Mingming Guo

4.0k total citations
172 papers, 3.0k citations indexed

About

Mingming Guo is a scholar working on Materials Chemistry, Aerospace Engineering and Computational Mechanics. According to data from OpenAlex, Mingming Guo has authored 172 papers receiving a total of 3.0k indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Materials Chemistry, 34 papers in Aerospace Engineering and 32 papers in Computational Mechanics. Recurrent topics in Mingming Guo's work include Computational Fluid Dynamics and Aerodynamics (23 papers), Fluid Dynamics and Turbulent Flows (14 papers) and Aerodynamics and Acoustics in Jet Flows (12 papers). Mingming Guo is often cited by papers focused on Computational Fluid Dynamics and Aerodynamics (23 papers), Fluid Dynamics and Turbulent Flows (14 papers) and Aerodynamics and Acoustics in Jet Flows (12 papers). Mingming Guo collaborates with scholars based in China, United States and Russia. Mingming Guo's co-authors include Ye Tian, Jialing Le, H. G. Zachmann, Fuyu Zhong, Stephen Z. D. Cheng, Frank W. Harris, Yichuan Zhang, Hao Chen, Yong Liu and Liming Dai and has published in prestigious journals such as The Journal of Chemical Physics, SHILAP Revista de lepidopterología and ACS Nano.

In The Last Decade

Mingming Guo

165 papers receiving 2.9k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mingming Guo China 32 874 508 476 459 407 172 3.0k
Satoru Yamamoto Japan 34 1.2k 1.4× 823 1.6× 570 1.2× 334 0.7× 228 0.6× 204 4.4k
Xin Han China 33 1.2k 1.3× 501 1.0× 406 0.9× 124 0.3× 258 0.6× 182 3.8k
Bo He China 23 847 1.0× 196 0.4× 1.2k 2.5× 308 0.7× 518 1.3× 67 3.5k
Hui Liu China 25 621 0.7× 102 0.2× 495 1.0× 256 0.6× 581 1.4× 169 3.4k
Ling Liu China 39 1.4k 1.6× 390 0.8× 1.1k 2.4× 279 0.6× 212 0.5× 191 4.7k
Qiang Wu China 38 1.1k 1.2× 953 1.9× 1.4k 2.9× 369 0.8× 398 1.0× 240 4.5k
Zhiwei He China 42 1.2k 1.3× 295 0.6× 890 1.9× 137 0.3× 284 0.7× 218 5.9k
Kwan H. Lee South Korea 36 897 1.0× 511 1.0× 1.2k 2.5× 280 0.6× 401 1.0× 186 4.7k
Xiaohan Zhang China 29 1.3k 1.5× 185 0.4× 458 1.0× 104 0.2× 206 0.5× 132 3.2k
Paul J. Pigram Australia 28 883 1.0× 660 1.3× 1.0k 2.1× 353 0.8× 382 0.9× 143 3.6k

Countries citing papers authored by Mingming Guo

Since Specialization
Citations

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

Fields of papers citing papers by Mingming Guo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mingming Guo

This figure shows the co-authorship network connecting the top 25 collaborators of Mingming Guo. A scholar is included among the top collaborators of Mingming Guo 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 Mingming Guo. Mingming Guo 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.
Chen, Jingjing, Shangsheng Li, Meihua Hu, et al.. (2025). Growth and characterization of diamond with B-Fe3P co-doped grown along the (100) surface. Ceramics International. 51(11). 14021–14027. 1 indexed citations
2.
Guo, Mingming, Ye Tian, Yi Zhang, et al.. (2025). Fast prediction of flow field in scramjet combustor based on physical information neural network under wide Mach number. Chinese Journal of Aeronautics. 38(7). 103482–103482. 2 indexed citations
3.
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5.
Le, Jialing, et al.. (2024). Progress and prospects of artificial intelligence development and applications in supersonic flow and combustion. Progress in Aerospace Sciences. 151. 101046–101046. 11 indexed citations
6.
Guo, Mingming, Ye Tian, Linjing Li, et al.. (2024). Supersonic combustion flow field reconstruction based on multi-view domain adaptation generative network in scramjet combustor. Engineering Applications of Artificial Intelligence. 136. 108981–108981. 4 indexed citations
7.
Xu, Yueling, et al.. (2024). Effect of ionic bonding on luminescence properties of histidine maleic anhydride derivatives. Materials Today Chemistry. 41. 102340–102340.
8.
Guo, Mingming, et al.. (2024). Supersonic combustion field evolution prediction in scramjet engine using a deblurring multi-scale attention network. Expert Systems with Applications. 252. 124290–124290. 5 indexed citations
9.
Tang, Zhimeng, Kun Huang, Yichuan Zhang, et al.. (2024). Microwave-treated layered graphite for highly efficient solar-powered seawater desalination and wastewater treatment. Desalination. 593. 118227–118227. 3 indexed citations
10.
Guo, Mingming, et al.. (2024). Hypersonic inlet flow field reconstruction dominated by shock wave and boundary layer based on small sample physics-informed neural networks. Aerospace Science and Technology. 150. 109205–109205. 12 indexed citations
11.
Yin, Na, Wenya Wang, Fei Pei, et al.. (2024). A Neutrophil Hijacking Nanoplatform Reprograming NETosis for Targeted Microglia Polarizing Mediated Ischemic Stroke Treatment. Advanced Science. 11(17). e2305877–e2305877. 21 indexed citations
12.
Guo, Mingming, et al.. (2024). Evolution prediction of flame structure in a hydrogen-fueled scramjet combustor based on lightweight deformable convolutional residual neural network. Engineering Applications of Artificial Intelligence. 138. 109435–109435. 4 indexed citations
13.
Tian, Ye, et al.. (2023). Intelligent reconstruction algorithm of hydrogen-fueled scramjet combustor flow based on knowledge distillation model compression. International Journal of Hydrogen Energy. 49. 1278–1291. 15 indexed citations
14.
Guo, Mingming, et al.. (2023). Uncertainty quantification and identification of SST turbulence model parameters based on Bayesian optimization algorithm in supersonic flow. International Journal for Numerical Methods in Fluids. 96(3). 277–296. 7 indexed citations
15.
Huang, Chuan, Qinbin Zhang, Yichuan Zhang, & Mingming Guo. (2023). Room temperature phosphorescence based on nitrogen-phosphorus co-doped carbonized polymer dots for information encryption. Colloids and Surfaces A Physicochemical and Engineering Aspects. 668. 131456–131456. 21 indexed citations
16.
17.
Zhang, Yichuan, Hanqi Zhang, Mingming Guo, J. De Coninck, & David Seveno. (2023). Reactive Spreading Dynamics of Molten Polymer Liquids. Macromolecules. 56(3). 1111–1121. 16 indexed citations
18.
Wang, Yang, Jun Chen, Jiekang Tian, et al.. (2022). Tryptophan-sorbitol based carbon quantum dots for theranostics against hepatocellular carcinoma. Journal of Nanobiotechnology. 20(1). 78–78. 44 indexed citations
19.
Hu, Hui, et al.. (2020). Synthesis, Characterization, and Charge-Transport Properties of Halogenated Dibenzo[a,j]perylenes. The Journal of Organic Chemistry. 85(19). 12243–12251. 5 indexed citations
20.
Yu, Kunpeng, Shangsheng Li, Qun Yang, et al.. (2019). Effects of phosphorus dopingviaMn3P2on diamond growth along the (100) surfaces. CrystEngComm. 21(44). 6810–6818. 17 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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