Ke‐Jun Wu

3.1k total citations · 1 hit paper
88 papers, 2.1k citations indexed

About

Ke‐Jun Wu is a scholar working on Materials Chemistry, Catalysis and Biomedical Engineering. According to data from OpenAlex, Ke‐Jun Wu has authored 88 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Materials Chemistry, 30 papers in Catalysis and 24 papers in Biomedical Engineering. Recurrent topics in Ke‐Jun Wu's work include Ionic liquids properties and applications (19 papers), Nanomaterials for catalytic reactions (14 papers) and Phase Equilibria and Thermodynamics (11 papers). Ke‐Jun Wu is often cited by papers focused on Ionic liquids properties and applications (19 papers), Nanomaterials for catalytic reactions (14 papers) and Phase Equilibria and Thermodynamics (11 papers). Ke‐Jun Wu collaborates with scholars based in China, United Kingdom and Australia. Ke‐Jun Wu's co-authors include Chao‐Hong He, Laura Torrente‐Murciano, Congxiao Shang, Edmund C. M. Tse, Zhengxiao Guo, Chun‐Xia Zhao, Liu‐Ying Yu, Simon Kuhn, Jin‐Shun Huang and Guo‐Cong Guo and has published in prestigious journals such as Angewandte Chemie International Edition, Advanced Functional Materials and Chemical Communications.

In The Last Decade

Ke‐Jun Wu

83 papers receiving 2.1k citations

Hit Papers

Nucleation and growth in solution synthesis of nanostruct... 2021 2026 2022 2024 2021 50 100 150 200
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Nucleation and growth in solution synthesis of nanostructures – From fundamentals to advanced applications
    2021 215 citations Ke‐Jun Wu et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ke‐Jun Wu China 28 867 673 619 328 317 88 2.1k
Ana P. C. Ribeiro Portugal 24 629 0.7× 591 0.9× 682 1.1× 235 0.7× 317 1.0× 108 2.1k
Changjun Peng China 26 782 0.9× 717 1.1× 825 1.3× 226 0.7× 344 1.1× 116 2.3k
Gregorio García Spain 24 773 0.9× 620 0.9× 1.5k 2.5× 639 1.9× 546 1.7× 83 2.8k
Juha Lehtonen Finland 27 1.1k 1.3× 1.2k 1.8× 590 1.0× 281 0.9× 821 2.6× 112 2.5k
Carl R.F. Lund United States 23 1.4k 1.6× 984 1.5× 1.0k 1.6× 146 0.4× 537 1.7× 62 2.5k
Ki-Sub Kim South Korea 27 557 0.6× 382 0.6× 1.0k 1.6× 477 1.5× 240 0.8× 95 2.4k
Víctor R. Ferro Spain 27 545 0.6× 699 1.0× 1.3k 2.1× 157 0.5× 725 2.3× 58 2.1k
David H. K. Jackson United States 26 1.3k 1.5× 412 0.6× 535 0.9× 970 3.0× 356 1.1× 44 2.8k
Peng Bai United States 24 742 0.9× 721 1.1× 254 0.4× 135 0.4× 501 1.6× 65 1.9k

Countries citing papers authored by Ke‐Jun Wu

Since Specialization
Citations

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

Fields of papers citing papers by Ke‐Jun Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ke‐Jun Wu. 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 Ke‐Jun Wu. The network helps show where Ke‐Jun Wu may publish in the future.

Co-authorship network of co-authors of Ke‐Jun Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Ke‐Jun Wu. A scholar is included among the top collaborators of Ke‐Jun Wu 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 Ke‐Jun Wu. Ke‐Jun Wu 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.
2.
Rao, C. R., et al.. (2025). Assisted Energetic Material Property Prediction through Advanced Transfer Learning with Graph Neural Networks. Industrial & Engineering Chemistry Research. 64(4). 2396–2405. 2 indexed citations
3.
Hu, Jun, et al.. (2025). High efficient synthesis of HMX from DPT using deep eutectic catalyst. Tetrahedron. 187. 134936–134936.
4.
Wu, Ke‐Jun, Zhenxing Li, You Yang, & Qiong Liu. (2024). Deep video compression based on Long-range Temporal Context Learning. Computer Vision and Image Understanding. 248. 104127–104127. 2 indexed citations
5.
Li, Shuang, et al.. (2024). Lepton pair photoproduction in hadronic heavy-ion collisions with nuclear overlap. Physical review. C. 109(6). 2 indexed citations
6.
Pask, Christopher M., Sang T. Pham, Andrew J. Britton, et al.. (2024). Modulating proton conductivity through crystal structure tuning in arenedisulfonate coordination polymers. Journal of Materials Chemistry A. 12(29). 18440–18451. 3 indexed citations
7.
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Yu, Liu‐Ying, Ke‐Jun Wu, & Chao‐Hong He. (2023). A two-step green liquid-liquid extraction strategy for selective lithium recovery and application to seawater. Hydrometallurgy. 220. 106102–106102. 7 indexed citations
9.
Wu, Ke‐Jun, et al.. (2023). Accelerated room temperature synthesis of desired cesium lead halide perovskite nanocrystals via automated microfluidic meta learner. Chemical Engineering Science. 282. 119318–119318. 3 indexed citations
10.
Wills, Corinne, Thomas W. Chamberlain, Richard A. Bourne, et al.. (2023). Amino‐Modified Polymer Immobilized Ionic Liquid Stabilized Ruthenium Nanoparticles: Efficient and Selective Catalysts for the Partial and Complete Reduction of Quinolines. ChemCatChem. 15(11). 9 indexed citations
11.
Chen, Jianli, et al.. (2023). Continuous heterogeneous synthesis of hexafluoroacetone and its machine learning-assisted optimization. Journal of Flow Chemistry. 13(3). 337–346. 12 indexed citations
12.
Zhang, Chengwei, et al.. (2023). A Review on Artificial Intelligence Enabled Design, Synthesis, and Process Optimization of Chemical Products for Industry 4.0. Processes. 11(2). 330–330. 36 indexed citations
13.
Wu, Ke‐Jun, et al.. (2023). Force field-inspired molecular representation learning for property prediction. Journal of Cheminformatics. 15(1). 17–17. 11 indexed citations
14.
Yu, Liu‐Ying, et al.. (2022). Viscosity model of deep eutectic solvents from group contribution method. AIChE Journal. 68(9). 27 indexed citations
15.
Yu, Liu‐Ying, et al.. (2022). Transition State Theory-Inspired Neural Network for Estimating the Viscosity of Deep Eutectic Solvents. ACS Central Science. 8(7). 983–995. 36 indexed citations
16.
Yu, Liu‐Ying, et al.. (2021). Group and group‐interaction contribution method for estimating the melting temperatures of deep eutectic solvents. AIChE Journal. 68(2). 27 indexed citations
17.
Yang, Mei, et al.. (2021). Integration of microfluidic systems with external fields for multiphase process intensification. Chemical Engineering Science. 234. 116450–116450. 23 indexed citations
18.
Yu, Liu‐Ying, et al.. (2021). Comprehensive Prediction of Densities for Deep Eutectic Solvents: A New Bonding-Group Interaction Contribution Scheme. Industrial & Engineering Chemistry Research. 60(35). 13127–13139. 22 indexed citations
19.
Wu, Ke‐Jun, et al.. (2021). Ultrasound-assisted synthesis of visible-light-driven Ag/g-C3N4 catalysts in a continuous flow reactor. Chemical Engineering Journal. 429. 132412–132412. 22 indexed citations
20.
Wu, Ke‐Jun & Simon Kuhn. (2014). Strategies for solids handling in microreactors. 32. 62–67. 54 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Ana P. C. Ribeiro Breakdown of academic impact, for papers by Changjun Peng Breakdown of academic impact, for papers by Gregorio García Breakdown of academic impact, for papers by Juha Lehtonen Breakdown of academic impact, for papers by Carl R.F. Lund Breakdown of academic impact, for papers by Ki-Sub Kim Breakdown of academic impact, for papers by Víctor R. Ferro Breakdown of academic impact, for papers by David H. K. Jackson Breakdown of academic impact, for papers by Peng Bai
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