The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Enhanced electrical conductivity and piezoresistive sensing in multi-wall carbon nanotubes/polydimethylsiloxane nanocomposites via the construction of a self-segregated structure
Abstract
Self-segregated PDMS/MWCNT nanocomposites exhibit high piezoresistive sensitivity, low percolation threshold and an enhanced mechanical properties.
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Citations
Cites
Kim, D.-H., Lu, N., Ma, R., Kim, Y.-S., Kim, R.-H., Wang, S., Wu, J., Won, S. M., Tao, H., Islam, A., et al. (2011) · Science · doi:10.1126/science.1206157 · Cited by 4,836
Cited by
Electrically conductive polymer composites for smart flexible strain sensors: a critical review
Liu, H., Li, Q., Zhang, S., Yin, R., Liu, X., He, Y., Dai, K., Shan, C., Guo, J., Liu, C., et al. (2018) · Journal of Materials Chemistry C · doi:10.1039/c8tc04079f · Cited by 709
Self-citationZhang, X., Zhao, N., & He, C. (2020) · Progress in Materials Science · doi:10.1016/j.pmatsci.2020.100672 · Cited by 293
Metadata
- Authors
- Wang, M., Zhang, K., Dai, X.-X., Li, Y., Guo, J., Liu, H., Li, G.-H., Tan, Y.-J., Zeng, J.-B., & Guo, Z.
- Venue
- Nanoscale
- Publisher
- Royal Society of Chemistry (RSC)
- Published
- 2017
- Volume
- 9
- Issue
- 31
- Pages
- 11017-11026
- ISSN
- 2040-3364 (ISSN-L)
- 2040-3372
- OpenAlex
- W2616749986
- Cited by
- 234
- References
- 1
- FWCI
- 12.53
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Enhanced electrical conductivity and piezoresistive sensing in multi-wall carbon nanotubes/polydimethylsiloxane nanocomposites via the construction of a self-segregated structure. https://app.cochat.ai/papers/10.1039/c7nr02322g
- The paper
- Wang, M., Zhang, K., Dai, X.-X., Li, Y., Guo, J., Liu, H., Li, G.-H., Tan, Y.-J., Zeng, J.-B., & Guo, Z. (2017). Enhanced electrical conductivity and piezoresistive sensing in multi-wall carbon nanotubes/polydimethylsiloxane nanocomposites via the construction of a self-segregated structure. Nanoscale. https://doi.org/10.1039/c7nr02322g
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
