When and how self-cleaning of superhydrophobic surfaces works
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- Science Advances
In The Last Decade
doi.org/10.1126/sciadv.aaw9727 →Countries where authors are citing When and how self-cleaning of superhydrophobic surfaces works
This map shows the geographic impact of When and how self-cleaning of superhydrophobic surfaces works. 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 When and how self-cleaning of superhydrophobic surfaces works with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites When and how self-cleaning of superhydrophobic surfaces works more than expected).
Fields of papers citing When and how self-cleaning of superhydrophobic surfaces works
This network shows the impact of When and how self-cleaning of superhydrophobic surfaces works. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the When and how self-cleaning of superhydrophobic surfaces works.
About When and how self-cleaning of superhydrophobic surfaces works
This paper, published in 2020, received 328 indexed citations . Written by Florian Geyer, Maria D’Acunzi, Alexander Saal, Nan Gao, Anke Kaltbeitzel, Rüdiger Berger, Hans‐Jürgen Butt and Doris Vollmer covering the research area of Surfaces, Coatings and Films, Mechanics of Materials and Computational Mechanics. It is primarily cited by scholars working on Surfaces, Coatings and Films (263 citations), Computational Mechanics (101 citations) and Biomedical Engineering (96 citations). Published in Science Advances.
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/10.1126/sciadv.aaw9727.