| People | Locations | Statistics |
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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Kononenko, Denys |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Bih, L. |
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| Casati, R. |
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| Muller, Hermance |
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| Kočí, Jan | Prague |
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| Šuljagić, Marija |
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| Kalteremidou, Kalliopi-Artemi | Brussels |
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| Azam, Siraj |
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| Ospanova, Alyiya |
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| Blanpain, Bart |
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| Ali, M. A. |
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| Popa, V. |
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| Rančić, M. |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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| Landes, Michael |
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| Rignanese, Gian-Marco |
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Jacob, Timo
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (22/22 displayed)
- 2024Process optimization of the morphological properties of epoxy resin molding compounds using response surface designcitations
- 2024Insights into electrode–electrolyte interfaces by in situ scanning tunnelling microscopy
- 2024Conjugated Polyimidazole Nanoparticles as Biodegradable Electrode Materials for Organic Batteries
- 2024In situ monitoring of the curing of highly filled epoxy molding compounds: the influence of reaction type and silica content on cure kinetic modelscitations
- 2024Optimizing epoxy molding compound processing: a multi-sensor approach to enhance material characterization and process reliability
- 2023Entropic contributions to sodium solvation and solvent stabilization upon electrochemical sodium deposition from diglyme and propylene carbonate electrolytes
- 2023Fully-conjugated polyimidazole nanoparticles as active material in biodegradable electrodes for organic batteries
- 2023Conjugated polyimidazole nanoparticles as biodegradable electrode materials for organic batteriescitations
- 2022First‐Principles Studies on the Atomistic Properties of Metallic Magnesium as Anode Material in Magnesium‐Ion Batteries
- 2022First-principles studies on the atomistic properties of metallic magnesium as snode material in magnesium-ion batteries
- 2022Initial Stages of Sodium Deposition onto Au(111) from [MPPip][TFSI]: An In‐Situ STM Study for Sodium‐Ion Battery Electrolytes
- 2022An interfacial study of Au(111) electrodes in deep eutectic solvents
- 2021Electrodeposition of Zinc onto Au(111) and Au(100) from the Ionic Liquid [MPPip][TFSI]
- 2021Hydrogen Peroxide Oxidation Reaction on a 4-Mercaptopyridine Self-Assembled Monolayer on Au(111) Metallized by Platinum Nanoislandscitations
- 2019Synthesis, structural and morphological characterizations of nano-Ru-based perovskites/RGO composites
- 2019Synthesis, structural and morphological characterizations of nano-Ru-based perovskites/RGO compositescitations
- 2019An electrochemical route for hot alkaline blackening of steel: a nitrite free approach.
- 2019Towards quantitative treatment of electron pair distribution functioncitations
- 2018Electrocatalytic Behavior of Pd and Pt Nanoislands Deposited onto 4,4′-Dithiodipyridine SAMs on Au(111)citations
- 2017Stabilization of Low-Valent Iron(I) in a High-Valent Vanadium(V) Oxide Clustercitations
- 2012Surface Modification of a n-Si(111) Electrode through Aldehyde Grafting and Subsequent Metallization: Theory and Experiment
- 2011Au@Hg Nanoalloy Formation Through Direct Amalgamation: Structural, Spectroscopic, and Computational Evidence for Slow Nanoscale Diffusioncitations
Places of action
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article
In situ monitoring of the curing of highly filled epoxy molding compounds: the influence of reaction type and silica content on cure kinetic models
Abstract
Monitoring of molding processes is one of the most challenging future tasks in polymer processing. In this work, the in situ monitoring of the curing behavior of highly filled EMCs (silica filler content ranging from 73 to 83 wt%) and the effect of filler load on curing kinetics are investigated. Kinetic modelling using the Friedman approach was applied using real-time process data obtained from in situ DEA measurements, and these online kinetic models were compared with curing analysis data obtained from offline DSC measurements. For an autocatalytic fast-reacting material to be processed above the glass transition temperature Tg and for an autocatalytic slow-reacting material to be processed below Tg, time–temperature–transformation (TTT) diagrams were generated to investigate the reaction behavior regarding Tg progression. Incorporating a material containing a lower silica filler content of 10 wt% enabled analysis of the effects of filler content on sensor sensitivity and curing kinetics. Lower silica particle content (and a larger fraction of organic resin, respectively) favored reaction kinetics, resulting in a faster reaction towards Tg1. Kinetic analysis using DEA and DSC facilitated the development of highly accurate prediction models using the Friedman model-free approach. Lower silica particle content resulted in enhanced sensitivity of the analytical method, leading, in turn, to more precise prediction models for the degree of cure.