John L. Weber

444 total citations
13 papers, 271 citations indexed

About

John L. Weber is a scholar working on Materials Chemistry, Atomic and Molecular Physics, and Optics and Catalysis. According to data from OpenAlex, John L. Weber has authored 13 papers receiving a total of 271 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Materials Chemistry, 6 papers in Atomic and Molecular Physics, and Optics and 4 papers in Catalysis. Recurrent topics in John L. Weber's work include Advanced Chemical Physics Studies (6 papers), Machine Learning in Materials Science (4 papers) and Catalysis and Oxidation Reactions (4 papers). John L. Weber is often cited by papers focused on Advanced Chemical Physics Studies (6 papers), Machine Learning in Materials Science (4 papers) and Catalysis and Oxidation Reactions (4 papers). John L. Weber collaborates with scholars based in United States and Germany. John L. Weber's co-authors include David R. Reichman, James Shee, Richard A. Friesner, Aleksandra Olow, Rob Oslund, Olugbeminiyi Fadeyi, Shiwei Zhang, Nicholas E. S. Tay, Tomislav Rovis and Keun Ah Ryu and has published in prestigious journals such as Journal of the American Chemical Society, The Journal of Chemical Physics and Nature Chemistry.

In The Last Decade

John L. Weber

11 papers receiving 271 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
John L. Weber United States 9 134 82 78 56 35 13 271
Mark R. Pollard United Kingdom 10 49 0.4× 48 0.6× 163 2.1× 48 0.9× 156 4.5× 15 454
Masahiro Sakurai Japan 13 231 1.7× 32 0.4× 63 0.8× 35 0.6× 131 3.7× 38 376
Andreas Eich Germany 12 252 1.9× 41 0.5× 168 2.2× 56 1.0× 32 0.9× 20 445
Yoichi Sakamoto Japan 10 129 1.0× 122 1.5× 88 1.1× 157 2.8× 54 1.5× 15 390
Daniel J. Aschaffenburg United States 9 137 1.0× 21 0.3× 130 1.7× 167 3.0× 33 0.9× 11 370
Yusuke Kanematsu Japan 11 89 0.7× 38 0.5× 55 0.7× 50 0.9× 87 2.5× 37 264
Danil Kaliakin United States 11 79 0.6× 44 0.5× 128 1.6× 48 0.9× 39 1.1× 18 316
Maximilian Kubillus Germany 6 171 1.3× 38 0.5× 162 2.1× 77 1.4× 116 3.3× 6 420
Inmaculada C. Pintre Spain 13 231 1.7× 236 2.9× 43 0.6× 17 0.3× 67 1.9× 18 499
Shingo Ito Japan 9 129 1.0× 49 0.6× 94 1.2× 10 0.2× 133 3.8× 19 290

Countries citing papers authored by John L. Weber

Since Specialization
Citations

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

Fields of papers citing papers by John L. Weber

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of John L. Weber

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

All Works

13 of 13 papers shown
1.
Wei, Yujing, John L. Weber, Zachary K. Goldsmith, et al.. (2026). An Accurate Charge-Aware Machine-Learning Interatomic Potential for the Reduction of Li-Ion Battery Electrolytes in Solution. Journal of Chemical Theory and Computation. 22(5). 2515–2528.
2.
3.
Shee, James, John L. Weber, David R. Reichman, Richard A. Friesner, & Shiwei Zhang. (2023). On the potentially transformative role of auxiliary-field quantum Monte Carlo in quantum chemistry: A highly accurate method for transition metals and beyond. The Journal of Chemical Physics. 158(14). 140901–140901. 16 indexed citations
4.
Jacobson, Leif D., et al.. (2023). Accurate Quantum Chemical Reaction Energies for Lithium-Mediated Electrolyte Decomposition and Evaluation of Density Functional Approximations. The Journal of Physical Chemistry A. 127(44). 9178–9184. 9 indexed citations
5.
Neugebauer, Hagen, et al.. (2023). Toward Benchmark-Quality Ab Initio Predictions for 3d Transition Metal Electrocatalysts: A Comparison of CCSD(T) and ph-AFQMC. Journal of Chemical Theory and Computation. 19(18). 6208–6225. 21 indexed citations
6.
Weber, John L., et al.. (2023). Expanding the Design Space of Constraints in Auxiliary-Field Quantum Monte Carlo. Journal of Chemical Theory and Computation. 19(21). 7567–7576. 4 indexed citations
7.
Rudshteyn, Benjamin, John L. Weber, Shiwei Zhang, et al.. (2022). Calculation of Metallocene Ionization Potentials via Auxiliary Field Quantum Monte Carlo: Toward Benchmark Quantum Chemistry for Transition Metals. Journal of Chemical Theory and Computation. 18(5). 2845–2862. 22 indexed citations
8.
Weber, John L., et al.. (2022). A Localized-Orbital Energy Evaluation for Auxiliary-Field Quantum Monte Carlo. Journal of Chemical Theory and Computation. 18(6). 3447–3459. 10 indexed citations
9.
Tay, Nicholas E. S., Keun Ah Ryu, John L. Weber, et al.. (2022). Targeted activation in localized protein environments via deep red photoredox catalysis. Nature Chemistry. 15(1). 101–109. 91 indexed citations
10.
Weber, John L., Emily M. Churchill, Steffen Jockusch, et al.. (2020). In silico prediction of annihilators for triplet–triplet annihilation upconversion via auxiliary-field quantum Monte Carlo. Chemical Science. 12(3). 1068–1079. 12 indexed citations
11.
Fallon, Kealan J., Emily M. Churchill, Samuel N. Sanders, et al.. (2020). Molecular Engineering of Chromophores to Enable Triplet–Triplet Annihilation Upconversion. Journal of the American Chemical Society. 142(47). 19917–19925. 62 indexed citations
12.
13.
Rudshteyn, Benjamin, John L. Weber, Evan J. Arthur, et al.. (2020). Predicting Ligand-Dissociation Energies of 3d Coordination Complexes with Auxiliary-Field Quantum Monte Carlo. Journal of Chemical Theory and Computation. 16(5). 3041–3054. 21 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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