Henrik Schopmans

772 citations
7 papers · 455 indexed · 1 hit paper · h-index 4
Topics
Machine Learning in Materials Science (2 papers)Supramolecular Self-Assembly in Materials (2 papers)Synthesis and Properties of Aromatic Compounds (2 papers)
Partner nations
GermanyArgentinaColombia

In The Last Decade

Henrik Schopmans

7 papers receiving 444 citations

Hit Papers

Graph neural networks for materials science and chemistry20222026202320242022100200300400

Peers

Henrik Schopmans
Comparison fields: 5 of 81
  • Materials Chemistry 300
  • Computational Theory and Mathematics 144
  • Electrical and Electronic Engineering 75
  • Molecular Biology 68
  • Artificial Intelligence 61
Replace Timo Sommer with:
Timo Sommer Ireland
Clint van Hoesel Netherlands
Marlen Neubert Germany
Luca Torresi Germany
Patrick Reiser Germany
Cher Tian Ser Canada
Steph-Yves Louis United States
Adam C. Mater Australia
Callum J. Court United Kingdom
Henrik Schopmans relative to Timo Sommer Ireland Timo Sommer's profile →
Citations per field
00.5×1.5×
Timo Sommer · 1×
Citations per year

Countries citing papers authored by Henrik Schopmans

Since Specialization
Citations

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

Fields of papers citing papers by Henrik Schopmans

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Henrik Schopmans

This figure shows the co-authorship network connecting the top 25 collaborators of Henrik Schopmans. A scholar is included among the top collaborators of Henrik Schopmans based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Henrik Schopmans. Henrik Schopmans is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

7 of 7 papers shown
#WorkIndexed citations
1 2
2 2
3 4
4
Graph neural networks for materials science and chemistrybreakdown →
407
5 9
6 3
7 28

About Henrik Schopmans

Henrik Schopmans is a scholar working on Biomaterials, Surfaces, Coatings and Films and Physical and Theoretical Chemistry, having authored 7 papers that have together received 455 indexed citations. Recurring topics across this work include Machine Learning in Materials Science (2 papers), Supramolecular Self-Assembly in Materials (2 papers) and Synthesis and Properties of Aromatic Compounds (2 papers). The work is most often cited by research in Computational Theory and Mathematics (144 citations), Materials Chemistry (300 citations) and Metals and Alloys (6 citations). Henrik Schopmans has collaborated with scholars based in Germany, Argentina and Colombia. Frequent co-authors include Pascal Friederich, Patrick Reiser, Luca Torresi, Clint van Hoesel, Chen Shao, Timo Sommer, Marlen Neubert, Chen Zhou, Mariana Kozłowska and Wolfgang Wenzel. Their work appears in journals such as Angewandte Chemie International Edition, International Journal of Biological Macromolecules and Advanced Engineering Materials.

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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