Long Su

2.8k citations
86 papers · 2.1k · 1 hit paper · h-index 17

Impact in

Papers in

    • Acute Myeloid Leukemia Research 26
    • Multiple Myeloma Research and Treatments 6
    • Chronic Myeloid Leukemia Treatments 6

Long Su

73 papers receiving 2.1k citations

Long Su's Hit Papers

Self-directed self-assembly of nanoparticle/copolymer mixtures 2005 · 821 citations
8210+7+14Years since publication250500750

Peers

Long Su
Comparison fields: 5 of 141
  • Surfaces, Coatings and Films 242
  • Materials Chemistry 769
  • Organic Chemistry 447
  • Hematology 158
  • Biomaterials 149
Replace Yuko Inoue with:
Yuko Inoue Japan
Kyeong Sik Jin South Korea
Matthijn Vos Netherlands
Martina Marchetti‐Deschmann Austria
Aitziber L. Cortajarena Spain
Yue Feng China
Gunter Reekmans Belgium
Katharina Achazi Germany
Thomas A. Jowitt United Kingdom
Herwig Brunner Germany
Long Su relative to Yuko Inoue Japan Yuko Inoue's profile →
Citations per field
00.5×2.7×
Yuko Inoue · 1×
Citations per year

Countries citing papers authored by Long Su

Since Specialization
Citations

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

Fields of papers citing papers by Long Su

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 86 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Self-directed self-assembly of nanoparticle/copolymer mixtures
Hit paper breakdown →
2005821
2 1994311
3 2005213
4 201786
5 201649
6 201249
7 201834
8 202033
9 200531
10 201130
11 201329
12 202127
13 202224
14 201724
15 201922
16 199419
17 199317
18 201115
19 202214
20 199314

About Long Su

Long Su is a scholar working on Molecular Biology, Hematology, Genetics, Genetics and Insect Science, having authored 86 papers that have together received 2.1k indexed citations. Recurring topics across this work include Acute Myeloid Leukemia Research (26 papers), Myeloproliferative Neoplasms: Diagnosis and Treatment (11 papers), Insect and Arachnid Ecology and Behavior (7 papers), Multiple Myeloma Research and Treatments (6 papers), Acute Lymphoblastic Leukemia research (6 papers), Chronic Myeloid Leukemia Treatments (6 papers), Insect-Plant Interactions and Control (6 papers) and Insect and Pesticide Research (5 papers). The work is most often cited by research in Surfaces, Coatings and Films (242 citations), Materials Chemistry (769 citations), Organic Chemistry (447 citations), Hematology (158 citations) and Biomaterials (149 citations). Long Su has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Qian Wang, Alexander Böker, Kevin Sill, Thomas P. Russell, Jinbo He, Yao Lin, Todd Emrick, Clarissa Abetz, Anna C. Balazs and Jin Wang. Their work appears in journals such as Insects, Annals of Hematology, Acta Haematologica, Scientific Data and International Journal of Molecular Sciences.

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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