Wei‐Chen Huang

2.4k citations
75 papers · 2.0k · h-index 26

Impact in

Papers in

Wei‐Chen Huang

73 papers receiving 1.9k citations

Peers

Wei‐Chen Huang
Comparison fields: 5 of 136
  • Biomaterials 558
  • Molecular Medicine 156
  • Pharmaceutical Science 142
  • Cellular and Molecular Neuroscience 259
  • Pharmacology 112
Replace Na Liang with:
Na Liang China
Madhumita Patel South Korea
Lingling Xu China
Yunxia Sun China
Zi‐Xian Liao Taiwan
Virgilio Brunetti Italy
Tianqing Liu China
Zhifang Sun China
Wei‐Chen Huang relative to Na Liang China Na Liang's profile →
Citations per field
00.5×3.4×
Na Liang · 1×
Citations per year

Countries citing papers authored by Wei‐Chen Huang

Since Specialization
Citations

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

Fields of papers citing papers by Wei‐Chen Huang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Wei‐Chen Huang. 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 Wei‐Chen Huang. The network helps show where Wei‐Chen Huang may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 75 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010219
2 202292
3 201389
4 201777
5 199767
6 201665
7 201863
8 201562
9 201560
10 200959
11 202257
12 202156
13 201655
14 201853
15 201744
16 201343
17 201841
18 201637
19 202034
20 201133

About Wei‐Chen Huang

Wei‐Chen Huang is a scholar working on Biomedical Engineering, Cellular and Molecular Neuroscience, Biomaterials, Polymers and Plastics and Electrical and Electronic Engineering, having authored 75 papers that have together received 2.0k indexed citations. Recurring topics across this work include Neuroscience and Neural Engineering (19 papers), Advanced Sensor and Energy Harvesting Materials (11 papers), Conducting polymers and applications (11 papers), Hydrogels: synthesis, properties, applications (5 papers), Polymer Surface Interaction Studies (5 papers), Nanoparticle-Based Drug Delivery (5 papers), Electrospun Nanofibers in Biomedical Applications (4 papers) and EEG and Brain-Computer Interfaces (4 papers). The work is most often cited by research in Biomaterials (558 citations), Molecular Medicine (156 citations), Pharmaceutical Science (142 citations), Cellular and Molecular Neuroscience (259 citations) and Pharmacology (112 citations). Wei‐Chen Huang has collaborated with scholars based in Taiwan, China and United States. Frequent co-authors include San‐Yuan Chen, You‐Yin Chen, Shang‐Hsiu Hu, Chuangnian Zhang, Zhi Yuan, Qin Tian, Wei Wang, Chunhong Wang, Dibakar Bhattacharyya and Leonidas G. Bachas. Their work appears in journals such as ACS Applied Materials & Interfaces, Journal of Controlled Release, Advanced Materials Interfaces, Advanced Functional Materials and Biomaterials.

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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