Matthias Mayr
- Materials Chemistry top 10%
- Condensed Matter Physics top 5%
- Atomic and Molecular Physics, and Optics top 10%
- Ceramics and Composites top 5%
- Fluid Flow and Transfer Processes top 5%
- Co-authors
- W. GötzeMatthias FuchsAjay SinghThomas FranoschStefan OrfFlorian KuhntFabian PoggenhansMaximilian Naumann
- Topics
- Material Dynamics and Properties (9 papers)Advanced Numerical Methods in Computational Mathematics (7 papers)Robot Manipulation and Learning (6 papers)
- Journals
- International Journal for Numerical Methods in EngineeringInternational Journal of Solids and StructuresJournal of Non-Crystalline Solids
- Partner nations
- GermanySwedenUnited States
In The Last Decade
Matthias Mayr
40 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 101
- Materials Chemistry 719
- Condensed Matter Physics 261
- Atomic and Molecular Physics, and Optics 260
- Ceramics and Composites 182
- Fluid Flow and Transfer Processes 155
Countries citing papers authored by Matthias Mayr
This map shows the geographic impact of Matthias Mayr'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 Matthias Mayr with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthias Mayr more than expected).
Fields of papers citing papers by Matthias Mayr
This network shows the impact of papers produced by Matthias Mayr. 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 Matthias Mayr. The network helps show where Matthias Mayr may publish in the future.
Co-authorship network of co-authors of Matthias Mayr
This figure shows the co-authorship network connecting the top 25 collaborators of Matthias Mayr. A scholar is included among the top collaborators of Matthias Mayr based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Matthias Mayr. Matthias Mayr is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 8 | |
| 2 | 5 | |
| 3 | 0 | |
| 4 | 3 | |
| 5 | 0 | |
| 6 | 1 | |
| 7 | 4 | |
| 8 | 3 | |
| 9 | 9 | |
| 10 | 2 | |
| 11 | 14 | |
| 12 | 30 | |
| 13 | 76 | |
| 14 | 16 | |
| 15 | 37 | |
| 16 | 1 | |
| 17 | 152 | |
| 18 | 176 | |
| 19 | 9 | |
| 20 | 2 |
About Matthias Mayr
Matthias Mayr is a scholar working on Structural Biology, Computational Theory and Mathematics and Numerical Analysis, having authored 43 papers that have together received 1.3k indexed citations. Recurring topics across this work include Material Dynamics and Properties (9 papers), Advanced Numerical Methods in Computational Mathematics (7 papers) and Robot Manipulation and Learning (6 papers). The work is most often cited by research in Ceramics and Composites (182 citations), Fluid Flow and Transfer Processes (155 citations) and Structural Biology (32 citations). Matthias Mayr has collaborated with scholars based in Germany, Sweden and United States. Frequent co-authors include W. Götze, Matthias Fuchs, Ajay Singh, Thomas Franosch, Stefan Orf, Florian Kuhnt, Fabian Poggenhans, Maximilian Naumann, Achilleas S. Frangakis and Sabine Pruggnaller. Their work appears in journals such as International Journal for Numerical Methods in Engineering, International Journal of Solids and Structures and Journal of Non-Crystalline Solids.
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.