics Letters B. 2020;34:2150159.
doi:10.1142/S0217984921501591
https://hdl.handle.net/21.15107/rcub_dais_10031 .

Ranđelović, Branislav M., Mitić, Vojislav V., Ribar, Srđan, Lu, Chun-An, Radović, Ivana, Stajčić, Aleksandar, Novaković, Igor, Vlahović, Branislav, "Ceramics, materials, microelectronics and graph theory new frontiers" in Modern Physics Letters B, 34 (2020):2150159,
https://doi.org/10.1142/S0217984921501591 .,
https://hdl.handle.net/21.15107/rcub_dais_10031 .