Daniel Siegmann
Impact in
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- Particle Detector Development and Performance
- Neutrino Physics Research
- Dark Matter and Cosmic Phenomena
- Particle physics theoretical and experimental studies
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- Radiation Detection and Scintillator Technologies
Papers in
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- Particle Detector Development and Performance 8
- Neutrino Physics Research 7
- Dark Matter and Cosmic Phenomena 3
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- Radiation Detection and Scintillator Technologies 5
- Co-authors
- Marco Carminati (8 shared papers)C. Fiorini (8 shared papers)P. Lechner (8 shared papers)S. Mertens (8 shared papers)T. Houdy (2 shared papers)F. Edzards (4 shared papers)David J. Fink (2 shared papers)T. Brunst (1 shared paper)
- Journals
- Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment (3 papers)Journal of Instrumentation (2 papers)2021 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) (1 paper)Virtual Community of Pathological Anatomy (University of Castilla La Mancha) (2 papers)
In The Last Decade
Daniel Siegmann
6 papers receiving 19 citations
Peers
Comparison fields: 5 of 9
- Nuclear and High Energy Physics 14
- Radiation 8
- Statistics, Probability and Uncertainty 1
- Hardware and Architecture 1
- Spectroscopy 1
Countries citing papers authored by Daniel Siegmann
This map shows the geographic impact of Daniel Siegmann'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 Daniel Siegmann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Siegmann more than expected).
Fields of papers citing papers by Daniel Siegmann
This network shows the impact of papers produced by Daniel Siegmann. 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 Daniel Siegmann. The network helps show where Daniel Siegmann may publish in the future.
Co-authors
The 15 scholars most cited alongside Daniel Siegmann, 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 | 2021 | 5 | |
| 2 | 2021 | 5 | |
| 3 | 2023 | 4 | |
| 4 | 2018 | 3 | |
| 5 | 2021 | 1 | |
| 6 | 2020 | 1 | |
| 7 | 2025 | 0 | |
| 8 | 2023 | 0 |
About Daniel Siegmann
Daniel Siegmann is a scholar working on Nuclear and High Energy Physics, Radiation, Electrical and Electronic Engineering, Infectious Diseases and Organic Chemistry, having authored 8 papers that have together received 19 indexed citations. Recurring topics across this work include Particle Detector Development and Performance (8 papers), Neutrino Physics Research (7 papers), Radiation Detection and Scintillator Technologies (5 papers), Dark Matter and Cosmic Phenomena (3 papers) and CCD and CMOS Imaging Sensors (1 paper). The work is most often cited by research in Nuclear and High Energy Physics (14 citations), Radiation (8 citations), Statistics, Probability and Uncertainty (1 citation), Hardware and Architecture (1 citation) and Spectroscopy (1 citation). Daniel Siegmann has collaborated with scholars based in Germany and Italy. Frequent co-authors include Marco Carminati, C. Fiorini, P. Lechner, S. Mertens, T. Houdy, F. Edzards, David J. Fink, T. Brunst, M. Steidl and M. Slezák. Their work appears in journals such as Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment, Journal of Instrumentation, 2021 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) and Virtual Community of Pathological Anatomy (University of Castilla La Mancha).
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.