Michael Seaton

676 citations
27 papers · 538 · h-index 9

Impact in

Papers in

Michael Seaton

24 papers receiving 528 citations

Peers

Michael Seaton
Comparison fields: 5 of 79
  • Computational Mechanics 144
  • Materials Chemistry 294
  • Physical and Theoretical Chemistry 46
  • Organic Chemistry 125
  • Information Systems and Management 29
Replace Maximilian Kohns with:
Maximilian Kohns Germany
Hiroshi Akiba Japan
Annalisa Cardellini Italy
Valmor F. de Almeida United States
Nicodemo Di Pasquale United Kingdom
Peter Klein Germany
J.P. Pérez France
Michael J. Nayhouse United States
Ganesh Sivaraman United States
Michael Seaton relative to Maximilian Kohns Germany Maximilian Kohns's profile →
Citations per field
00.5×2×4×6×7.5×
Maximilian Kohns · 1×
Citations per year

Countries citing papers authored by Michael Seaton

Since Specialization
Citations

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

Fields of papers citing papers by Michael Seaton

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2013134
2 201898
3 201386
4 201454
5 201546
6 201929
7 202021
8 201810
9 20209
10 20218
11 20185
12 20214
13 20214
14 20114
15
Virtual channel concept for measuring solids mass flow rate
20034
16 20203
17 20213
18 20213
19 20212
20 20032

About Michael Seaton

Michael Seaton is a scholar working on Computational Mechanics, Information Systems and Management, Materials Chemistry, Industrial and Manufacturing Engineering and Condensed Matter Physics, having authored 27 papers that have together received 538 indexed citations. Recurring topics across this work include Lattice Boltzmann Simulation Studies (6 papers), Nuclear Materials and Properties (3 papers), Semantic Web and Ontologies (3 papers), Scientific Computing and Data Management (3 papers), Machine Learning in Materials Science (3 papers), Aerosol Filtration and Electrostatic Precipitation (3 papers), Block Copolymer Self-Assembly (2 papers) and Injection Molding Process and Properties (2 papers). The work is most often cited by research in Computational Mechanics (144 citations), Materials Chemistry (294 citations), Physical and Theoretical Chemistry (46 citations), Organic Chemistry (125 citations) and Information Systems and Management (29 citations). Michael Seaton has collaborated with scholars based in United Kingdom, Germany and Finland. Frequent co-authors include R. L. Anderson, William R. Smith, Sebastian Metz, Ilian Todorov, Dorothy M. Duffy, Eva Zarkadoula, Kostya Trachenko, K. Nordlund, Szymon L. Daraszewicz and Martin T. Dove. Their work appears in journals such as Journal of Physics Condensed Matter, Molecular Simulation, Journal of Physics A Mathematical and Theoretical, Soft Matter and Physics of Fluids.

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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