Mingdi Yan

6.8k citations
174 papers · 5.5k indexed · h-index 44

Impact in

Papers in

Mingdi Yan

171 papers receiving 5.4k citations

Peers

Mingdi Yan
Comparison fields: 5 of 125
  • Surfaces, Coatings and Films 450
  • Organic Chemistry 1.7k
  • Biomaterials 680
  • Materials Chemistry 1.8k
  • Biomedical Engineering 1.6k
Replace Kenichi Niikura with:
Kenichi Niikura Japan
Matthias Karg Germany
Yoshiko Miura Japan
Thomas Hellweg Germany
Haruma Kawaguchi Japan
Guosong Chen China
Kuniharu Ijiro Japan
Steven L. Regen United States
Aldrik H. Velders Netherlands
Daniel L. Feldheim United States
Mingdi Yan relative to Kenichi Niikura Japan Kenichi Niikura's profile →
Citations per field
00.5×3.4×
Kenichi Niikura · 1×
Citations per year

Countries citing papers authored by Mingdi Yan

Since Specialization
Citations

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

Fields of papers citing papers by Mingdi Yan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20252
2 20251
3 20246
4 20245
5 20245
6 202320
7 20218
8 20216
9 202061
10 202013
11 201817
12 201714
13 201520
14 201420
15 201327
16 201130
17 20118
18
Quantitative Analysis of Multivalent Ligand Presentation on Gold Glyconanoparticles and Their Effects on Protein Binding
20101
19 201075
20 200994

About Mingdi Yan

Mingdi Yan is a scholar working on Surfaces, Coatings and Films, Organic Chemistry, Physical and Theoretical Chemistry, Bioengineering and Biomedical Engineering, having authored 174 papers that have together received 5.5k indexed citations. Recurring topics across this work include Molecular Junctions and Nanostructures (30 papers), Glycosylation and Glycoproteins Research (30 papers), Nanofabrication and Lithography Techniques (24 papers), Click Chemistry and Applications (22 papers), Monoclonal and Polyclonal Antibodies Research (18 papers), Graphene research and applications (17 papers), Carbohydrate Chemistry and Synthesis (13 papers) and Chemical Reactions and Mechanisms (12 papers). The work is most often cited by research in Surfaces, Coatings and Films (450 citations), Organic Chemistry (1.7k citations), Biomaterials (680 citations), Materials Chemistry (1.8k citations) and Biomedical Engineering (1.6k citations). Mingdi Yan has collaborated with scholars based in United States, Sweden and China. Frequent co-authors include Olof Ramström, Lihong Liu, Jaehyeung Park, Xuan Chen, Sheng Xie, Kalana W. Jayawardana, H. Surangi N. Jayawardena, John F. W. Keana, Nanjing Hao and Xin Wang. Their work appears in journals such as Chemical Communications, Analytical Chemistry, Bioconjugate Chemistry, ACS Applied Materials & Interfaces and Chemistry - A European Journal.

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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