Lan Luan

2.7k citations
44 papers · 1.9k · 1 hit paper · h-index 21

Impact in

Papers in

Lan Luan

42 papers receiving 1.9k citations

Lan Luan's Hit Papers

Ultraflexible nanoelectronic probes form reliable, glial scar–free neural integration 2017 · 432 citations
4320+3+6Years since publication100200300400

Peers

Lan Luan
Comparison fields: 5 of 106
  • Cellular and Molecular Neuroscience 963
  • Cognitive Neuroscience 538
  • Condensed Matter Physics 298
  • Polymers and Plastics 200
  • Biomedical Engineering 513
Replace Yoon‐Kyu Song with:
Yoon‐Kyu Song United States
Xavi Illa Spain
E.J. Tarte United Kingdom
Erin Patrick United States
Michele Dipalo Italy
James S. Harris United States
Li Zhu China
Takafumi Suzuki Japan
W. Mokwa Germany
Kiwoong Kim South Korea
Lan Luan relative to Yoon‐Kyu Song United States Yoon‐Kyu Song's profile →
Citations per field
00.5×4.9×
Yoon‐Kyu Song · 1×
Citations per year

Countries citing papers authored by Lan Luan

Since Specialization
Citations

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

Fields of papers citing papers by Lan Luan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 44 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Ultraflexible nanoelectronic probes form reliable, glial scar–free neural integration
Hit paper breakdown →
2017432
2 2013169
3 2008155
4 2018119
5 2022106
6 2020101
7 201695
8 202073
9 201072
10 201159
11 201753
12 202051
13 201945
14 202344
15 200742
16 200941
17 202138
18 201534
19 200931
20 201931

About Lan Luan

Lan Luan is a scholar working on Cellular and Molecular Neuroscience, Cognitive Neuroscience, Electrical and Electronic Engineering, Biomedical Engineering and Atomic and Molecular Physics, and Optics, having authored 44 papers that have together received 1.9k indexed citations. Recurring topics across this work include Neuroscience and Neural Engineering (18 papers), Advanced Memory and Neural Computing (11 papers), Neural dynamics and brain function (8 papers), Photoreceptor and optogenetics research (6 papers), EEG and Brain-Computer Interfaces (5 papers), Bone Tissue Engineering Materials (4 papers), Magnetic properties of thin films (4 papers) and Physics of Superconductivity and Magnetism (4 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (963 citations), Cognitive Neuroscience (538 citations), Condensed Matter Physics (298 citations), Polymers and Plastics (200 citations) and Biomedical Engineering (513 citations). Lan Luan has collaborated with scholars based in United States, China and Brazil. Frequent co-authors include Chong Xie, Zhengtuo Zhao, Xiaoling Wei, Ojas Potnis, Andrew K. Dunn, Hanlin Zhu, Kathryn A. Moler, Fei He, Raymond A. Chitwood and Xue Li. Their work appears in journals such as Physical Review B, Cell Reports, Neuron, Science Advances and Advanced Science.

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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