Zenan Li

631 citations
29 papers · 365 · h-index 11

Impact in

Papers in

Zenan Li

27 papers receiving 357 citations

Peers

Zenan Li
Comparison fields: 5 of 52
  • Software 49
  • Renewable Energy, Sustainability and the Environment 112
  • Artificial Intelligence 86
  • Materials Chemistry 114
  • Automotive Engineering 29
Replace Lei Shang with:
Lei Shang China
Junkil Park South Korea
K. Punitha India
K. Scott United States
Haijin Ji China
Kaushik Mallik Germany
Inhwan Lee South Korea
Ross Smith United States
Frederick Webber United States
Zenan Li relative to Lei Shang China Lei Shang's profile →
Citations per field
00.5×4.7×
Lei Shang · 1×
Citations per year

Countries citing papers authored by Zenan Li

Since Specialization
Citations

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

Fields of papers citing papers by Zenan Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201979
2 202337
3 202431
4 202427
5 202425
6 202322
7 202419
8 202417
9 202412
10 202411
11 202510
12 202410
13 20239
14 20238
15 20247
16 20247
17 20226
18 20245
19 20235
20 20204

About Zenan Li

Zenan Li is a scholar working on Electrical and Electronic Engineering, Renewable Energy, Sustainability and the Environment, Artificial Intelligence, Materials Chemistry and Automotive Engineering, having authored 29 papers that have together received 365 indexed citations. Recurring topics across this work include Advanced Photocatalysis Techniques (7 papers), Advancements in Battery Materials (7 papers), Adversarial Robustness in Machine Learning (5 papers), Advanced Battery Materials and Technologies (4 papers), Advanced Nanomaterials in Catalysis (4 papers), Advanced Battery Technologies Research (3 papers), Anomaly Detection Techniques and Applications (3 papers) and Machine Learning and Data Classification (3 papers). The work is most often cited by research in Software (49 citations), Renewable Energy, Sustainability and the Environment (112 citations), Artificial Intelligence (86 citations), Materials Chemistry (114 citations) and Automotive Engineering (29 citations). Zenan Li has collaborated with scholars based in China, Macao and United States. Frequent co-authors include Xiaoxing Ma, Chun Cao, Chang Xu, Zhenhui Kang, Jun Wang, Ting Yang, Y. Zhang, Yonghong Deng, Yang Liu and Fan Liao. Their work appears in journals such as Applied Catalysis B: Environmental, Journal of Power Sources, Nano Research, Nature Communications and ACS Energy Letters.

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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