Dongli Tan

3.0k total citations · 4 hit papers
54 papers, 2.3k citations indexed

About

Dongli Tan is a scholar working on Fluid Flow and Transfer Processes, Materials Chemistry and Automotive Engineering. According to data from OpenAlex, Dongli Tan has authored 54 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Fluid Flow and Transfer Processes, 27 papers in Materials Chemistry and 23 papers in Automotive Engineering. Recurrent topics in Dongli Tan's work include Advanced Combustion Engine Technologies (30 papers), Catalytic Processes in Materials Science (27 papers) and Biodiesel Production and Applications (22 papers). Dongli Tan is often cited by papers focused on Advanced Combustion Engine Technologies (30 papers), Catalytic Processes in Materials Science (27 papers) and Biodiesel Production and Applications (22 papers). Dongli Tan collaborates with scholars based in China, United Kingdom and Thailand. Dongli Tan's co-authors include Zhiqing Zhang, Jie Tian, Junshuai Lv, Jiangtao Li, Rui Dong, Sheng Gao, Su Wang, Yunhao Zhong, Jianbin Luo and Jiedong Ye and has published in prestigious journals such as Energy, Fuel and Journal of Environmental Management.

In The Last Decade

Dongli Tan

51 papers receiving 2.3k citations

Hit Papers

The effects of Fe2O3 based DOC and SCR catalyst on the co... 2021 2026 2022 2024 2021 2022 2022 2024 50 100 150 200

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dongli Tan China 25 1.3k 1.1k 963 772 407 54 2.3k
Jianbing Gao China 31 1.4k 1.0× 721 0.7× 944 1.0× 1.3k 1.6× 428 1.1× 103 2.7k
Ayat Gharehghani Iran 34 1.6k 1.2× 1.2k 1.1× 671 0.7× 931 1.2× 689 1.7× 101 2.9k
Jinke Gong China 21 675 0.5× 734 0.7× 559 0.6× 565 0.7× 354 0.9× 55 1.7k
Stanislav V. Bohac United States 28 1.7k 1.3× 762 0.7× 732 0.8× 843 1.1× 217 0.5× 88 2.2k
Ocktaeck Lim South Korea 21 952 0.7× 549 0.5× 436 0.5× 579 0.8× 469 1.2× 210 1.9k
Fanhua Ma China 28 1.7k 1.3× 657 0.6× 545 0.6× 946 1.2× 157 0.4× 79 2.1k
Christopher Depcik United States 22 716 0.5× 531 0.5× 522 0.5× 632 0.8× 736 1.8× 120 2.3k
Long Liu China 21 972 0.7× 439 0.4× 573 0.6× 378 0.5× 308 0.8× 84 1.7k
Xingyu Liang China 34 958 0.7× 583 0.5× 924 1.0× 566 0.7× 1.9k 4.6× 180 3.7k
Yuqiang Li China 23 1.0k 0.8× 969 0.9× 459 0.5× 431 0.6× 347 0.9× 77 1.9k

Countries citing papers authored by Dongli Tan

Since Specialization
Citations

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

Fields of papers citing papers by Dongli Tan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dongli Tan

This figure shows the co-authorship network connecting the top 25 collaborators of Dongli Tan. A scholar is included among the top collaborators of Dongli Tan 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 Dongli Tan. Dongli Tan 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, Zhiqing, He Zhang, Yuguo Wang, et al.. (2025). An artificial intelligence optimization of NOx conversion efficiency under dual catalytic mechanism reaction based on multi-objective gray wolf algorithm. Fuel Processing Technology. 268. 108182–108182. 3 indexed citations
2.
Li, Junming, Dongli Tan, Zhiqing Zhang, et al.. (2025). Multi-objective optimization of combustion and emission characteristics of ammonia-diesel dual-fuel engines under HPDI strategy based on ELM-MOPSO. Results in Engineering. 29. 108705–108705.
4.
Li, Dongmei, Mingzhang Pan, Wei Guan, et al.. (2024). Soot formation mechanism of modern automobile engines and methods of reducing soot emission for catalyzed diesel particulate filter: A review. Process Safety and Environmental Protection. 190. 1403–1430. 7 indexed citations
5.
Zhang, Zhiqing, et al.. (2024). Experimental study of ammonia storage characteristics of selective catalytic reduction for diesel engine based on Cu-based catalysts. Process Safety and Environmental Protection. 190. 368–380. 5 indexed citations
6.
Pan, Mingzhang, Wei Guan, Liang Lu, et al.. (2024). An energy management strategy for fuel cell hybrid electric vehicle based on HHO-BiLSTM-TCN-self attention speed prediction. Energy. 307. 132734–132734. 8 indexed citations
7.
Zhang, Zhiqing, Hui Liu, Dayong Yang, et al.. (2024). Performance enhancements of power density and exergy efficiency for high-temperature proton exchange membrane fuel cell based on RSM-NSGA III. Energy. 301. 131687–131687. 13 indexed citations
8.
Zhang, Zhiqing, Jingyi Hu, Dayong Yang, et al.. (2024). A comprehensive assessment over the environmental impact and combustion efficiency of using ammonia/ hydrogen/diesel blends in a diesel engine. Energy. 303. 131955–131955. 27 indexed citations
10.
Tan, Dongli, Rui Dong, Zhiqing Zhang, et al.. (2023). Multi-objective impact mechanism on the performance characteristic for a diesel particulate filter by RF-NSGA III-TOPSIS during soot loading. Energy. 286. 129582–129582. 38 indexed citations
11.
Zhang, Zhiqing, Ziheng Zhao, Dongli Tan, et al.. (2023). Overview of mechanisms of promotion and inhibition by H2O for selective catalytic reduction denitrification. Fuel Processing Technology. 252. 107956–107956. 12 indexed citations
12.
Zhang, Zhiqing, Rui Dong, Dongli Tan, et al.. (2023). Effect of structural parameters on diesel particulate filter trapping performance of heavy-duty diesel engines based on grey correlation analysis. Energy. 271. 127025–127025. 60 indexed citations
13.
Dong, Rui, et al.. (2023). Diesel particulate filter regeneration mechanism of modern automobile engines and methods of reducing PM emissions: a review. Environmental Science and Pollution Research. 30(14). 39338–39376. 64 indexed citations
16.
Luo, Jianbin, et al.. (2022). Investigation of the Aerodynamic Characteristics of Platoon Vehicles Based on Ahmed Body. Shock and Vibration. 2022. 1–19. 4 indexed citations
17.
Tan, Dongli, Zhiyong Chen, Jiangtao Li, et al.. (2021). Effects of Swirl and Boiling Heat Transfer on the Performance Enhancement and Emission Reduction for a Medium Diesel Engine Fueled with Biodiesel. Processes. 9(3). 568–568. 53 indexed citations
18.
Zhang, Yanhui, Yunhao Zhong, Jie Wang, et al.. (2021). Effects of Different Biodiesel-Diesel Blend Fuel on Combustion and Emission Characteristics of a Diesel Engine. Processes. 9(11). 1984–1984. 46 indexed citations
19.
Zhang, Zhiqing, Jie Tian, Jiangtao Li, et al.. (2021). Effects of Different Mixture Ratios of Methanol-Diesel on the Performance Enhancement and Emission Reduction for a Diesel Engine. Processes. 9(8). 1366–1366. 24 indexed citations
20.
Zhang, Zhiqing, et al.. (2021). Effects of Different Diesel-Ethanol Dual Fuel Ratio on Performance and Emission Characteristics of Diesel Engine. Processes. 9(7). 1135–1135. 35 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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