John A. Keith

7.0k total citations · 3 hit papers
96 papers, 5.8k citations indexed

About

John A. Keith is a scholar working on Materials Chemistry, Renewable Energy, Sustainability and the Environment and Atomic and Molecular Physics, and Optics. According to data from OpenAlex, John A. Keith has authored 96 papers receiving a total of 5.8k indexed citations (citations by other indexed papers that have themselves been cited), including 45 papers in Materials Chemistry, 41 papers in Renewable Energy, Sustainability and the Environment and 20 papers in Atomic and Molecular Physics, and Optics. Recurrent topics in John A. Keith's work include Electrocatalysts for Energy Conversion (25 papers), CO2 Reduction Techniques and Catalysts (22 papers) and Machine Learning in Materials Science (19 papers). John A. Keith is often cited by papers focused on Electrocatalysts for Energy Conversion (25 papers), CO2 Reduction Techniques and Catalysts (22 papers) and Machine Learning in Materials Science (19 papers). John A. Keith collaborates with scholars based in United States, Germany and Italy. John A. Keith's co-authors include Emily A. Carter, Timo Jacob, Peilin Liao, Patrick M. Henry, Michele Pavone, Ana B. Muñoz‐García, Andrew M. Ritzmann, Kyle A. Grice, Yasemin Basdogan and Alexandre Tkatchenko and has published in prestigious journals such as Science, Chemical Reviews and Journal of the American Chemical Society.

In The Last Decade

John A. Keith

93 papers receiving 5.7k citations

Hit Papers

Combining Machine Learnin... 2012 2026 2016 2021 2021 2012 2020 100 200 300 400 500

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
John A. Keith 2.6k 2.3k 1.3k 1.2k 962 96 5.8k
Zheng‐Wang Qu 3.2k 1.2× 1.9k 0.9× 2.2k 1.7× 2.1k 1.7× 375 0.4× 169 6.7k
Stephan N. Steinmann 1.8k 0.7× 2.3k 1.0× 735 0.5× 1.2k 1.0× 638 0.7× 125 4.7k
Robert J. Nielsen 1.5k 0.6× 1.2k 0.5× 1.8k 1.3× 777 0.6× 653 0.7× 69 4.3k
Charles B. Musgrave 1.2k 0.4× 3.4k 1.5× 1.9k 1.4× 2.7k 2.2× 1.0k 1.1× 144 7.2k
Biswarup Pathak 2.0k 0.8× 4.5k 2.0× 886 0.7× 2.6k 2.1× 737 0.8× 327 7.4k
Wenzhen Lai 2.6k 1.0× 1.8k 0.8× 833 0.6× 1.5k 1.2× 434 0.5× 80 5.2k
Huan Yan 4.1k 1.6× 4.3k 1.9× 1.3k 0.9× 1.8k 1.5× 1.4k 1.5× 79 6.9k
Takeshi Kobayashi 837 0.3× 2.6k 1.1× 580 0.4× 914 0.7× 698 0.7× 163 4.8k
Zhuofeng Ke 2.0k 0.8× 1.6k 0.7× 3.9k 2.9× 1.3k 1.0× 384 0.4× 217 7.6k
Andreas Heyden 1.5k 0.6× 4.2k 1.8× 908 0.7× 573 0.5× 1.9k 1.9× 130 7.3k

Countries citing papers authored by John A. Keith

Since Specialization
Citations

This map shows the geographic impact of John A. Keith'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 A. Keith with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John A. Keith more than expected).

Fields of papers citing papers by John A. Keith

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John A. Keith. 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 A. Keith. The network helps show where John A. Keith may publish in the future.

Co-authorship network of co-authors of John A. Keith

This figure shows the co-authorship network connecting the top 25 collaborators of John A. Keith. A scholar is included among the top collaborators of John A. Keith 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 A. Keith. John A. Keith is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Zhao, Lingyan, et al.. (2025). Electrochemical Corrosion and Catalysis Dynamics of Tin Oxide during Water Oxidation. ACS Catalysis. 15(21). 18601–18611. 1 indexed citations
2.
Petersson, George A., et al.. (2025). Zero-point energies from bond orders and populations relationships. The Journal of Chemical Physics. 162(8).
3.
Keith, John A., et al.. (2025). A focus on delocalization error poisoning the density-functional many-body expansion. Chemical Science. 16(11). 4566–4567. 2 indexed citations
4.
Zhao, Lingyan, et al.. (2024). Interplay between Catalyst Corrosion and Homogeneous Reactive Oxygen Species in Electrochemical Ozone Production. ACS Catalysis. 14(9). 6868–6880. 4 indexed citations
5.
Poltavsky, Igor, et al.. (2023). Modeling molecular ensembles with gradient-domain machine learning force fields. Digital Discovery. 2(3). 871–880. 13 indexed citations
6.
Rudorff, Guido Falk von, et al.. (2022). Evaluating quantum alchemy of atoms with thermodynamic cycles: Beyond ground electronic states. The Journal of Chemical Physics. 156(6). 64106–64106. 8 indexed citations
7.
Rudorff, Guido Falk von, et al.. (2022). Quantum alchemy beyond singlets: Bonding in diatomic molecules with hydrogen. The Journal of Chemical Physics. 156(20). 204111–204111. 6 indexed citations
8.
Westmoreland, Phillip R., et al.. (2022). A Bond-Energy/Bond-Order and Populations Relationship. Journal of Chemical Theory and Computation. 18(8). 4774–4794. 12 indexed citations
9.
Anderson, Rachel M., et al.. (2020). Combined Neural Network Potential and Density Functional Theory Study of TiAl2O5Surface Morphology and Oxygen Reduction Reaction Overpotentials. The Journal of Physical Chemistry C. 124(28). 15171–15179. 14 indexed citations
10.
Bullock, R. Morris, Jingguang G. Chen, Laura Gagliardi, et al.. (2020). Using nature’s blueprint to expand catalysis with Earth-abundant metals. Science. 369(6505). 432 indexed citations breakdown →
11.
Basdogan, Yasemin, et al.. (2020). First-principles modeling of chemistry in mixed solvents: Where to go from here?. The Journal of Chemical Physics. 152(13). 130902–130902. 19 indexed citations
12.
Zhao, Lingyan, et al.. (2020). Machine learning corrected alchemical perturbation density functional theory for catalysis applications. AIChE Journal. 66(12). 15 indexed citations
13.
Basdogan, Yasemin, et al.. (2019). Advances and challenges in modeling solvated reaction mechanisms for renewable fuels and chemicals. Wiley Interdisciplinary Reviews Computational Molecular Science. 10(2). 49 indexed citations
14.
15.
Geib, Steven J., Qiang Zhu, Hari B. Sunkara, et al.. (2018). Oligomer Hydrate Crystallization Improves Carbon Nanotube Memory. Chemistry of Materials. 30(11). 3813–3818. 6 indexed citations
16.
Ilić, Stefan, et al.. (2018). Thermodynamic Hydricities of Biomimetic Organic Hydride Donors. Journal of the American Chemical Society. 140(13). 4569–4579. 79 indexed citations
17.
Keith, John A., et al.. (2018). Benchmarking Computational Alchemy for Carbide, Nitride, and Oxide Catalysts. Advanced Theory and Simulations. 2(4). 16 indexed citations
18.
Gao, Wang, John A. Keith, J. Anton, & Timo Jacob. (2010). Oxidation of formic acid on the Pt(111) surface in the gas phase. Dalton Transactions. 39(36). 8450–8450. 57 indexed citations
19.
Keith, John A. & Timo Jacob. (2010). Theoretical Studies of Potential‐Dependent and Competing Mechanisms of the Electrocatalytic Oxygen Reduction Reaction on Pt(111). Angewandte Chemie International Edition. 49(49). 9521–9525. 214 indexed citations
20.
Keith, John A. & Patrick M. Henry. (2009). The Mechanism of the Wacker Reaction: A Tale of Two Hydroxypalladations. Angewandte Chemie International Edition. 48(48). 9038–9049. 260 indexed citations

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.

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