Matthew S. Johnson
- Materials Chemistry
- Fluid Flow and Transfer Processes top 5%
- Catalysis top 10%
- Computational Mechanics top 10%
- Atomic and Molecular Physics, and Optics
- Co-authors
- William H. GreenRichard H. WestAlon Grinberg DanaMengjie LiuA. Mark PayneC. Franklin GoldsmithEmily MazeauColin A. Grambow
- Topics
- Machine Learning in Materials Science (9 papers)Advanced Combustion Engine Technologies (5 papers)Computational Drug Discovery Methods (4 papers)
- Partner nations
- United StatesIsraelMexico
In The Last Decade
Matthew S. Johnson
17 papers receiving 476 citations
Hit Papers
Peers
Comparison fields: 5 of 59
- Materials Chemistry 219
- Fluid Flow and Transfer Processes 145
- Catalysis 99
- Computational Mechanics 97
- Atomic and Molecular Physics, and Optics 79
Countries citing papers authored by Matthew S. Johnson
This map shows the geographic impact of Matthew S. Johnson'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 Matthew S. Johnson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthew S. Johnson more than expected).
Fields of papers citing papers by Matthew S. Johnson
This network shows the impact of papers produced by Matthew S. Johnson. 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 Matthew S. Johnson. The network helps show where Matthew S. Johnson may publish in the future.
Co-authorship network of co-authors of Matthew S. Johnson
This figure shows the co-authorship network connecting the top 25 collaborators of Matthew S. Johnson. A scholar is included among the top collaborators of Matthew S. Johnson 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 Matthew S. Johnson. Matthew S. Johnson is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 12 | |
| 5 | 6 | |
| 6 | 5 | |
| 7 | 3 | |
| 8 | 3 | |
| 9 | 9 | |
| 10 | 7 | |
| 11 | 5 | |
| 12 | 88 | |
| 13 | 5 | |
| 14 | 5 | |
| 15 | Reaction Mechanism Generator v3.0: Advances in Automatic Mechanism Generationbreakdown → | 197 |
| 16 | 28 | |
| 17 | 1 | |
| 18 | 73 | |
| 19 | 35 |
About Matthew S. Johnson
Matthew S. Johnson is a scholar working on Fluid Flow and Transfer Processes, Catalysis and Computational Theory and Mathematics, having authored 19 papers that have together received 483 indexed citations. Recurring topics across this work include Machine Learning in Materials Science (9 papers), Advanced Combustion Engine Technologies (5 papers) and Computational Drug Discovery Methods (4 papers). The work is most often cited by research in Fluid Flow and Transfer Processes (145 citations), Catalysis (99 citations) and Materials Chemistry (219 citations). Matthew S. Johnson has collaborated with scholars based in United States, Israel and Mexico. Frequent co-authors include William H. Green, Richard H. West, Alon Grinberg Dana, Mengjie Liu, A. Mark Payne, C. Franklin Goldsmith, Emily Mazeau, Colin A. Grambow, Nathan W. Yee and Katrín Blöndal. Their work appears in journals such as The Journal of Physical Chemistry C, The Journal of Physical Chemistry A and Combustion and Flame.
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.