Ian M. Pendleton
Impact in
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- Scientific Computing and Data Management
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- Machine Learning in Materials Science
- Quantum Dots Synthesis And Properties
Papers in
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- Machine Learning in Materials Science 4
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- Nanomaterials for catalytic reactions 1
- Co-authors
- Paul M. Zimmerman (2 shared papers)Alexander J. Norquist (4 shared papers)Joshua Schrier (5 shared papers)Melanie S. Sanford (1 shared paper)Emory M. Chan (3 shared papers)Mónica H. Pérez‐Temprano (1 shared paper)Mansoor Ani Najeeb (2 shared papers)Matthias Zeller (1 shared paper)
- Journals
- Journal of the American Chemical Society (2 papers)The Journal of Physical Chemistry C (1 paper)Chemistry of Materials (1 paper)MRS Communications (1 paper)The Journal of Physical Chemistry B (1 paper)
- Partner nations
- United States
In The Last Decade
Ian M. Pendleton
8 papers receiving 319 citations
Peers
Comparison fields: 5 of 48
- Information Systems and Management 29
- Materials Chemistry 192
- Inorganic Chemistry 37
- Organic Chemistry 68
- Computational Theory and Mathematics 32
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 | 135 | |
| 2 | 2016 | 75 | |
| 3 | 2019 | 56 | |
| 4 | 2020 | 26 | |
| 5 | 2016 | 15 | |
| 6 | 2020 | 11 | |
| 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, Organic Chemistry, Molecular Biology, Electrical and Electronic Engineering and Inorganic Chemistry, having authored 8 papers that have together received 320 indexed citations. Recurring topics across this work include Machine Learning in Materials Science (4 papers), Perovskite Materials and Applications (2 papers), Asymmetric Hydrogenation and Catalysis (2 papers), Machine Learning in Bioinformatics (1 paper), Chemical Reactions and Isotopes (1 paper), Various Chemistry Research Topics (1 paper), RNA and protein synthesis mechanisms (1 paper) and Nanomaterials for catalytic reactions (1 paper). The work is most often cited by research in Information Systems and Management (29 citations), Materials Chemistry (192 citations), Inorganic Chemistry (37 citations), Organic Chemistry (68 citations) and Computational Theory and Mathematics (32 citations). Ian M. Pendleton has collaborated with scholars based in United States. Frequent co-authors include Paul M. Zimmerman, Alexander J. Norquist, Joshua Schrier, Melanie S. Sanford, Emory M. Chan, Mónica H. Pérez‐Temprano, Mansoor Ani Najeeb, Matthias Zeller, Zhi Li and Wesley Wang. Their work appears in journals such as Journal of the American Chemical Society, The Journal of Physical Chemistry C, Chemistry of Materials, MRS Communications and The Journal of Physical Chemistry B.
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.