Dendrimers in Supramolecular Chemistry: From Molecular Recognition to Self-Assembly
- Authors
- Fanwen ZengSteven C. Zimmerman
- Journal
- Chemical Reviews
In The Last Decade
doi.org/10.1021/cr9603892 →Countries where authors are citing Dendrimers in Supramolecular Chemistry: From Molecular Recognition to Self-Assembly
This map shows the geographic impact of Dendrimers in Supramolecular Chemistry: From Molecular Recognition to Self-Assembly. 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 Dendrimers in Supramolecular Chemistry: From Molecular Recognition to Self-Assembly with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dendrimers in Supramolecular Chemistry: From Molecular Recognition to Self-Assembly more than expected).
Fields of papers citing Dendrimers in Supramolecular Chemistry: From Molecular Recognition to Self-Assembly
This network shows the impact of Dendrimers in Supramolecular Chemistry: From Molecular Recognition to Self-Assembly. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Dendrimers in Supramolecular Chemistry: From Molecular Recognition to Self-Assembly.
About Dendrimers in Supramolecular Chemistry: From Molecular Recognition to Self-Assembly
This paper, published in 1997, received 1.2k indexed citations . Written by Fanwen Zeng and Steven C. Zimmerman covering the research area of Molecular Biology and Polymers and Plastics. It is primarily cited by scholars working on Polymers and Plastics (1.0k citations), Molecular Biology (502 citations) and Organic Chemistry (456 citations). Published in Chemical Reviews.
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/10.1021/cr9603892.