Fang Lan

4.5k citations
182 papers · 3.6k · h-index 30

Impact in

    • Nanoparticle-Based Drug Delivery
    • Bone Tissue Engineering Materials
    • Nanoplatforms for cancer theranostics
    • Graphene and Nanomaterials Applications

Papers in

Fang Lan

173 papers receiving 3.5k citations

Peers

Fang Lan
Comparison fields: 5 of 148
  • Biomaterials 712
  • Biomedical Engineering 1.1k
  • Condensed Matter Physics 244
  • Spectroscopy 305
  • Molecular Biology 1.2k
Replace Yi Jia with:
Yi Jia China
Kang Chen China
Dermot F. Brougham Ireland
Zhuo Chen China
Zhi Li China
Qinrui Fu China
Yiyang Lin China
Ke Wang China
Zi Gu Australia
Fang Lan relative to Yi Jia China Yi Jia's profile →
Citations per field
00.5×1.5×2.4×
Yi Jia · 1×
Citations per year

Countries citing papers authored by Fang Lan

Since Specialization
Citations

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

Fields of papers citing papers by Fang Lan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 182 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2013431
2 2014155
3 2017113
4 201998
5 201896
6 201186
7 199383
8 201779
9 201972
10 201970
11 201667
12 201962
13 201860
14 202055
15 201153
16 201650
17 201643
18 202341
19 201240
20 201839

About Fang Lan

Fang Lan is a scholar working on Molecular Biology, Biomedical Engineering, Materials Chemistry, Electrical and Electronic Engineering and Condensed Matter Physics, having authored 182 papers that have together received 3.6k indexed citations. Recurring topics across this work include Advanced biosensing and bioanalysis techniques (30 papers), Physics of Superconductivity and Magnetism (28 papers), Nanoparticle-Based Drug Delivery (20 papers), Advanced Proteomics Techniques and Applications (11 papers), Glycosylation and Glycoproteins Research (9 papers), Metal-Organic Frameworks: Synthesis and Applications (9 papers), Iron-based superconductors research (9 papers) and CRISPR and Genetic Engineering (9 papers). The work is most often cited by research in Biomaterials (712 citations), Biomedical Engineering (1.1k citations), Condensed Matter Physics (244 citations), Spectroscopy (305 citations) and Molecular Biology (1.2k citations). Fang Lan has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Yao Wu, Zhongwei Gu, Bin Luo, Wen Jiang, Li Li, Hongmei Song, Kui Luo, Zhiyu Li, Qi Yang and Peipei Jiang. Their work appears in journals such as Journal of Materials Chemistry B, Nanoscale, Superconductor Science and Technology, Journal of Colloid and Interface Science and Physica C Superconductivity.

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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