Institute for Functional Intelligent Materials
Impact in
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- Electrocatalysts for Energy Conversion
- Advanced Photocatalysis Techniques
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- 2D Materials and Applications
- Graphene research and applications
Papers in
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- 2D Materials and Applications 99
- Graphene research and applications 62
- Machine Learning in Materials Science 21
- Top scholars
- Kostya S. NovoselovShaila AfrojNazmul KarimDaria V. AndreevaMd. Rashedul IslamJiong Ping LuGuillermo Carlos BazanShuzhi Sam Ge
- Journals
- Nature Communications (32 papers)Advanced Materials (29 papers)ACS Nano (25 papers)Advanced Functional Materials (21 papers)Physical review. B. (16 papers)
- Partner nations
- SingaporeChinaUnited States
In The Last Decade
Institute for Functional Intelligent Materials
425 papers receiving 8.2k citations
Peers
Comparison fields: 5 of 135
- Renewable Energy, Sustainability and the Environment 1.2k
- Materials Chemistry 2.8k
- Catalysis 205
- Electronic, Optical and Magnetic Materials 661
- Biomedical Engineering 1.1k
Countries citing scholars working at Institute for Functional Intelligent Materials
This map shows the geographic impact of research produced by authors working at Institute for Functional Intelligent Materials. 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 papers produced at Institute for Functional Intelligent Materials with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Institute for Functional Intelligent Materials more than expected).
Fields of papers published by authors at Institute for Functional Intelligent Materials
This network shows the impact of papers affiliated with Institute for Functional Intelligent Materials at the time of their publication. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers affiliated with Institute for Functional Intelligent Materials at the time of their publication.
About Institute for Functional Intelligent Materials
In recent decades, authors affiliated with Institute for Functional Intelligent Materials have published 492 papers, which have received a total of 8.4k indexed citations . Scholars at this organization have produced 206 papers in Materials Chemistry, 25 papers in Condensed Matter Physics, 63 papers in Atomic and Molecular Physics, and Optics, 33 papers in Electronic, Optical and Magnetic Materials and 4 papers in Structural Biology on the topics of 2D Materials and Applications (99 papers), Graphene research and applications (62 papers), Magnetic properties of thin films (27 papers), Machine Learning in Materials Science (21 papers), Supercapacitor Materials and Fabrication (19 papers), Advanced Memory and Neural Computing (19 papers), Microbial Fuel Cells and Bioremediation (18 papers) and Nanopore and Nanochannel Transport Studies (17 papers). Their work is cited by papers focused on Renewable Energy, Sustainability and the Environment (1.2k citations), Materials Chemistry (2.8k citations), Catalysis (205 citations), Electronic, Optical and Magnetic Materials (661 citations) and Biomedical Engineering (1.1k citations). Authors at Institute for Functional Intelligent Materials collaborate with scholars in Singapore, China and United States and have published in prestigious journals including Nature Communications, Advanced Materials, ACS Nano, Advanced Functional Materials and Physical review. B.. Some of Institute for Functional Intelligent Materials's most productive authors include Kostya S. Novoselov, Shaila Afroj, Nazmul Karim, Daria V. Andreeva, Md. Rashedul Islam, Jiong Ping Lu, Guillermo Carlos Bazan, Shuzhi Sam Ge, Bin Liu and Jing Li.
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.