Tu C. Le

82 papers receiving 3.8k citations

Tu C. Le's Hit Papers

Machine Learning for Electrocatalyst and Photocatalyst Design and Discovery 2022 · 391 citations
3910+1+3Years since publication100200300

Peers

Tu C. Le
Comparison fields: 5 of 166
  • Nephrology 633
  • Catalysis 199
  • Materials Chemistry 1.3k
  • Computational Theory and Mathematics 404
  • Renewable Energy, Sustainability and the Environment 359
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Junbo Gong China
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Tu C. Le relative to Junbo Gong China Junbo Gong's profile →
Citations per field
00.5×7.6×
Junbo Gong · 1×
Citations per year

Countries citing papers authored by Tu C. Le

Since Specialization
Citations

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

Fields of papers citing papers by Tu C. Le

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tu C. Le. 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 Tu C. Le. The network helps show where Tu C. Le may publish in the future.

Co-authors

The 25 scholars most cited alongside Tu C. Le, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Tu C. Le Line = papers co-authored together Tu C. Le links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 84 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012428
2
Machine Learning for Electrocatalyst and Photocatalyst Design and Discovery
Hit paper breakdown →
2022391
3 2011292
4
Systematic Comparison of the Structural and Dynamic Properties of Commonly Used Water Models for Molecular Dynamics Simulations
Hit paper breakdown →
2021213
5 2003196
6 2002179
7 2016156
8 2002144
9 2001132
10 2005121
11 2004116
12 201696
13 201977
14 201663
15 201262
16 201861
17 202158
18 201955
19 201354
20 202152

About Tu C. Le

Tu C. Le is a scholar working on Materials Chemistry, Molecular Biology, Organic Chemistry, Biomedical Engineering and Electrical and Electronic Engineering, having authored 84 papers that have together received 3.9k indexed citations. Recurring topics across this work include Machine Learning in Materials Science (13 papers), Lipid Membrane Structure and Behavior (9 papers), Computational Drug Discovery Methods (7 papers), Renal Diseases and Glomerulopathies (7 papers), Microbial Natural Products and Biosynthesis (7 papers), Advanced Photocatalysis Techniques (6 papers), Ionic liquids properties and applications (6 papers) and Surfactants and Colloidal Systems (5 papers). The work is most often cited by research in Nephrology (633 citations), Catalysis (199 citations), Materials Chemistry (1.3k citations), Computational Theory and Mathematics (404 citations) and Renewable Energy, Sustainability and the Environment (359 citations). Tu C. Le has collaborated with scholars based in Australia, United States and United Kingdom. Frequent co-authors include David A. Winkler, Calum J. Drummond, Frank R. Burden, V. Chandana Epa, Celesta Fong, Dehong Chen, Haoxin Mai, Rachel A. Caruso, Martin R. Pollak and Raghu Kalluri. Their work appears in journals such as Journal of Clinical Investigation, The Journal of Chemical Physics, Journal of Chemical Information and Modeling, Crystal Growth & Design and Marine Drugs.

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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