Kevin Maik Jablonka

About

Kevin Maik Jablonka is a scholar working on Materials Chemistry, Inorganic Chemistry and Computational Theory and Mathematics. According to data from OpenAlex, Kevin Maik Jablonka has authored 24 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Materials Chemistry, 12 papers in Inorganic Chemistry and 7 papers in Computational Theory and Mathematics. Recurrent topics in Kevin Maik Jablonka’s work include Machine Learning in Materials Science (17 papers), Metal-Organic Frameworks: Synthesis and Applications (12 papers) and Computational Drug Discovery Methods (6 papers). Kevin Maik Jablonka is often cited by papers focused on Machine Learning in Materials Science (17 papers), Metal-Organic Frameworks: Synthesis and Applications (12 papers) and Computational Drug Discovery Methods (6 papers). Kevin Maik Jablonka collaborates with scholars based in Switzerland, United States and Germany. Kevin Maik Jablonka's co-authors include Berend Smit, Seyed Mohamad Moosavi, Daniele Ongari, Andres Ortega‐Guerrero, Heather J. Kulik, Yongjin Lee, Aditya Nandy, Peter G. Boyd, Jon Paul Janet and Philippe Schwaller and has published in prestigious journals such as Chemical Reviews, Journal of the American Chemical Society and Chemical Society Reviews.

In The Last Decade

Co-authorship network of co-authors of Kevin Maik Jablonka i

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Fields of papers citing papers by Kevin Maik Jablonka

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kevin Maik Jablonka. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Kevin Maik Jablonka. The network helps show where Kevin Maik Jablonka may publish in the future.

Countries citing papers authored by Kevin Maik Jablonka

Since Specialization

Citations

This map shows the geographic impact of Kevin Maik Jablonka's research. 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 Kevin Maik Jablonka with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kevin Maik Jablonka more than expected).

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.

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