Junfu Li

5.0k total citations
98 papers, 2.6k citations indexed

About

Junfu Li is a scholar working on Electrical and Electronic Engineering, Automotive Engineering and Renewable Energy, Sustainability and the Environment. According to data from OpenAlex, Junfu Li has authored 98 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 61 papers in Electrical and Electronic Engineering, 53 papers in Automotive Engineering and 11 papers in Renewable Energy, Sustainability and the Environment. Recurrent topics in Junfu Li's work include Advanced Battery Technologies Research (53 papers), Advancements in Battery Materials (50 papers) and Advanced Battery Materials and Technologies (31 papers). Junfu Li is often cited by papers focused on Advanced Battery Technologies Research (53 papers), Advancements in Battery Materials (50 papers) and Advanced Battery Materials and Technologies (31 papers). Junfu Li collaborates with scholars based in China, United Kingdom and United States. Junfu Li's co-authors include Chao Lyu, Michael Pecht, Daqiang Gao, Lixin Wang, Zhengmei Zhang, Jinmei Qian, Liqiang Zhang, Jun Zheng, Dafang Wang and Gareth Hinds and has published in prestigious journals such as Angewandte Chemie International Edition, SHILAP Revista de lepidopterología and Nano Letters.

In The Last Decade

Junfu Li

94 papers receiving 2.5k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Junfu Li China 31 1.8k 1.4k 483 289 271 98 2.6k
Guangxu Zhang China 24 1.6k 0.9× 1.5k 1.1× 78 0.2× 109 0.4× 76 0.3× 70 2.1k
Gaozhi Xiao Canada 25 1.3k 0.7× 309 0.2× 74 0.2× 45 0.2× 181 0.7× 102 2.2k
Yanyan Shao China 24 1.4k 0.8× 211 0.1× 172 0.4× 14 0.0× 423 1.6× 61 2.6k
Jiajie Chen China 24 479 0.3× 371 0.3× 195 0.4× 34 0.1× 176 0.6× 90 2.0k
Jae Hyun Lee South Korea 20 1.4k 0.8× 841 0.6× 251 0.5× 39 0.1× 140 0.5× 62 1.9k
Yonglu Liu China 23 1.6k 0.9× 452 0.3× 117 0.2× 672 2.3× 40 0.1× 134 2.0k
Wencheng Tang China 38 1.2k 0.7× 60 0.0× 824 1.7× 190 0.7× 3.3k 12.3× 128 4.3k
Siamak Farhad United States 31 1.6k 0.9× 1.2k 0.9× 193 0.4× 117 0.4× 547 2.0× 91 2.6k
Yutian Lei China 38 3.1k 1.8× 335 0.2× 100 0.2× 448 1.6× 680 2.5× 93 3.8k
E. Larsen Denmark 15 651 0.4× 412 0.3× 99 0.2× 261 0.9× 108 0.4× 37 1.2k

Countries citing papers authored by Junfu Li

Since Specialization
Citations

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

Fields of papers citing papers by Junfu Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Junfu Li

This figure shows the co-authorship network connecting the top 25 collaborators of Junfu Li. A scholar is included among the top collaborators of Junfu Li based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Junfu Li. Junfu Li is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Wang, Yaxuan, Yue Cui, Liang Deng, et al.. (2025). A comprehensive review of machine learning-based state of health estimation for lithium-ion batteries: data, features, algorithms, and future challenges. Renewable and Sustainable Energy Reviews. 224. 116125–116125. 7 indexed citations
2.
Li, Junfu, et al.. (2025). A simplified electrochemical modeling method for sodium-ion batteries. Journal of Energy Storage. 112. 115495–115495. 5 indexed citations
3.
Wang, Yaxuan, et al.. (2025). A diagnostic model for lithium plating in lithium-ion batteries incorporating a simplified electrochemical-thermal coupling model. Journal of Solid State Electrochemistry. 29(9). 3811–3828. 1 indexed citations
4.
Li, Junfu, et al.. (2025). 3D-printed hydrogel substrates with tailored pore architectures enhance root development and elicit species-specific growth responses. Chemical Engineering Journal. 512. 162425–162425. 1 indexed citations
5.
Wang, Yaxuan, Yue Cui, Lei Zhao, et al.. (2025). A method for battery health estimation under variable operating conditions based on the fusion of simplified electrochemical model and alpha evolution-back propagation model. Journal of Energy Storage. 123. 116866–116866. 2 indexed citations
6.
7.
8.
Li, Junfu, et al.. (2024). Deep learning method for online parameter identification of lithium-ion batteries using electrochemical synthetic data. Energy storage materials. 72. 103697–103697. 9 indexed citations
9.
Li, Junfu, et al.. (2024). Engineering living root with mechanical stimulation derived from reciprocating compression in a double network hydrogel as elastic soil. SHILAP Revista de lepidopterología. 4(2). 123–131. 1 indexed citations
10.
Liu, Qinbo, et al.. (2024). Ternary Eutectic Electrolyte for Flexible Wide‐Temperature Zinc‐Ion Batteries from −20 °C to 70 °C. Angewandte Chemie International Edition. 64(2). e202414728–e202414728. 17 indexed citations
11.
Yu, Hanqing, Zhengjie Zhang, Lisheng Zhang, et al.. (2023). Physics-informed ensemble deep learning framework for improving state of charge estimation of lithium-ion batteries. Journal of Energy Storage. 73. 108915–108915. 19 indexed citations
12.
Li, Junfu, et al.. (2023). A novel method of discharge capacity prediction based on simplified electrochemical model-aging mechanism for lithium-ion batteries. Journal of Energy Storage. 61. 106788–106788. 43 indexed citations
13.
Yu, Hanqing, Lisheng Zhang, Wentao Wang, et al.. (2023). Simplified numerical modeling and analysis of electrolyte behavior in multiple physical fields for lithium-ion batteries. Journal of Energy Storage. 72. 108536–108536. 9 indexed citations
14.
Yu, Hanqing, Mengzheng Ouyang, Bin Ma, et al.. (2023). Multi-output ensemble deep learning: A framework for simultaneous prediction of multiple electrode material properties. Chemical Engineering Journal. 475. 146280–146280. 17 indexed citations
15.
Qiu, Jingjiang, Junfu Li, Zhongwei Guo, et al.. (2023). 3D Printing of Individualized Microfluidic Chips with DLP-Based Printer. Materials. 16(21). 6984–6984. 13 indexed citations
16.
Li, Junfu, et al.. (2023). Internal fault diagnosis method for lithium batteries based on a failure physical model. Engineering Failure Analysis. 154. 107714–107714. 14 indexed citations
17.
Wang, Yaxuan, Junfu Li, Ming Zhao, et al.. (2023). A Method of Lithium-Ion Battery Failure Diagnosis Based on Parameter Boundaries of Heterogeneous Multi-Physics Aging Model. SSRN Electronic Journal. 1 indexed citations
18.
Yu, Quanqing, et al.. (2022). A branch current estimation and correction method for a parallel connected battery system based on dual BP neural networks. Green Energy and Intelligent Transportation. 1(2). 100029–100029. 60 indexed citations
19.
Li, Junfu, Rungtiwa Phookamsak, Hong-Bo Jiang, et al.. (2022). Additions to the Inventory of the Genus Alternaria Section Alternaria (Pleosporaceae, Pleosporales) in Italy. Journal of Fungi. 8(9). 898–898. 23 indexed citations
20.
Li, Junfu, Rajesh Jeewon, Rungtiwa Phookamsak, et al.. (2018). Marinophialophora garethjonesii gen. et sp. nov.: a new hyphomycete associated with Halocyphina from marine habitats in Thailand. Phytotaxa. 345(1). 10 indexed citations

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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