Ian M. Pendleton
Impact in
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- Machine Learning in Materials Science
Papers in
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- Machine Learning in Materials Science 4
- Boron and Carbon Nanomaterials Research 1
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- Advanced Chemical Physics Studies 2
- Co-authors
- Paul M. Zimmerman (2 shared papers)Alexander J. Norquist (4 shared papers)Joshua Schrier (5 shared papers)Emory M. Chan (3 shared papers)Melanie Sarah Sanford (1 shared paper)Mónica H. Pérez‐Temprano (1 shared paper)Mansoor Ani Najeeb (3 shared papers)Wesley Wang (1 shared paper)
- Journals
- Journal of the American Chemical Society (2 papers)Chemistry of Materials (1 paper)The Journal of Physical Chemistry B (1 paper)The Journal of Physical Chemistry A (1 paper)MRS Communications (1 paper)
- Partner nations
- United States
In The Last Decade
Ian M. Pendleton
8 papers receiving 350 citations
Peers
Comparison fields: 5 of 39
- Materials Chemistry 186
- Drug Discovery 1
- Organic Chemistry 80
- Physical and Theoretical Chemistry 22
- Information Systems and Management 18
Countries citing papers authored by Ian M. Pendleton
This map shows the geographic impact of Ian M. Pendleton'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 Ian M. Pendleton with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ian M. Pendleton more than expected).
Fields of papers citing papers by Ian M. Pendleton
This network shows the impact of papers produced by Ian M. Pendleton. 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 Ian M. Pendleton. The network helps show where Ian M. Pendleton may publish in the future.
Co-authors
The 20 scholars most cited alongside Ian M. Pendleton, 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 | 2020 | 160 | |
| 2 | 2016 | 82 | |
| 3 | 2019 | 63 | |
| 4 | 2020 | 24 | |
| 5 | 2016 | 15 | |
| 6 | 2020 | 9 | |
| 7 | Computational Chemistry Studies of Organometallic Energy Landscapes | 2018 | 1 |
| 8 | 2021 | 1 |
About Ian M. Pendleton
Ian M. Pendleton is a scholar working on Materials Chemistry, Atomic and Molecular Physics, and Optics, Organic Chemistry, Inorganic Chemistry and Electronic, Optical and Magnetic Materials, having authored 8 papers that have together received 355 indexed citations. Recurring topics across this work include Machine Learning in Materials Science (4 papers), Advanced Chemical Physics Studies (2 papers), Organometallic Complex Synthesis and Catalysis (2 papers), Catalytic Cross-Coupling Reactions (1 paper), Crystal Structures and Properties (1 paper), Protein Structure and Dynamics (1 paper), Chemical Reaction Mechanisms (1 paper) and Boron and Carbon Nanomaterials Research (1 paper). The work is most often cited by research in Materials Chemistry (186 citations), Drug Discovery (1 citation), Organic Chemistry (80 citations), Physical and Theoretical Chemistry (22 citations) and Information Systems and Management (18 citations). Ian M. Pendleton has collaborated with scholars based in United States. Frequent co-authors include Paul M. Zimmerman, Alexander J. Norquist, Joshua Schrier, Emory M. Chan, Melanie Sarah Sanford, Mónica H. Pérez‐Temprano, Mansoor Ani Najeeb, Wesley Wang, Zhi Li and Matthias Zeller. Their work appears in journals such as Journal of the American Chemical Society, Chemistry of Materials, The Journal of Physical Chemistry B, The Journal of Physical Chemistry A and MRS Communications.
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.