Filler network structure in graphene nanoplatelet (GNP)-filled polymethyl methacrylate (PMMA) composites: From thermorheology to electrically and thermally conductive properties. (September 2020)
- Record Type:
- Journal Article
- Title:
- Filler network structure in graphene nanoplatelet (GNP)-filled polymethyl methacrylate (PMMA) composites: From thermorheology to electrically and thermally conductive properties. (September 2020)
- Main Title:
- Filler network structure in graphene nanoplatelet (GNP)-filled polymethyl methacrylate (PMMA) composites: From thermorheology to electrically and thermally conductive properties
- Authors:
- Yang, Bin
Pan, Yang
Yu, Yangnan
Wu, Jinpu
Xia, Ru
Wang, Shuqin
Wang, Yingying
Su, Lifen
Miao, Jibin
Qian, Jiasheng
Shi, You
Tu, Youlei - Abstract:
- Abstract: In this work, graphene nanoplatelet (GNP) filled polymethyl methacrylate (PMMA) composites were prepared using solution method via a specially designed route and relatively high thermal conductivities of the composites were achieved at a low GNP loading. The effect of GNP content on rheological behavior, thermal and electrical conductivity of the composites was intensively investigated. Thermorheological complexity was displayed at elevated GNP loading, and the rheological percolation threshold of GNP in PMMA decreased from 7.96 wt% at 220 °C to 4.02 wt% at 260 °C according to Winter - Chambon method, suggesting that GNP was more likely to form a seepage network at higher temperature. The DMTA results showed that the increase in moduli of the composites should be ascribed to the formation of the GNP-GNP network structure. The electrical conductivity of the composites underwent a sudden jump by seven orders of magnitude, which also indicated the formation of a GNP conductive pathway in the matrix with an electrical percolation threshold of 2–4 wt%. The results of transient temperature measurement were in good consistent with the thermal conductivity versus GNP loading, which was compared with various thermal conduction models with a modified Agari model presenting an acceptable evaluation of the dispersion status of GNP in the matrix. The experimental electrical and thermal conductivities as a function of GNP content could well be interpreted by the filler networkAbstract: In this work, graphene nanoplatelet (GNP) filled polymethyl methacrylate (PMMA) composites were prepared using solution method via a specially designed route and relatively high thermal conductivities of the composites were achieved at a low GNP loading. The effect of GNP content on rheological behavior, thermal and electrical conductivity of the composites was intensively investigated. Thermorheological complexity was displayed at elevated GNP loading, and the rheological percolation threshold of GNP in PMMA decreased from 7.96 wt% at 220 °C to 4.02 wt% at 260 °C according to Winter - Chambon method, suggesting that GNP was more likely to form a seepage network at higher temperature. The DMTA results showed that the increase in moduli of the composites should be ascribed to the formation of the GNP-GNP network structure. The electrical conductivity of the composites underwent a sudden jump by seven orders of magnitude, which also indicated the formation of a GNP conductive pathway in the matrix with an electrical percolation threshold of 2–4 wt%. The results of transient temperature measurement were in good consistent with the thermal conductivity versus GNP loading, which was compared with various thermal conduction models with a modified Agari model presenting an acceptable evaluation of the dispersion status of GNP in the matrix. The experimental electrical and thermal conductivities as a function of GNP content could well be interpreted by the filler network structure as observed in morphological studies. Highlights: Thermorheological complexity displayed at elevated GNP loadings. Temperature dependence of rheological percolation threshold of GNP in PMMA. Electrical percolation threshold of GNP in PMMA within concentration of 2–4 wt%. Thermal conductivity versus GNP loading reasonably predicted by a modified Agari model. Relatively high thermal conductivities of composites achieved at low GNP loadings. … (more)
- Is Part Of:
- Polymer testing. Volume 89(2020)
- Journal:
- Polymer testing
- Issue:
- Volume 89(2020)
- Issue Display:
- Volume 89, Issue 2020 (2020)
- Year:
- 2020
- Volume:
- 89
- Issue:
- 2020
- Issue Sort Value:
- 2020-0089-2020-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-09
- Subjects:
- Polymethyl methacrylate (PMMA) -- Graphene nanoplatelet (GNP) -- Filler network -- Thermorheological complexity -- Conductivity
Polymers -- Testing -- Periodicals
Polymères -- Tests -- Périodiques
620.1920287 - Journal URLs:
- http://www.sciencedirect.com/science/journal/01429418 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.polymertesting.2020.106575 ↗
- Languages:
- English
- ISSNs:
- 0142-9418
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 6547.740500
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 24940.xml