Electrical conductivity of carbon-polymer composites as a function of carbon content

387 indexed citations
published 1982

Countries where authors are citing Electrical conductivity of carbon-polymer composites as a function of carbon content

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This map shows the geographic impact of Electrical conductivity of carbon-polymer composites as a function of carbon content. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Electrical conductivity of carbon-polymer composites as a function of carbon content with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Electrical conductivity of carbon-polymer composites as a function of carbon content more than expected).

Fields of papers citing Electrical conductivity of carbon-polymer composites as a function of carbon content

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Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of Electrical conductivity of carbon-polymer composites as a function of carbon content. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Electrical conductivity of carbon-polymer composites as a function of carbon content.

About Electrical conductivity of carbon-polymer composites as a function of carbon content

This paper, published in 1982, received 387 indexed citations . Written by Keizo Miyasaka, Eiichiro Jojima, Masao Sumita and Kinzo Ishikawa covering the research area of Pollution, Polymers and Plastics and Electrical and Electronic Engineering. It is primarily cited by scholars working on Polymers and Plastics (248 citations), Biomedical Engineering (183 citations) and Materials Chemistry (118 citations). Published in Journal of Materials Science.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

This paper is also available at doi.org/10.1007/bf00540785.

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