David Lonie
Impact in
- Organic Chemistry top 0.5%
- Synthesis and biological activity
- Free Radicals and Antioxidants
- Physical and Theoretical Chemistry top 0.5%
- Crystallography and molecular interactions
Papers in
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- Machine Learning in Materials Science 4
- Enzyme Structure and Function 1
- Hydrogen Storage and Materials 1
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- Computational Drug Discovery Methods 3
- Co-authors
- Eva Zurek (8 shared papers)Marcus D. Hanwell (1 shared paper)Geoffrey Hutchison (1 shared paper)Donald Curtis (1 shared paper)James Hooper (1 shared paper)Burlen Loring (2 shared papers)E. Wes Bethel (2 shared papers)Berk Geveci (2 shared papers)
- Journals
- Computer Physics Communications (4 papers)Journal of Cheminformatics (1 paper)Physical Review B (1 paper)Analytical Chemistry (1 paper)Journal of Chemical Education (1 paper)
- Partner nations
- United StatesIndiaTürkiye
In The Last Decade
David Lonie
12 papers receiving 8.7k citations
David Lonie's Hit Papers
Peers
Comparison fields: 5 of 169
- Organic Chemistry 2.1k
- Physical and Theoretical Chemistry 655
- Toxicology 188
- Materials Chemistry 2.2k
- Computational Theory and Mathematics 784
Countries citing papers authored by David Lonie
This map shows the geographic impact of David Lonie'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 David Lonie with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Lonie more than expected).
Fields of papers citing papers by David Lonie
This network shows the impact of papers produced by David Lonie. 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 David Lonie. The network helps show where David Lonie may publish in the future.
Co-authors
The 25 scholars most cited alongside David Lonie, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Avogadro: an advanced semantic chemical editor, visualization, and analysis platform Hit paper breakdown → | 2012 | 8121 |
| 2 | 2010 | 278 | |
| 3 | 2013 | 115 | |
| 4 | 2011 | 69 | |
| 5 | 2016 | 44 | |
| 6 | 2011 | 37 | |
| 7 | The SENSEI Generic In Situ Interface: | 2017 | 29 |
| 8 | 2015 | 25 | |
| 9 | 2013 | 20 | |
| 10 | 2017 | 11 | |
| 11 | 2013 | 7 | |
| 12 | 2014 | 2 |
About David Lonie
David Lonie is a scholar working on Materials Chemistry, Computational Theory and Mathematics, Computer Networks and Communications, Molecular Biology and Hardware and Architecture, having authored 12 papers that have together received 8.8k indexed citations. Recurring topics across this work include Machine Learning in Materials Science (4 papers), Computational Drug Discovery Methods (3 papers), Parallel Computing and Optimization Techniques (2 papers), Protein Structure and Dynamics (2 papers), Distributed and Parallel Computing Systems (2 papers), Distributed systems and fault tolerance (2 papers), Enzyme Structure and Function (1 paper) and Hydrogen Storage and Materials (1 paper). The work is most often cited by research in Organic Chemistry (2.1k citations), Physical and Theoretical Chemistry (655 citations), Toxicology (188 citations), Materials Chemistry (2.2k citations) and Computational Theory and Mathematics (784 citations). David Lonie has collaborated with scholars based in United States, India and Türkiye. Frequent co-authors include Eva Zurek, Marcus D. Hanwell, Geoffrey Hutchison, Donald Curtis, James Hooper, Burlen Loring, E. Wes Bethel, Berk Geveci, Matthew Wolf and Brad Whitlock. Their work appears in journals such as Computer Physics Communications, Journal of Cheminformatics, Physical Review B, Analytical Chemistry and Journal of Chemical Education.
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.