Patrick Reiser

1.6k citations
24 papers · 864 · 1 hit paper · h-index 12

Impact in

Papers in

Patrick Reiser

24 papers receiving 852 citations

Patrick Reiser's Hit Papers

Graph neural networks for materials science and chemistry 2022 · 472 citations
4720+1+2Years since publication100200300400

Peers

Patrick Reiser
Comparison fields: 5 of 99
  • Computational Theory and Mathematics 187
  • Materials Chemistry 459
  • Polymers and Plastics 100
  • Electrical and Electronic Engineering 267
  • Physical and Theoretical Chemistry 32
Replace Zhonglin Cao with:
Zhonglin Cao United States
Deepak Kamal United States
Peter Bjørn Jørgensen Denmark
Ganesh Sivaraman United States
Xun Jiang China
Youn-Suk Choi South Korea
Anna M. Hiszpanski United States
Zekun Ren Singapore
G. Lambard Japan
Nathan J. Szymanski United States
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Citations per field
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Citations per year

Countries citing papers authored by Patrick Reiser

Since Specialization
Citations

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

Fields of papers citing papers by Patrick Reiser

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Patrick Reiser, 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 Patrick Reiser Line = papers co-authored together Patrick Reiser links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Graph neural networks for materials science and chemistry
Hit paper breakdown →
2022472
2 202168
3 201941
4 201735
5 201930
6 201828
7 201628
8 202426
9 202326
10 202319
11 202116
12 202312
13 202310
14 202010
15 20229
16 20247
17 20235
18 20235
19 20234
20 20234

About Patrick Reiser

Patrick Reiser is a scholar working on Materials Chemistry, Electrical and Electronic Engineering, Computational Theory and Mathematics, Polymers and Plastics and Molecular Biology, having authored 24 papers that have together received 864 indexed citations. Recurring topics across this work include Machine Learning in Materials Science (12 papers), Organic Electronics and Photovoltaics (9 papers), Computational Drug Discovery Methods (5 papers), Conducting polymers and applications (4 papers), Advanced Graph Neural Networks (3 papers), Molecular Junctions and Nanostructures (3 papers), Organic Light-Emitting Diodes Research (2 papers) and Protein Structure and Dynamics (2 papers). The work is most often cited by research in Computational Theory and Mathematics (187 citations), Materials Chemistry (459 citations), Polymers and Plastics (100 citations), Electrical and Electronic Engineering (267 citations) and Physical and Theoretical Chemistry (32 citations). Patrick Reiser has collaborated with scholars based in Germany, United Kingdom and United States. Frequent co-authors include Pascal Friederich, Henrik Schopmans, Luca Torresi, Chen Shao, Houssam Metni, Clint van Hoesel, Timo Sommer, Chen Zhou, Marlen Neubert and Eric Mankel. Their work appears in journals such as Advanced Engineering Materials, Chemical Science, Advanced Materials Interfaces, Advanced Materials and Sustainable Energy & Fuels.

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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