Lan Luan

2.8k citations
47 papers · 2.1k · 1 hit paper · h-index 21

Impact in

Papers in

Lan Luan

43 papers receiving 2.0k citations

Lan Luan's Hit Papers

Ultraflexible nanoelectronic probes form reliable, glial scar–free neural integration 2017 · 466 citations
4660+3+6Years since publication100200300400

Peers

Lan Luan
Comparison fields: 5 of 108
  • Cellular and Molecular Neuroscience 1.0k
  • Cognitive Neuroscience 533
  • Condensed Matter Physics 304
  • Polymers and Plastics 201
  • Biomedical Engineering 526
Replace Yoon‐Kyu Song with:
Yoon‐Kyu Song United States
James S. Harris United States
E.J. Tarte United Kingdom
Michele Dipalo Italy
Xavi Illa Spain
Herc P. Neves Belgium
Hongda Chen China
Takafumi Suzuki Japan
Shigeo Sato Japan
Tatsuo Yoshinobu Japan
Lan Luan relative to Yoon‐Kyu Song United States Yoon‐Kyu Song's profile →
Citations per field
00.5×4.6×
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 47 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 →
2017466
2 2013175
3 2008161
4 2018122
5 2022115
6 2020107
7 201697
8 202077
9 201073
10 201162
11 201755
12 202052
13 201948
14 202346
15 200746
16 202143
17 200942
18 201535
19 200932
20 201932

About Lan Luan

Lan Luan is a scholar working on Cellular and Molecular Neuroscience, Electrical and Electronic Engineering, Cognitive Neuroscience, Biomedical Engineering and Atomic and Molecular Physics, and Optics, having authored 47 papers that have together received 2.1k indexed citations. Recurring topics across this work include Neuroscience and Neural Engineering (19 papers), Advanced Memory and Neural Computing (12 papers), Neural dynamics and brain function (8 papers), EEG and Brain-Computer Interfaces (5 papers), Photoreceptor and optogenetics research (5 papers), Magnetic properties of thin films (4 papers), Bone Tissue Engineering Materials (4 papers) and Physics of Superconductivity and Magnetism (4 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (1.0k citations), Cognitive Neuroscience (533 citations), Condensed Matter Physics (304 citations), Polymers and Plastics (201 citations) and Biomedical Engineering (526 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, Fei He, Kathryn A. Moler, Jennifer J. Siegel and Raymond A. Chitwood. Their work appears in journals such as Physical Review B, Advanced Science, Biomaterials, Neuron and Cell 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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