Hagen Eckert

728 citations
21 papers · 294 · h-index 8

Impact in

Papers in

    • Machine Learning in Materials Science 4
    • X-ray Diffraction in Crystallography 3
    • Boron and Carbon Nanomaterials Research 2
    • Advanced Materials Characterization Techniques 2

Hagen Eckert

20 papers receiving 290 citations

Peers

Hagen Eckert
Comparison fields: 5 of 72
  • Renewable Energy, Sustainability and the Environment 94
  • Pollution 43
  • Materials Chemistry 145
  • Ceramics and Composites 16
  • Water Science and Technology 31
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Qianyu Wang China
Andjelika Bjelajac Serbia
Han Feng Singapore
Xiaojie Feng China
Achraf Amir Assadi Tunisia
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Citations per year

Countries citing papers authored by Hagen Eckert

Since Specialization
Citations

This map shows the geographic impact of Hagen Eckert'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 Hagen Eckert with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hagen Eckert more than expected).

Fields of papers citing papers by Hagen Eckert

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hagen Eckert. 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 Hagen Eckert. The network helps show where Hagen Eckert may publish in the future.

Co-authors

The 25 scholars most cited alongside Hagen Eckert, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Hagen Eckert Line = papers co-authored together Hagen Eckert links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201590
2 202243
3 202227
4 201427
5 201716
6 201615
7 202211
8 201310
9 20237
10 20247
11 20247
12 20237
13 20226
14 20236
15 20205
16 20204
17 20253
18 20151
19 20201
20 20191

About Hagen Eckert

Hagen Eckert is a scholar working on Materials Chemistry, Biomedical Engineering, Molecular Biology, Biomaterials and Paleontology, having authored 21 papers that have together received 294 indexed citations. Recurring topics across this work include Machine Learning in Materials Science (4 papers), X-ray Diffraction in Crystallography (3 papers), Metal and Thin Film Mechanics (2 papers), Advanced Photocatalysis Techniques (2 papers), Paleontology and Stratigraphy of Fossils (2 papers), Advanced Materials Characterization Techniques (2 papers), Diatoms and Algae Research (2 papers) and Boron and Carbon Nanomaterials Research (2 papers). The work is most often cited by research in Renewable Energy, Sustainability and the Environment (94 citations), Pollution (43 citations), Materials Chemistry (145 citations), Ceramics and Composites (16 citations) and Water Science and Technology (31 citations). Hagen Eckert has collaborated with scholars based in Germany, United States and Austria. Frequent co-authors include Gianaurelio Cuniberti, Sara Teixeira, Klaus Kühn, Robert Gurke, Joachim Fauler, Stefano Curtarolo, Simon Divilov, Xiomara Campilongo, M. Bobeth and Marco Esters. Their work appears in journals such as Computational Materials Science, Acta Materialia, Tissue Engineering Part C Methods, Journal of environmental chemical engineering and Journal of Tissue Engineering and Regenerative Medicine.

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.

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