John Parkhill
- Materials Chemistry top 5%
- Atomic and Molecular Physics, and Optics top 5%
- Electrical and Electronic Engineering top 10%
- Computational Theory and Mathematics top 2%
- Molecular Biology
- Co-authors
- Kun YaoJohn E. HerrMartin Head‐GordonSergei RouvimovSergiu DragutaMichael C. BrennanMasaru KunoJessica Zinna
- Topics
- Spectroscopy and Quantum Chemical Studies (14 papers)Advanced Chemical Physics Studies (13 papers)Machine Learning in Materials Science (8 papers)
- Journals
- Proceedings of the National Academy of SciencesJournal of the American Chemical SocietyThe Journal of Chemical Physics
- Partner nations
- United StatesPhilippinesGermany
In The Last Decade
John Parkhill
31 papers receiving 1.5k citations
Hit Papers
Peers
Comparison fields: 5 of 73
- Materials Chemistry 917
- Atomic and Molecular Physics, and Optics 612
- Electrical and Electronic Engineering 390
- Computational Theory and Mathematics 344
- Molecular Biology 222
Countries citing papers authored by John Parkhill
This map shows the geographic impact of John Parkhill'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 John Parkhill with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John Parkhill more than expected).
Fields of papers citing papers by John Parkhill
This network shows the impact of papers produced by John Parkhill. 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 John Parkhill. The network helps show where John Parkhill may publish in the future.
Co-authorship network of co-authors of John Parkhill
This figure shows the co-authorship network connecting the top 25 collaborators of John Parkhill. A scholar is included among the top collaborators of John Parkhill 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 John Parkhill. John Parkhill is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 7 | |
| 2 | Orbital optimisation in the perfect pairing hierarchy: applications to full-valence calculations on linear polyacenes | 22 |
| 3 | 52 | |
| 4 | 19 | |
| 5 | 102 | |
| 6 | 16 | |
| 7 | 287 | |
| 8 | 3 | |
| 9 | 33 | |
| 10 | 33 | |
| 11 | 19 | |
| 12 | 2 | |
| 13 | 21 | |
| 14 | 76 | |
| 15 | 8 | |
| 16 | 2 | |
| 17 | 16 | |
| 18 | 8 | |
| 19 | 4 | |
| 20 | 30 |
About John Parkhill
John Parkhill is a scholar working on Atomic and Molecular Physics, and Optics, Physical and Theoretical Chemistry and Computational Theory and Mathematics, having authored 31 papers that have together received 1.5k indexed citations. Recurring topics across this work include Spectroscopy and Quantum Chemical Studies (14 papers), Advanced Chemical Physics Studies (13 papers) and Machine Learning in Materials Science (8 papers). The work is most often cited by research in Computational Theory and Mathematics (344 citations), Physical and Theoretical Chemistry (181 citations) and Materials Chemistry (917 citations). John Parkhill has collaborated with scholars based in United States, Philippines and Germany. Frequent co-authors include Kun Yao, John E. Herr, Martin Head‐Gordon, Sergei Rouvimov, Sergiu Draguta, Michael C. Brennan, Masaru Kuno, Jessica Zinna, Keith V. Lawler and Seth N. Brown. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and The Journal of Chemical Physics.
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.