The DOI matches its Crossref record; 41 of the 41 references it cites were found in a registry or an index.
Electrical conductivity of CNT/polymer composites: 3D printing, measurements and modeling
Open accessAbstract
We present electrical conductivity measurements and modeling aspects of carbon nanotube (CNT)/polymer composites enabled via fused filament fabrication (FFF) additive manufacturing (AM). CNT/polylactic acid (PLA) and CNT/high density polyethylene (HDPE) filament feedstocks were synthesized through melt blending with controlled CNT loading to realize 3D printed polymer nanocomposites. Electrical conductivity of 3D printed CNT/PLA and CNT/HDPE composites was measured for various CNT loadings. Low percolation thresholds were obtained from measured data as 0.23 vol. % and 0.18 vol. % of CNTs for CNT/PLA and CNT/HDPE nanocomposites, respectively. Moreover, a micromechanics-based two-parameter agglomeration model was developed to predict the electrical conductivity of CNT/polymer composites. We further show that the two agglomeration parameters can also be used to describe segregated structures, wherein nanofillers are constrained to certain locations within the matrix. To the best of our knowledge, this is the first ever electrical conductivity model to account for segregation of CNTs in the matrix. A good agreement between measured conductivity and predictions demonstrates the adequacy of the proposed model. We further evince the robustness of the model by accurately capturing the conductivity measurements reported in the literature for both elastomeric and thermoplastic nanocomposites. The findings of the study would provide guidelines for the design of electro-conductive polymer nanocomposites.
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Cites
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Cited by
Yanamandra, K., Chen, G. L., Xu, X., Mac, G., & Gupta, N. (2020) · Composites Science and Technology · doi:10.1016/j.compscitech.2020.108318 · Cited by 72
Metadata
- Authors
- Mora, A., Verma, P., & Kumar, S.
- Venue
- Composites Part B: Engineering
- Publisher
- Elsevier BV
- Published
- 2020-02
- Volume
- 183
- Pages
- 107600
- ISSN
- 1359-8368 (ISSN-L)
- OpenAlex
- W2990009619
- Cited by
- 294
- References
- 41
- FWCI
- 8.42
- Type
- journal article
- Language
- en
- Open access
- hybrid
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