Daniel Marchand
Impact in
- Metals and Alloys top 5%
- Hydrogen embrittlement and corrosion behaviors in metals
-
- Microstructure and mechanical properties
- Machine Learning in Materials Science
- Nuclear Materials and Properties
- Corrosion Behavior and Inhibition
- X-ray Diffraction in Crystallography
Papers in
-
- Machine Learning in Materials Science 4
- X-ray Diffraction in Crystallography 2
- Microstructure and mechanical properties 2
-
- Aluminum Alloy Microstructure Properties 5
- Co-authors
- W.A. Curtin (3 shared papers)Albert Glensk (2 shared papers)Abhinav Jain (2 shared papers)W. A. Curtin (2 shared papers)David L. McDowell (1 shared paper)Xiao Zhou (1 shared paper)Jun Song (1 shared paper)Ting Zhu (1 shared paper)
- Journals
- Physical Review Materials (3 papers)Physical Review Letters (1 paper)Acta Materialia (1 paper)MRS Bulletin (1 paper)PubMed (1 paper)
- Partner nations
- SwitzerlandAustriaUnited States
In The Last Decade
Daniel Marchand
7 papers receiving 380 citations
Peers
Comparison fields: 5 of 38
- Metals and Alloys 87
- Materials Chemistry 290
- Aerospace Engineering 151
- Mechanical Engineering 162
- Structural Biology 3
Countries citing papers authored by Daniel Marchand
This map shows the geographic impact of Daniel Marchand'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 Marchand with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Marchand more than expected).
Fields of papers citing papers by Daniel Marchand
This network shows the impact of papers produced by Daniel Marchand. 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 Marchand. The network helps show where Daniel Marchand may publish in the future.
Co-authors
The 18 scholars most cited alongside Daniel Marchand, 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 | 119 | |
| 2 | 2016 | 100 | |
| 3 | 2020 | 73 | |
| 4 | 2021 | 35 | |
| 5 | 2022 | 28 | |
| 6 | 2012 | 25 | |
| 7 | 2020 | 1 | |
| 8 | 2025 | 0 |
About Daniel Marchand
Daniel Marchand is a scholar working on Materials Chemistry, Aerospace Engineering, Metals and Alloys, Mechanical Engineering and Mechanics of Materials, having authored 8 papers that have together received 381 indexed citations. Recurring topics across this work include Aluminum Alloy Microstructure Properties (5 papers), Machine Learning in Materials Science (4 papers), X-ray Diffraction in Crystallography (2 papers), Aluminum Alloys Composites Properties (2 papers), Microstructure and mechanical properties (2 papers), Hydrogen embrittlement and corrosion behaviors in metals (2 papers), Magnesium Alloys: Properties and Applications (1 paper) and Metal and Thin Film Mechanics (1 paper). The work is most often cited by research in Metals and Alloys (87 citations), Materials Chemistry (290 citations), Aerospace Engineering (151 citations), Mechanical Engineering (162 citations) and Structural Biology (3 citations). Daniel Marchand has collaborated with scholars based in Switzerland, Austria and United States. Frequent co-authors include W.A. Curtin, Albert Glensk, Abhinav Jain, W. A. Curtin, David L. McDowell, Xiao Zhou, Jun Song, Ting Zhu, Stefan Pogatscher and Matheus A. Tunes. Their work appears in journals such as Physical Review Materials, Physical Review Letters, Acta Materialia, MRS Bulletin and PubMed.
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.