Maurício Azevedo
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Previous Organizations / Institutes
The organizations / institutes from the scholar's other articles in the past ten years
Research Subjects
Maurício Azevedo has a total of 38 co-authors. Here are the top co-authors by number of shared publications:
- Clemens Holzer
Department of Polymer Engineering and Science, Institute of Polymer Processing, Montanuniversitaet Leoben, Otto Gloeckel-Straße 2, 8700 Leoben, Austria
4 shared publications - Roman Christopher Kerschbaumer
Polymer Competence Center Leoben GmbH, Sauraugasse 1, 8700 Leoben, Austria
4 shared publications - Martin Traintinger
Polymer Competence Center Leoben GmbH, Sauraugasse 1, 8700 Leoben, Austria
2 shared publications Roman Christopher Kerschbaumer
2 shared publications- Sandra Schlögl
Polymer Competence Center Leoben GmbH Leoben Austria
2 shared publications - Silvester Bolka
Faculty of Polymer Technology, Ozare 19, 2380 Slovenj Gradec, Slovenia
2 shared publications
Latest Publications
- Open Access
- 18 January 2026
- Published by Elsevier in Journal of Environmental Chemical Engineering
- Vol. 14 (2)
Industrial assessment of recycled steelmaking slag as a sustainable alternative to carbon black in NBR composites
- 18 January 2026
- Published by Elsevier in Journal of Environmental Chemical Engineering
- Vol. 14 (2)
Open AccessIndustrial assessment of recycled steelmaking slag as a sustainable alternative to carbon black in NBR composites
- Open Access
- 12 December 2025
- Published by Elsevier in Results in Materials
- Vol. 29
Rheological insights: A comparative analysis of viscosity determination techniques for liquid silicone rubber injection moulding simulation
- 12 December 2025
- Published by Elsevier in Results in Materials
- Vol. 29
Open AccessRheological insights: A comparative analysis of viscosity determination techniques for liquid silicone rubber injection moulding simulation
- Open Access
How Method Matters: The Impact of Material Characterisation Techniques on Liquid Silicone Rubber Injection Moulding Simulations
Injection moulding of liquid silicone rubber (LSR) requires reliable computer-aided engineering simulations to support process optimisation, which in turn depend on accurate material data. In this study, thermo-physical and kinetic properties of a highly filled injection moulding (IM) grade of LSR were systematically characterised using complementary experimental approaches, and their impact on simulation fidelity was critically assessed. Specific heat capacity was measured using both modulated DSC and the standard sapphire method, revealing temperature dependence but no intrinsic change during curing, with sapphire-based data incorporating enthalpic effects more realistically for process prediction. Thermal conductivity was found to be nearly constant across the processing temperature range. Curing kinetics were investigated by calorimetry and rheology, with the former supporting an autocatalytic mechanism and the latter suggesting an -order model, reflecting differences in detection sensitivity and onset characterisation. When implemented into injection moulding simulations, viscosity primarily affected injection pressures, while differences in specific heat capacity and curing kinetics strongly influenced predicted curing profiles and cycle times. These results emphasise that dataset choice, particularly for curing-related parameters, is critical to achieving predictive accuracy in LSR injection moulding simulations. Unlike previous studies on LSR injection moulding, which typically adapt thermoplastic-inspired characterisation methods without systematically addressing their limitations, this work introduces an organised and comparative methodology to evaluate how different material characterisation techniques influence simulation outcomes. The proposed approach establishes a methodological framework that can guide future research and improve the reliability of process simulations for LSR and other polymeric systems.Open AccessHow Method Matters: The Impact of Material Characterisation Techniques on Liquid Silicone Rubber Injection Moulding Simulations
Injection moulding of liquid silicone rubber (LSR) requires reliable computer-aided engineering simulations to support process optimisation, which in turn depend on accurate material data. In this study, thermo-physical and kinetic properties of a highly filled injection moulding (IM) grade of LSR were systematically characterised using complementary experimental approaches, and their impact on simulation fidelity was critically assessed. Specific heat capacity was measured using both modulated DSC and the standard sapphire method, revealing temperature dependence but no intrinsic change during curing, with sapphire-based data incorporating enthalpic effects more realistically for process prediction. Thermal conductivity was found to be nearly constant across the processing temperature range. Curing kinetics were investigated by calorimetry and rheology, with the former supporting an autocatalytic mechanism and the latter suggesting an -order model, reflecting differences in detection sensitivity and onset characterisation. When implemented into injection moulding simulations, viscosity primarily affected injection pressures, while differences in specific heat capacity and curing kinetics strongly influenced predicted curing profiles and cycle times. These results emphasise that dataset choice, particularly for curing-related parameters, is critical to achieving predictive accuracy in LSR injection moulding simulations. Unlike previous studies on LSR injection moulding, which typically adapt thermoplastic-inspired characterisation methods without systematically addressing their limitations, this work introduces an organised and comparative methodology to evaluate how different material characterisation techniques influence simulation outcomes. The proposed approach establishes a methodological framework that can guide future research and improve the reliability of process simulations for LSR and other polymeric systems. - Open Access
- 1 October 2025
- Published by MDPI AG in Preprints.org
How Method Matters: The Impact of Material Characterization Techniques on Liquid Silicone Rubber Injection Moulding Simulations
Injection moulding of liquid silicone rubber (LSR) requires reliable computer-aided engineering simulations to support process optimisation, which in turn depend on accurate material data. In this study, thermo-physical and kinetic properties of a highly filled injection moulding (IM) grade of LSR were systematically characterised using complementary experimental approaches and their impact on simulation fidelity was critically assessed. Specific heat capacity was measured using both modulated DSC and the standard sapphire method, revealing temperature dependence but no intrinsic change during curing, with sapphire-based data incorporating enthalpic effects more realistically for process prediction. Thermal conductivity was found to be nearly constant across the processing temperature range. Curing kinetics were investigated by calorimetry and rheology, with the former supporting an autocatalytic mechanism and the latter suggesting an $n^{th}$-order model, reflecting differences in detection sensitivity and onset characterization. When implemented into injection moulding simulations, viscosity primarily affected injection pressures, while differences in specific heat capacity and curing kinetics strongly influenced predicted curing profiles and cycle times. These results emphasize that dataset choice, particularly for curing-related parameters, is critical to achieving predictive accuracy in LSR injection moulding simulations.
- 1 October 2025
- Published by MDPI AG in Preprints.org
Open AccessHow Method Matters: The Impact of Material Characterization Techniques on Liquid Silicone Rubber Injection Moulding Simulations
Injection moulding of liquid silicone rubber (LSR) requires reliable computer-aided engineering simulations to support process optimisation, which in turn depend on accurate material data. In this study, thermo-physical and kinetic properties of a highly filled injection moulding (IM) grade of LSR were systematically characterised using complementary experimental approaches and their impact on simulation fidelity was critically assessed. Specific heat capacity was measured using both modulated DSC and the standard sapphire method, revealing temperature dependence but no intrinsic change during curing, with sapphire-based data incorporating enthalpic effects more realistically for process prediction. Thermal conductivity was found to be nearly constant across the processing temperature range. Curing kinetics were investigated by calorimetry and rheology, with the former supporting an autocatalytic mechanism and the latter suggesting an $n^{th}$-order model, reflecting differences in detection sensitivity and onset characterization. When implemented into injection moulding simulations, viscosity primarily affected injection pressures, while differences in specific heat capacity and curing kinetics strongly influenced predicted curing profiles and cycle times. These results emphasize that dataset choice, particularly for curing-related parameters, is critical to achieving predictive accuracy in LSR injection moulding simulations.
- Open Access
Shifting Focus to Quality: An Innovative Modeling Approach Includes Processing History for Rubber Part Quality Simulation
An innovative modeling approach for the simulative description of the part quality of rubber materials, including the processing history, is presented in this paper. This modeling approach, the so-called average curing speed (ACS) model, is based on the degree of cure and the average curing speed instead of the conventionally considered temperature approach. Such approach neglects the processing history by calculating only the degree of cure. Thus, the correlation with part quality has to be performed either after the simulation or with the aid of other numerical analysis programs. Instead, by applying the ACS model, the key advantage is that the processing history is already taken into account during the filling and curing simulation, demanding a single calibration step with quality information to be able to calculate the part quality. For this purpose, parts were manufactured at mold temperatures ranging from 140 °C to 170 °C and degrees of cure from 24% to 99% via compression molding and subsequently the permanent deformation, i.e., the compression set (CS), of each part was analyzed. The CS results show that one and the same degree of cure; for example, 80%, which was defined on the basis of reaction isotherms, causes an almost twofold higher CS value for parts manufactured at 170 °C. Consequently, considerable deviations may occur when real part qualities are correlated with degrees of cure from simulations with common state-of-the-art kinetic models. By applying the ACS model, it was demonstrated that this challenge could be solved. Parts manufactured by compression molding exhibited the same quality as those simulated with the ACS model. Finally, this innovative modeling approach (fully implemented in the SIGMASOFT® v simulation routine) provides enormous potential for understanding local differences in the quality of rubber parts, being an ideal tool for optimizing rubber parts through simulation routines.Open AccessShifting Focus to Quality: An Innovative Modeling Approach Includes Processing History for Rubber Part Quality Simulation
An innovative modeling approach for the simulative description of the part quality of rubber materials, including the processing history, is presented in this paper. This modeling approach, the so-called average curing speed (ACS) model, is based on the degree of cure and the average curing speed instead of the conventionally considered temperature approach. Such approach neglects the processing history by calculating only the degree of cure. Thus, the correlation with part quality has to be performed either after the simulation or with the aid of other numerical analysis programs. Instead, by applying the ACS model, the key advantage is that the processing history is already taken into account during the filling and curing simulation, demanding a single calibration step with quality information to be able to calculate the part quality. For this purpose, parts were manufactured at mold temperatures ranging from 140 °C to 170 °C and degrees of cure from 24% to 99% via compression molding and subsequently the permanent deformation, i.e., the compression set (CS), of each part was analyzed. The CS results show that one and the same degree of cure; for example, 80%, which was defined on the basis of reaction isotherms, causes an almost twofold higher CS value for parts manufactured at 170 °C. Consequently, considerable deviations may occur when real part qualities are correlated with degrees of cure from simulations with common state-of-the-art kinetic models. By applying the ACS model, it was demonstrated that this challenge could be solved. Parts manufactured by compression molding exhibited the same quality as those simulated with the ACS model. Finally, this innovative modeling approach (fully implemented in the SIGMASOFT® v simulation routine) provides enormous potential for understanding local differences in the quality of rubber parts, being an ideal tool for optimizing rubber parts through simulation routines. - Open Access
Optimization Strategy for Process Design in Rubber Injection Molding: A Simulation-Based Approach Allowing for the Prediction of Mechanical Properties of Vulcanizates
Selecting the optimal settings for the production of rubber goods can be a very time-consuming and resource-intensive process. A promising method for optimizing rubber processing in a short period of time is the use of simulation routines. However, process simulations have only recently enabled meaningful predictions of not only the part’s state of cure but also its mechanical characteristics. As a first approach, second-order polynomials were considered suitable for describing the properties of compression-molded parts. However, more precision is required for injection molding due to the narrower distribution of mechanical characteristics of parts produced at different vulcanization temperatures. This became evident when the approximation of mechanical data with second order models partly revealed significant failures of part behavior prediction. To tackle this issue, a combined approach for approximation is proposed in this contribution by means of logistic growth function in addition to second order polynomials. To feed the model, an experimental plan was designed for producing injection-molded parts from an SBR compound at various temperatures and to different degrees of cure. The parts obtained were then characterized mechanically, and the results were opposed to varying degrees of cure and extents of reaction to calculate the model coefficients. Once available, a simulation-based calculation of the mechanical part quality is possible. The comparison of test results from the simulation and the real process has shown a reliable prediction, as simulation results were found within the natural deviation of the real measurements.
Open AccessOptimization Strategy for Process Design in Rubber Injection Molding: A Simulation-Based Approach Allowing for the Prediction of Mechanical Properties of Vulcanizates
Selecting the optimal settings for the production of rubber goods can be a very time-consuming and resource-intensive process. A promising method for optimizing rubber processing in a short period of time is the use of simulation routines. However, process simulations have only recently enabled meaningful predictions of not only the part’s state of cure but also its mechanical characteristics. As a first approach, second-order polynomials were considered suitable for describing the properties of compression-molded parts. However, more precision is required for injection molding due to the narrower distribution of mechanical characteristics of parts produced at different vulcanization temperatures. This became evident when the approximation of mechanical data with second order models partly revealed significant failures of part behavior prediction. To tackle this issue, a combined approach for approximation is proposed in this contribution by means of logistic growth function in addition to second order polynomials. To feed the model, an experimental plan was designed for producing injection-molded parts from an SBR compound at various temperatures and to different degrees of cure. The parts obtained were then characterized mechanically, and the results were opposed to varying degrees of cure and extents of reaction to calculate the model coefficients. Once available, a simulation-based calculation of the mechanical part quality is possible. The comparison of test results from the simulation and the real process has shown a reliable prediction, as simulation results were found within the natural deviation of the real measurements.
- Open Access
- 1 April 2024
- Published by Elsevier in Polymer Testing
- Vol. 133
Investigation into the state of cure of elastomers through nanoindentation
- 1 April 2024
- Published by Elsevier in Polymer Testing
- Vol. 133
Open AccessInvestigation into the state of cure of elastomers through nanoindentation
- Open Access
- 20 May 2023
- Published by Wiley in Journal of Applied Polymer Science
- Vol. 140 (31)
Peroxide‐based crosslinking of solid silicone rubber, part II: The counter‐intuitive influence of dicumylperoxide concentration on crosslink effectiveness and related network structure
Application of elastomers in general demands the conversion of their soluble networks into crosslinked structures. This abrupt change causes several modifications, both in the atomic/molecular level and at the macro‐scale. In this study, solid silicone rubber (high molecular weight poly(dimethylsiloxane)), was crosslinked with dicumylperoxide (DCP), a widely used crosslinking agent by the rubber industry. The changes caused by different DCP concentrations were investigated, aiming to bring attention to the molecular transformations, usually neglected when processing‐oriented studies are conducted. DCP concentration showed a limited contribution to the network's molecular dynamics, which was found to be mainly dominated by entanglements. The dominance of entanglements over other molecular constraints, like crosslink points, justifies the threshold and counter‐intuitive behavior of tensile and hardness properties. However, differences were found in the crystallization ability after crosslinking, when the more crosslink points were introduced, the lower the crystallinity was and the less stable the PDMS crystallites were. In addition to providing a deeper understanding of an industrially applied rubber system n terms of the effective concentration of DCP, and the reasoning behind such concentration, the findings of this study add to the state‐of‐the‐art comprehension of elastomeric networks, and how they behave on a molecular level.
- 20 May 2023
- Published by Wiley in Journal of Applied Polymer Science
- Vol. 140 (31)
Open AccessPeroxide‐based crosslinking of solid silicone rubber, part II: The counter‐intuitive influence of dicumylperoxide concentration on crosslink effectiveness and related network structure
Application of elastomers in general demands the conversion of their soluble networks into crosslinked structures. This abrupt change causes several modifications, both in the atomic/molecular level and at the macro‐scale. In this study, solid silicone rubber (high molecular weight poly(dimethylsiloxane)), was crosslinked with dicumylperoxide (DCP), a widely used crosslinking agent by the rubber industry. The changes caused by different DCP concentrations were investigated, aiming to bring attention to the molecular transformations, usually neglected when processing‐oriented studies are conducted. DCP concentration showed a limited contribution to the network's molecular dynamics, which was found to be mainly dominated by entanglements. The dominance of entanglements over other molecular constraints, like crosslink points, justifies the threshold and counter‐intuitive behavior of tensile and hardness properties. However, differences were found in the crystallization ability after crosslinking, when the more crosslink points were introduced, the lower the crystallinity was and the less stable the PDMS crystallites were. In addition to providing a deeper understanding of an industrially applied rubber system n terms of the effective concentration of DCP, and the reasoning behind such concentration, the findings of this study add to the state‐of‐the‐art comprehension of elastomeric networks, and how they behave on a molecular level.
- Open Access
Peroxide-Based Crosslinking of Solid Silicone Rubber, Part I: Insights into the Influence of Dicumylperoxide Concentration on the Curing Kinetics and Thermodynamics Determined by a Rheological Approach
Predicting the curing behaviour of industrially employed elastomeric compounds under typical processing conditions in a reliable and scientifically driven way is important for rubber processing simulation routines, such as injection moulding. Herein, a rubber process analyser was employed to study the crosslinking kinetics of solid silicone rubber based on the concentration of dicumylperoxide. A model was proposed to describe the optimal cure time variation with peroxide concentration and temperature, based on the analysis of processing parameters applying kinetic and thermodynamic judgments. Additionally, the conversion rate was described with the aid of a phenomenological model, and the effect of dicumylperoxide concentration on the final crosslink state was investigated using kinetic and thermodynamic explanations. Optimal curing time was affected both by temperature and dicumylperoxide concentration. However, the effects were less pronounced for high temperatures (>170 C) and high concentrations (>0.70 phr). A limit on the crosslink state was detected, meaning that the dicumylperoxide capacity to crosslink the silicone network is restricted by the curing mechanism. Curing restrictions were presumed to be primarily thermodynamic, based on the proton abstraction mechanism that drives the crosslinking reaction. In addition to providing more realistic crosslinking models for rubber injection moulding simulation routines, the results of this study may also explain the chemical behaviour of organic peroxides widely used for silicone crosslinking.Open AccessPeroxide-Based Crosslinking of Solid Silicone Rubber, Part I: Insights into the Influence of Dicumylperoxide Concentration on the Curing Kinetics and Thermodynamics Determined by a Rheological Approach
Predicting the curing behaviour of industrially employed elastomeric compounds under typical processing conditions in a reliable and scientifically driven way is important for rubber processing simulation routines, such as injection moulding. Herein, a rubber process analyser was employed to study the crosslinking kinetics of solid silicone rubber based on the concentration of dicumylperoxide. A model was proposed to describe the optimal cure time variation with peroxide concentration and temperature, based on the analysis of processing parameters applying kinetic and thermodynamic judgments. Additionally, the conversion rate was described with the aid of a phenomenological model, and the effect of dicumylperoxide concentration on the final crosslink state was investigated using kinetic and thermodynamic explanations. Optimal curing time was affected both by temperature and dicumylperoxide concentration. However, the effects were less pronounced for high temperatures (>170 C) and high concentrations (>0.70 phr). A limit on the crosslink state was detected, meaning that the dicumylperoxide capacity to crosslink the silicone network is restricted by the curing mechanism. Curing restrictions were presumed to be primarily thermodynamic, based on the proton abstraction mechanism that drives the crosslinking reaction. In addition to providing more realistic crosslinking models for rubber injection moulding simulation routines, the results of this study may also explain the chemical behaviour of organic peroxides widely used for silicone crosslinking. - 1 February 2021
- Published by SAGE Publications in Journal of Elastomers & Plastics
- Vol. 53 (7) , 806-824
Chemically modified soybean oils as plasticizers for silica-filled e-SBR/Br compounds for tire tread applications
Silica-filled styrene butadiene rubber (SBR)/butadiene rubber (BR) compounds plasticized with mineral oils are mainly used to produce green tire treads. Previous works have demonstrated that the partial replacement of naphthenic oil (ONAF) by bio-based oils can provide processing and performance improvements for rubber compounds, along with environmental benefits. In this study, two modified soybean oils (esterified, OEST or esterified and epoxidized, OEPX) were investigated with the aim of evaluating the complete replacement of ONAF and determining whether the chemical properties of the oils affect the performance of silica-filled E-SBR/BR compounds, using the compound with ONAF as a reference. The physical properties, curing characteristics, morphology, and dynamic mechanical behavior were evaluated. The use of the modified soybean oils decreased the optimal cure time while increasing the crosslink density and the abrasive wear resistance. Further, the compounds with both modified soybean oils showed a good balance of mechanical properties. The modified soybean oils decreased the glass transition temperature of the rubber compounds, thus acting as true plasticizers. At 0°C, the tan δ value of E-SBR/BR/OEPX increased relative to that of E-SBR/BR/ONAF, whereas at 60°C, the values of the compounds with both modified soybean oils showed slight increases. The tan δ values reveal that compared with E-SBR/BR/ONAF, E-SBR/BR/OEPX has better wet grip and a similar rolling resistance, whereas E-SBR/BR/OEST has a higher rolling resistance. Thus, both modified soybean oils can fully replace ONAF and appear to be extremely attractive plasticizers for use in silica-filled E-SBR/BR compounds employed as green tire treads for passenger cars.
- 1 February 2021
- Published by SAGE Publications in Journal of Elastomers & Plastics
- Vol. 53 (7) , 806-824
Chemically modified soybean oils as plasticizers for silica-filled e-SBR/Br compounds for tire tread applications
Silica-filled styrene butadiene rubber (SBR)/butadiene rubber (BR) compounds plasticized with mineral oils are mainly used to produce green tire treads. Previous works have demonstrated that the partial replacement of naphthenic oil (ONAF) by bio-based oils can provide processing and performance improvements for rubber compounds, along with environmental benefits. In this study, two modified soybean oils (esterified, OEST or esterified and epoxidized, OEPX) were investigated with the aim of evaluating the complete replacement of ONAF and determining whether the chemical properties of the oils affect the performance of silica-filled E-SBR/BR compounds, using the compound with ONAF as a reference. The physical properties, curing characteristics, morphology, and dynamic mechanical behavior were evaluated. The use of the modified soybean oils decreased the optimal cure time while increasing the crosslink density and the abrasive wear resistance. Further, the compounds with both modified soybean oils showed a good balance of mechanical properties. The modified soybean oils decreased the glass transition temperature of the rubber compounds, thus acting as true plasticizers. At 0°C, the tan δ value of E-SBR/BR/OEPX increased relative to that of E-SBR/BR/ONAF, whereas at 60°C, the values of the compounds with both modified soybean oils showed slight increases. The tan δ values reveal that compared with E-SBR/BR/ONAF, E-SBR/BR/OEPX has better wet grip and a similar rolling resistance, whereas E-SBR/BR/OEST has a higher rolling resistance. Thus, both modified soybean oils can fully replace ONAF and appear to be extremely attractive plasticizers for use in silica-filled E-SBR/BR compounds employed as green tire treads for passenger cars.