Toru Maekawa

4.6k citations
59 papers · 3.4k indexed · 2 hit papers · h-index 29

Toru Maekawa

59 papers receiving 3.3k citations

Hit Papers

Synthesis and characterization of Mon...38720102026201520202505007501000

Peers

Toru Maekawa
Comparison fields: 5 of 130
  • Biomaterials 846
  • Materials Chemistry 1.7k
  • Biomedical Engineering 1.1k
  • Pharmaceutical Science 132
  • Molecular Medicine 103
Replace Denise Wingett with:
Denise Wingett United States
Xiang Zhao China
Diannan Lu China
Zhanghua Zeng China
Rabia Javed Pakistan
Hemant Kumar Daima India
Neenu Singh United Kingdom
Richard C. Murdock United States
Li Zhou China
Shaukat Khan South Korea
Toru Maekawa relative to Denise Wingett United States Denise Wingett's profile →
Citations per field
00.5×2.7×
Denise Wingett · 1×
Citations per year

Countries citing papers authored by Toru Maekawa

Since Specialization
Citations

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

Fields of papers citing papers by Toru Maekawa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 202211
2 20216
3 202044
4 2020101
5 202014
6
Synthesis and characterization of Mono-disperse Carbon Quantum Dots from Fennel Seeds: Photoluminescence analysis using Machine Learningbreakdown →
2019387
7 201838
8 201741
9 201655
10 201510
11 201542
12 201378
13 2012155
14 201234
15 201266
16 201228
17 201234
18 201235
19 201271
20 201143

About Toru Maekawa

Toru Maekawa is a scholar working on Biomaterials, Molecular Medicine and Structural Biology, having authored 59 papers that have together received 3.4k indexed citations. Recurring topics across this work include Nanoparticle-Based Drug Delivery (15 papers), Quantum Dots Synthesis And Properties (14 papers), Nanoplatforms for cancer theranostics (11 papers), Electrospun Nanofibers in Biomedical Applications (10 papers), RNA Interference and Gene Delivery (7 papers), Advanced biosensing and bioanalysis techniques (7 papers), Gold and Silver Nanoparticles Synthesis and Applications (6 papers) and Nanoparticles: synthesis and applications (6 papers). The work is most often cited by research in Biomaterials (846 citations), Materials Chemistry (1.7k citations) and Biomedical Engineering (1.1k citations). Toru Maekawa has collaborated with scholars based in Japan, United States and India. Frequent co-authors include D. Sakthi Kumar, Remya Nair, Saino Hanna Varghese, Baiju G. Nair, Yuko Yoshida, Yasuhiko Yoshida, Yutaka Nagaoka, Masaru Tachibana, Takashi Uchida and M. Sheikh Mohamed. Their work appears in journals such as Advanced Functional Materials, Langmuir and Scientific Reports.

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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