Jan G. Rittig
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- Advanced Combustion Engine Technologies 3
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- Computational Drug Discovery Methods 7
- Control and Systems Engineering top 10%
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- Machine Learning in Materials Science 6
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- Protein Structure and Dynamics 3
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- Petroleum Processing and Analysis 2
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- Chemical Thermodynamics and Molecular Structure 2
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- Enhanced Oil Recovery Techniques 2
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- Phase Equilibria and Thermodynamics 2
- Co-authors
- Alexander MitsosArtur M. SchweidtmannManuel DahmenKobi FeltonAlexei A. LapkinMartin GroheAndrea KönigKai Leonhard
- Journals
- Energy & Fuels (3 papers)Computers & Chemical Engineering (3 papers)Colloids and Surfaces A Physicochemical and Engineering Aspects (1 paper)
- Partner nations
- GermanyNetherlandsUnited Kingdom
In The Last Decade
Jan G. Rittig
13 papers receiving 335 citations
Peers
Comparison fields: 5 of 66
- Fluid Flow and Transfer Processes 47
- Computational Theory and Mathematics 115
- Catalysis 25
- Control and Systems Engineering 82
- Materials Chemistry 147
Countries citing papers authored by Jan G. Rittig
This map shows the geographic impact of Jan G. Rittig'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 Jan G. Rittig with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jan G. Rittig more than expected).
Fields of papers citing papers by Jan G. Rittig
This network shows the impact of papers produced by Jan G. Rittig. 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 Jan G. Rittig. The network helps show where Jan G. Rittig may publish in the future.
Co-authorship network
The 23 scholars most cited alongside Jan G. Rittig, 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 | 2025 | 0 | |
| 2 | 2025 | 2 | |
| 3 | 2024 | 1 | |
| 4 | 2024 | 14 | |
| 5 | 2024 | 12 | |
| 6 | 2024 | 11 | |
| 7 | 2023 | 27 | |
| 8 | 2023 | 29 | |
| 9 | 2023 | 48 | |
| 10 | 2023 | 18 | |
| 11 | 2022 | 22 | |
| 12 | 2021 | 48 | |
| 13 | 2021 | 20 | |
| 14 | 2020 | 92 |
About Jan G. Rittig
Jan G. Rittig is a scholar working on Fluid Flow and Transfer Processes, Computational Theory and Mathematics, Analytical Chemistry, Electrochemistry and Materials Chemistry, having authored 14 papers that have together received 344 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (7 papers), Machine Learning in Materials Science (6 papers), Protein Structure and Dynamics (3 papers), Advanced Combustion Engine Technologies (3 papers), Petroleum Processing and Analysis (2 papers), Chemical Thermodynamics and Molecular Structure (2 papers), Enhanced Oil Recovery Techniques (2 papers) and Phase Equilibria and Thermodynamics (2 papers). The work is most often cited by research in Fluid Flow and Transfer Processes (47 citations), Computational Theory and Mathematics (115 citations), Catalysis (25 citations), Control and Systems Engineering (82 citations) and Materials Chemistry (147 citations). Jan G. Rittig has collaborated with scholars based in Germany, Netherlands and United Kingdom. Frequent co-authors include Alexander Mitsos, Artur M. Schweidtmann, Manuel Dahmen, Kobi Felton, Alexei A. Lapkin, Martin Grohe, Andrea König, Kai Leonhard, Jana M. Weber and Jörn Viell. Their work appears in journals such as Energy & Fuels, Computers & Chemical Engineering, Colloids and Surfaces A Physicochemical and Engineering Aspects, Chemical Science and Chemical Engineering Science.
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.