Shaorui Sun

3.9k total citations · 1 hit paper
75 papers, 3.3k citations indexed

About

Shaorui Sun is a scholar working on Materials Chemistry, Electrical and Electronic Engineering and Renewable Energy, Sustainability and the Environment. According to data from OpenAlex, Shaorui Sun has authored 75 papers receiving a total of 3.3k indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Materials Chemistry, 39 papers in Electrical and Electronic Engineering and 28 papers in Renewable Energy, Sustainability and the Environment. Recurrent topics in Shaorui Sun's work include Electrocatalysts for Energy Conversion (19 papers), Advancements in Battery Materials (18 papers) and Advanced Battery Materials and Technologies (13 papers). Shaorui Sun is often cited by papers focused on Electrocatalysts for Energy Conversion (19 papers), Advancements in Battery Materials (18 papers) and Advanced Battery Materials and Technologies (13 papers). Shaorui Sun collaborates with scholars based in China, Australia and United States. Shaorui Sun's co-authors include Lirong Zheng, Ge Chen, Xing Cheng, Dingguo Xia, Zaicheng Sun, Hongliang Bao, Jian‐Qiang Wang, Junxing Han, Zhong Lin Wang and Chunwen Sun and has published in prestigious journals such as Advanced Materials, Angewandte Chemie International Edition and Energy & Environmental Science.

In The Last Decade

Shaorui Sun

75 papers receiving 3.3k citations

Hit Papers

3D N-doped ordered mesoporous carbon supported single-ato... 2020 2026 2022 2024 2020 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shaorui Sun China 31 2.1k 1.8k 1.7k 327 267 75 3.3k
Yi Xiao China 34 1.7k 0.8× 1.4k 0.7× 1.8k 1.1× 457 1.4× 262 1.0× 145 3.3k
Beibei Xiao China 37 2.3k 1.1× 2.4k 1.3× 2.6k 1.6× 521 1.6× 288 1.1× 149 4.5k
Kihyun Shin South Korea 26 1.4k 0.7× 1.4k 0.8× 905 0.5× 332 1.0× 295 1.1× 57 2.5k
Xin Ge China 28 1.7k 0.8× 1.5k 0.8× 1.2k 0.7× 400 1.2× 229 0.9× 54 2.7k
Ted H. Yu United States 22 2.4k 1.2× 2.4k 1.3× 1.2k 0.7× 225 0.7× 215 0.8× 36 3.4k
Xunhua Zhao United States 24 2.1k 1.0× 1.5k 0.8× 1.2k 0.7× 545 1.7× 172 0.6× 42 3.0k
Zhao Li China 36 3.0k 1.5× 2.4k 1.3× 1.9k 1.2× 302 0.9× 796 3.0× 80 4.5k
Zhenming Cao China 26 2.0k 1.0× 1.4k 0.8× 1.4k 0.9× 285 0.9× 388 1.5× 47 2.9k
Miao Xie China 30 1.1k 0.5× 1.8k 1.0× 1.2k 0.7× 238 0.7× 463 1.7× 104 2.9k

Countries citing papers authored by Shaorui Sun

Since Specialization
Citations

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

Fields of papers citing papers by Shaorui Sun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shaorui Sun

This figure shows the co-authorship network connecting the top 25 collaborators of Shaorui Sun. A scholar is included among the top collaborators of Shaorui Sun 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 Shaorui Sun. Shaorui Sun 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.
Zhang, Yunjiang, et al.. (2025). Machine learning and text mining approaches to design selective catalyst reduction synthesis routes. Catalysis Science & Technology. 15(4). 1217–1227. 1 indexed citations
2.
Zhang, Yunjiang, et al.. (2025). CL-GNN: Contrastive Learning and Graph Neural Network for Protein–Ligand Binding Affinity Prediction. Journal of Chemical Information and Modeling. 65(4). 1724–1735. 1 indexed citations
3.
Wang, Huimin, et al.. (2024). The study of strong metal-support interaction enhanced PdZn alloy nanocatalysts for methanol steam reforming. Journal of Alloys and Compounds. 986. 174006–174006. 13 indexed citations
5.
Bai, Kun, et al.. (2024). Artificial intelligence driven design of cathode materials for sodium-ion batteries using graph deep learning method. Journal of Energy Storage. 101. 113809–113809. 16 indexed citations
6.
Zhang, Yunjiang, et al.. (2023). Universal Approach to De Novo Drug Design for Target Proteins Using Deep Reinforcement Learning. ACS Omega. 8(6). 5464–5474. 16 indexed citations
7.
Zhang, Yunjiang, et al.. (2023). Extracting the Synthetic Route of Pd-Based Catalysts in Methanol Steam Reforming from the Scientific Literature. Journal of Chemical Information and Modeling. 63(20). 6249–6260. 6 indexed citations
8.
Zhang, Yunjiang, et al.. (2022). Prediction of Carbon Dioxide Reduction Catalyst Using Machine Learning with a Few-Feature Model: WLEDZ. The Journal of Physical Chemistry C. 126(40). 17025–17035. 19 indexed citations
9.
Li, Yongli, Jinshu Wang, Wei Luo, et al.. (2020). Post-redox engineering electron configurations of atomic thick C3N4 nanosheets for enhanced photocatalytic hydrogen evolution. Applied Catalysis B: Environmental. 270. 118855–118855. 60 indexed citations
10.
Zhang, Guizhen, et al.. (2020). Theoretical Study of the Catalytic Activity and Anti-SO2 Poisoning of a MoO3/V2O5 Selective Catalytic Reduction Catalyst. ACS Omega. 5(42). 26978–26985. 12 indexed citations
11.
Cheng, Xing, Yue Lu, Lirong Zheng, et al.. (2020). Charge redistribution within platinum–nitrogen coordination structure to boost hydrogen evolution. Nano Energy. 73. 104739–104739. 85 indexed citations
12.
Gao, Xiang, Li An, Dan Qu, et al.. (2019). Enhanced photocatalytic N2 fixation by promoting N2 adsorption with a co-catalyst. Science Bulletin. 64(13). 918–925. 133 indexed citations
13.
Yan, Yong, Xing Cheng, Wanwan Zhang, et al.. (2018). Plasma Hydrogenated TiO₂/Nickel Foam as an Efficient Bifunctional Electrocatalyst for Overall Water Splitting. ACS Sustainable Chemistry & Engineering. 1 indexed citations
14.
Cheng, Xing, Yonghe Li, Lirong Zheng, et al.. (2017). Highly active, stable oxidized platinum clusters as electrocatalysts for the hydrogen evolution reaction. Energy & Environmental Science. 10(11). 2450–2458. 282 indexed citations
15.
Sun, Shaorui, et al.. (2017). The effect of point defect on mechanical properties of MoSi2. International Journal of Modern Physics B. 31(16-19). 1744081–1744081. 3 indexed citations
16.
Zhang, Wanwan, et al.. (2016). A precise theoretical method for high- throughput screening of novel organic electrode materials for Li-ion batteries. Journal of Materiomics. 3(3). 184–190. 15 indexed citations
17.
Zhang, Guoqiang, Shaorui Sun, Wenshuai Jiang, et al.. (2016). A Novel Perovskite SrTiO3‐Ba2FeNbO6 Solid Solution for Visible Light Photocatalytic Hydrogen Production. Advanced Energy Materials. 7(2). 54 indexed citations
18.
19.
Sun, Shaorui, Xiaozhou Li, Heng Wang, et al.. (2013). First-principles investigations on the electronic properties and stabilities of low-index surfaces of L12–Al3Sc intermetallic. Applied Surface Science. 288. 609–618. 50 indexed citations
20.
Chen, Ge, Min Li, Fan Li, Shaorui Sun, & Dingguo Xia. (2009). Protein‐Mediated Synthesis of Nanostructured Titania with Different Polymorphs at Room Temperature. Advanced Materials. 22(11). 1258–1262. 33 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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