Daniel Elbrecht
Impact in
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- 3D Printing in Biomedical Research
- Innovative Microfluidic and Catalytic Techniques Innovation
- Microfluidic and Bio-sensing Technologies
- Microfluidic and Capillary Electrophoresis Applications
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- Neuroscience and Neural Engineering
Papers in ⓘ
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- Neural dynamics and brain function 3
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- Ferroelectric and Negative Capacitance Devices 3
- Advanced Memory and Neural Computing 3
- Co-authors
- James J. Hickman (3 shared papers)Michael L. Shuler (3 shared papers)Christopher J. Long (3 shared papers)Lee Bridges (2 shared papers)Adrian Roth (2 shared papers)Christopher W. McAleer (2 shared papers)John W. Rumsey (2 shared papers)Ying I. Wang (2 shared papers)
- Journals
- Science Translational Medicine (1 paper)Advanced Science (1 paper)MRS Communications (1 paper)BearWorks (Missouri State University) (1 paper)OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (3 papers)
- Partner nations
- United StatesSwitzerland
In The Last Decade
Daniel Elbrecht
7 papers receiving 225 citations
Peers
Comparison fields: 5 of 52
- Biomedical Engineering 183
- Cellular and Molecular Neuroscience 45
- Biophysics 12
- Hepatology 14
- Oncology 31
Countries citing papers authored by Daniel Elbrecht
This map shows the geographic impact of Daniel Elbrecht'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 Elbrecht with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Elbrecht more than expected).
Fields of papers citing papers by Daniel Elbrecht
This network shows the impact of papers produced by Daniel Elbrecht. 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 Elbrecht. The network helps show where Daniel Elbrecht may publish in the future.
Co-authors
The 23 scholars most cited alongside Daniel Elbrecht, 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 | 2019 | 141 | |
| 2 | 2020 | 70 | |
| 3 | 2019 | 11 | |
| 4 | 2020 | 7 | |
| 5 | 2020 | 3 | |
| 6 | 2013 | 2 | |
| 7 | 2020 | 1 |
About Daniel Elbrecht
Daniel Elbrecht is a scholar working on Cognitive Neuroscience, Electrical and Electronic Engineering, Biomedical Engineering, Molecular Biology and Cellular and Molecular Neuroscience, having authored 7 papers that have together received 235 indexed citations. Recurring topics across this work include Neural dynamics and brain function (3 papers), Ferroelectric and Negative Capacitance Devices (3 papers), 3D Printing in Biomedical Research (3 papers), Advanced Memory and Neural Computing (3 papers), Neuroscience and Neural Engineering (2 papers), Genetics, Bioinformatics, and Biomedical Research (1 paper), Pluripotent Stem Cells Research (1 paper) and Receptor Mechanisms and Signaling (1 paper). The work is most often cited by research in Biomedical Engineering (183 citations), Cellular and Molecular Neuroscience (45 citations), Biophysics (12 citations), Hepatology (14 citations) and Oncology (31 citations). Daniel Elbrecht has collaborated with scholars based in United States and Switzerland. Frequent co-authors include James J. Hickman, Michael L. Shuler, Christopher J. Long, Lee Bridges, Adrian Roth, Christopher W. McAleer, John W. Rumsey, Ying I. Wang, Candace Martin and Franz Schuler. Their work appears in journals such as Science Translational Medicine, Advanced Science, MRS Communications, BearWorks (Missouri State University) and OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information).
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.