Ming-Long Yao

578 citations
22 papers · 517 · h-index 15

Impact in

Papers in

Ming-Long Yao

22 papers receiving 503 citations

Peers

Ming-Long Yao
Comparison fields: 5 of 66
  • Fluid Flow and Transfer Processes 275
  • Polymers and Plastics 258
  • Materials Chemistry 254
  • Organic Chemistry 147
  • Molecular Medicine 14
Replace J. Mewis with:
J. Mewis Belgium
B. Ernst France
Roland Horst Germany
Y. Séréro France
Hui Dai China
Michael E. De Rosa United States
F. N. Kelley United States
A. Hakiki France
Wenlin Zhang United States
A. V. Semakov Russia
Ming-Long Yao relative to J. Mewis Belgium J. Mewis's profile →
Citations per field
00.5×1.5×2.1×
J. Mewis · 1×
Citations per year

Countries citing papers authored by Ming-Long Yao

Since Specialization
Citations

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

Fields of papers citing papers by Ming-Long Yao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ming-Long Yao. 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 Ming-Long Yao. The network helps show where Ming-Long Yao may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 199772
2 199853
3 199653
4 199640
5 199933
6 199632
7 199730
8 199629
9 199723
10 202122
11 199921
12 201120
13 199819
14 199817
15 199914
16 199813
17 200212
18 19985
19 20225
20 19972

About Ming-Long Yao

Ming-Long Yao is a scholar working on Fluid Flow and Transfer Processes, Materials Chemistry, Organic Chemistry, Polymers and Plastics and Complementary and alternative medicine, having authored 22 papers that have together received 517 indexed citations. Recurring topics across this work include Rheology and Fluid Dynamics Studies (15 papers), Surfactants and Colloidal Systems (10 papers), Material Dynamics and Properties (9 papers), Polymer Nanocomposites and Properties (7 papers), Polymer crystallization and properties (6 papers), Block Copolymer Self-Assembly (2 papers), Neurological Disease Mechanisms and Treatments (2 papers) and Liquid Crystal Research Advancements (2 papers). The work is most often cited by research in Fluid Flow and Transfer Processes (275 citations), Polymers and Plastics (258 citations), Materials Chemistry (254 citations), Organic Chemistry (147 citations) and Molecular Medicine (14 citations). Ming-Long Yao has collaborated with scholars based in Japan, China and Russia. Frequent co-authors include Kunihiro Osaki, Hiroshi Watanabe, Tomohiro Sato, Yotaro Morishima, Toshiyuki Shikata, Yumi Matsumiya, Hirofumi Yamada, Osamu Urakawa, Tadashi Inoue and Nitash P. Balsara. Their work appears in journals such as Rheologica Acta, Macromolecules, Journal of Macromolecular Science Part A, Macromolecular Rapid Communications and Green Chemistry.

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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