Long V. Le

506 citations
34 papers · 408 · h-index 9

Impact in

Papers in

Long V. Le

25 papers receiving 400 citations

Peers

Long V. Le
Comparison fields: 5 of 51
  • Pharmaceutical Science 123
  • Drug Discovery 2
  • Molecular Medicine 35
  • Biomaterials 31
  • Bioengineering 5
Replace Minhui Lu with:
Minhui Lu China
Baomei Zhang China
Razina Z. Seeni Singapore
Hye Eun Choi South Korea
Ying‐Pei Hsu Taiwan
Ian A. P. Thompson United States
Hariharasudhan D. Chirra United States
Dinh‐Tuan Phan Singapore
Xiewen Liu United Kingdom
Robbie J. Walczak United States
Long V. Le relative to Minhui Lu China Minhui Lu's profile →
Citations per field
00.5×5×10×14×
Minhui Lu · 1×
Citations per year

Countries citing papers authored by Long V. Le

Since Specialization
Citations

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

Fields of papers citing papers by Long V. Le

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Long V. 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 Long V. Le Line = papers co-authored together Long V. Le links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201599
2 201394
3 201873
4 201918
5 202217
6 202314
7 202311
8 202010
9 202110
10 20208
11 20248
12 20176
13 20256
14 20215
15 20225
16 20234
17 20193
18 20223
19 20223
20 20243

About Long V. Le

Long V. Le is a scholar working on Materials Chemistry, Analytical Chemistry, Renewable Energy, Sustainability and the Environment, Electronic, Optical and Magnetic Materials and Applied Mathematics, having authored 34 papers that have together received 408 indexed citations. Recurring topics across this work include 2D Materials and Applications (10 papers), Spectroscopy and Chemometric Analyses (6 papers), Chalcogenide Semiconductor Thin Films (4 papers), Optical Polarization and Ellipsometry (4 papers), Quantum Dots Synthesis And Properties (4 papers), Statistical and numerical algorithms (3 papers), Electrocatalysts for Energy Conversion (2 papers) and Crystal Structures and Properties (2 papers). The work is most often cited by research in Pharmaceutical Science (123 citations), Drug Discovery (2 citations), Molecular Medicine (35 citations), Biomaterials (31 citations) and Bioengineering (5 citations). Long V. Le has collaborated with scholars based in Vietnam, South Korea and United States. Frequent co-authors include Tejal Ashwin Desai, Cade B. Fox, Jean Kim, Cameron L. Nemeth, Hariharasudhan D. Chirra, Benjamin C. Tang, Michael A. Invernale, Daniel G. Anderson, Young Dong Kim and D. E. Aspnes. Their work appears in journals such as Nanomaterials, Journal of Applied Physics, physica status solidi (b), Journal of Controlled Release and International Journal of Hydrogen Energy.

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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