<abstract xmlns="http://www.w3.org/1999/xhtml"><sec id="j_jdis-2018-0005_s_005_w2aab3b7b5b1b6b1aab1c17b1Aa"><h3>Purpose</h3><p>This study aims to reveal the landscape and trends of graphene research in the world by using data from Chemical Abstracts Service (CAS).</p></sec><sec id="j_jdis-2018-0005_s_006_w2aab3b7b5b1b6b1aab1c17b2Aa"><h3>Design/methodology/approach</h3><p>Index data from CAS have been retrieved on 78,756 papers and 23,057 patents on graphene from 1985 to March 2016, and scientometric methods were used to analyze the growth and distribution of R&amp;D output, topic distribution and evolution, and distribution and evolution of substance properties and roles.</p></sec><sec id="j_jdis-2018-0005_s_007_w2aab3b7b5b1b6b1aab1c17b3Aa"><h3>Findings</h3><p>In recent years R&amp;D in graphene keeps in rapid growth, while China, South Korea and United States are the largest producers in research but China is relatively weak in patent applications in other countries. Research topics in graphene are continuously expanding from mechanical, material, and electrical properties to a diverse range of application areas such as batteries, capacitors, semiconductors, and sensors devices. The roles of emerging substances are increasing in Preparation and Biological Study. More techniques have been included to improve the preparation processes and applications of graphene in various fields.</p></sec><sec id="j_jdis-2018-0005_s_008_w2aab3b7b5b1b6b1aab1c17b4Aa"><h3>Research limitations</h3><p>Only data from CAS is used and some R&amp;D activities solely reported through other channels may be missed. Also more detailed analysis need to be done to reveal the impact of research on development or vice verse, development dynamics among the players, and impact of emerging terms or substance roles on research and technology development.</p></sec><sec id="j_jdis-2018-0005_s_009_w2aab3b7b5b1b6b1aab1c17b5Aa"><h3>Practical implications</h3><p>This will provide a valuable reference for scientists and developers, R&amp;D managers, R&amp;D policy makers, industrial and business investers to understand the landscape and trends of graphene research. Its methodologies can be applied to other fields or with data from other similar sources.</p></sec><sec id="j_jdis-2018-0005_s_010_w2aab3b7b5b1b6b1aab1c17b6Aa"><h3>Originality/value</h3><p>The integrative use of indexing data on papers and patents of CAS and the systematic exploration of the distribution trends in output, topics, substance roles are distinctive and insightful.</p></sec></abstract>

PurposeThis study aims to reveal the landscape and trends of graphene research in the world by using data from Chemical Abstracts Service (CAS).Design/methodology/approachIndex data from CAS have been retrieved on 78,756 papers and 23,057 patents on graphene from 1985 to March 2016, and scientometric methods were used to analyze the growth and distribution of R&D output, topic distribution and evolution, and distribution and evolution of substance properties and roles.FindingsIn recent years R&D in graphene keeps in rapid growth, while China, South Korea and United States are the largest producers in research but China is relatively weak in patent applications in other countries. Research topics in graphene are continuously expanding from mechanical, material, and electrical properties to a diverse range of application areas such as batteries, capacitors, semiconductors, and sensors devices. The roles of emerging substances are increasing in Preparation and Biological Study. More techniques have been included to improve the preparation processes and applications of graphene in various fields.Research limitationsOnly data from CAS is used and some R&D activities solely reported through other channels may be missed. Also more detailed analysis need to be done to reveal the impact of research on development or vice verse, development dynamics among the players, and impact of emerging terms or substance roles on research and technology development.Practical implicationsThis will provide a valuable reference for scientists and developers, R&D managers, R&D policy makers, industrial and business investers to understand the landscape and trends of graphene research. Its methodologies can be applied to other fields or with data from other similar sources.Originality/valueThe integrative use of indexing data on papers and patents of CAS and the systematic exploration of the distribution trends in output, topics, substance roles are distinctive and insightful.

Trends Analysis of Graphene Research and Development

Journal of Data and Information Science

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

{"article-title":"Trends Analysis of Graphene Research and Development"}

PurposeThis study aims to reveal the landscape and trends of graphene research in the world by using data from Chemical Abstracts Service...

Trends Analysis of Graphene Research and Development

Article Category: Research Paper

Online veröffentlicht: 13. März 2018

Seitenbereich: 82 - 100

Eingereicht: 15. Jan. 2018

Akzeptiert: 09. Feb. 2018

DOI: https://doi.org/10.2478/jdis-2018-0005

Schlüsselwörter
Graphene, R&D distribution, Topic distribution and evolution, Substance roles distribution and evolution, Text mining

© 2018 Walter de Gruyter GmbH, Berlin/Boston

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Trends Analysis of Graphene Research and Development

Article Category: Research Paper

Online veröffentlicht: 13. März 2018

Seitenbereich: 82 - 100

Eingereicht: 15. Jan. 2018

Akzeptiert: 09. Feb. 2018

DOI: https://doi.org/10.2478/jdis-2018-0005

SchlüsselwörterGraphene, R&D distribution, Topic distribution and evolution, Substance roles distribution and evolution, Text mining

© 2018 Walter de Gruyter GmbH, Berlin/Boston

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Schlüsselwörter
Graphene, R&D distribution, Topic distribution and evolution, Substance roles distribution and evolution, Text mining