Melt-Mixed 3D Hierarchical Graphene/Polypropylene Nanocomposites with Low Electrical Percolation Threshold
Autor: | Aleksandar Matic, Christian Müller, Antonis Gitsas, Thomas Gkourmpis, Karolina Gaska, Davide Tranchida, Roland Kádár |
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Jazyk: | angličtina |
Rok vydání: | 2019 |
Předmět: |
Polypropylene
Nanocomposite Materials science electrical conductivity melt mixing Graphene General Chemical Engineering graphene Percolation threshold Article law.invention chemistry.chemical_compound electrical percolation chemistry law Percolation nanocomposites General Materials Science Graphite Crystallization Composite material Dispersion (chemistry) polypropylene |
Zdroj: | Nanomaterials Volume 9 Issue 12 |
ISSN: | 2079-4991 |
DOI: | 10.3390/nano9121766 |
Popis: | Graphene-based materials are a family of carbonaceous structures that can be produced using a variety of processes either from graphite or other precursors. These materials are typically a few layered sheets of graphene in the form of platelets and maintain some of the properties of pristine graphene (such as two-dimensional platelet shape, aspect ratio, and graphitic bonding). In this work we present melt mixed graphene-based polypropylene systems with significantly reduced percolation threshold. Traditionally melt-mixed systems suffer from poor dispersion that leads to high electrical percolation values. In contrast in our work, graphene was added into an isotactic polypropylene matrix, achieving an electrical percolation threshold of ~1 wt.%. This indicates that the filler dispersion process has been highly efficient, something that leads to the suppression of the &beta phase that have a strong influence on the crystallization behavior and subsequent thermal and mechanical performance. The electrical percolation values obtained are comparable with reported solution mixed systems, despite the use of simple melt mixing protocols and the lack of any pre or post-treatment of the final compositions. The latter is of particular importance as the preparation method used in this work is industrially relevant and is readily scalable. |
Databáze: | OpenAIRE |
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