Simon Wengert
Impact in
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- Machine Learning in Materials Science
- X-ray Diffraction in Crystallography
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- Computational Drug Discovery Methods
Papers in
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- Machine Learning in Materials Science 6
- Electronic and Structural Properties of Oxides 1
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- Computational Drug Discovery Methods 4
- Co-authors
- Karsten Reuter (7 shared papers)Johannes T. Margraf (4 shared papers)Gábor Cśanyi (4 shared papers)Heike Boehm (1 shared paper)Ann‐Kathrin Huber (1 shared paper)Christian Künkel (2 shared papers)Noam Bernstein (2 shared papers)Tamás K. Stenczel (2 shared papers)
- Journals
- Advanced Energy Materials (2 papers)Chemical Science (1 paper)Machine Learning Science and Technology (1 paper)Frontiers in Oncology (1 paper)The Journal of Chemical Physics (1 paper)
- Partner nations
- GermanyUnited KingdomUnited States
In The Last Decade
Simon Wengert
10 papers receiving 408 citations
Peers
Comparison fields: 5 of 76
- Materials Chemistry 260
- Computational Theory and Mathematics 79
- Physical and Theoretical Chemistry 38
- Cell Biology 50
- Catalysis 20
Countries citing papers authored by Simon Wengert
This map shows the geographic impact of Simon Wengert'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 Simon Wengert with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Simon Wengert more than expected).
Fields of papers citing papers by Simon Wengert
This network shows the impact of papers produced by Simon Wengert. 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 Simon Wengert. The network helps show where Simon Wengert may publish in the future.
Co-authors
The 25 scholars most cited alongside Simon Wengert, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 93 | |
| 2 | 2021 | 82 | |
| 3 | 2017 | 82 | |
| 4 | 2021 | 67 | |
| 5 | 2022 | 31 | |
| 6 | 2022 | 28 | |
| 7 | 2024 | 13 | |
| 8 | 2023 | 10 | |
| 9 | 2017 | 3 | |
| 10 | 2021 | 1 |
About Simon Wengert
Simon Wengert is a scholar working on Materials Chemistry, Computational Theory and Mathematics, Physical and Theoretical Chemistry, Electrical and Electronic Engineering and Biomedical Engineering, having authored 10 papers that have together received 410 indexed citations. Recurring topics across this work include Machine Learning in Materials Science (6 papers), Computational Drug Discovery Methods (4 papers), Crystallography and molecular interactions (3 papers), Advanced Battery Materials and Technologies (2 papers), Advancements in Battery Materials (2 papers), Glycosylation and Glycoproteins Research (1 paper), Electronic and Structural Properties of Oxides (1 paper) and Chemical Synthesis and Characterization (1 paper). The work is most often cited by research in Materials Chemistry (260 citations), Computational Theory and Mathematics (79 citations), Physical and Theoretical Chemistry (38 citations), Cell Biology (50 citations) and Catalysis (20 citations). Simon Wengert has collaborated with scholars based in Germany, United Kingdom and United States. Frequent co-authors include Karsten Reuter, Johannes T. Margraf, Gábor Cśanyi, Heike Boehm, Ann‐Kathrin Huber, Christian Künkel, Noam Bernstein, Tamás K. Stenczel, Bingqing Cheng and Ryan‐Rhys Griffiths. Their work appears in journals such as Advanced Energy Materials, Chemical Science, Machine Learning Science and Technology, Frontiers in Oncology and The Journal of Chemical Physics.
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.