Z. M. Hu

1.2k total citations · 1 hit paper
35 papers, 907 citations indexed

About

Z. M. Hu is a scholar working on Molecular Biology, Computational Mechanics and Aerospace Engineering. According to data from OpenAlex, Z. M. Hu has authored 35 papers receiving a total of 907 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Molecular Biology, 15 papers in Computational Mechanics and 11 papers in Aerospace Engineering. Recurrent topics in Z. M. Hu's work include Computational Fluid Dynamics and Aerodynamics (14 papers), Natural product bioactivities and synthesis (9 papers) and Plant biochemistry and biosynthesis (8 papers). Z. M. Hu is often cited by papers focused on Computational Fluid Dynamics and Aerodynamics (14 papers), Natural product bioactivities and synthesis (9 papers) and Plant biochemistry and biosynthesis (8 papers). Z. M. Hu collaborates with scholars based in China, South Korea and Singapore. Z. M. Hu's co-authors include Xue Qiao, Yi Kuang, Zilong Wang, Min Ye, Shuang Wang, Min Ye, Jun‐Bin He, Boo Cheong Khoo, Meng Zhang and R.S. Myong and has published in prestigious journals such as Angewandte Chemie International Edition, SHILAP Revista de lepidopterología and Journal of Fluid Mechanics.

In The Last Decade

Z. M. Hu

34 papers receiving 894 citations

Hit Papers

A comprehensive review on phytochemistry, pharmacology, a... 2018 2026 2020 2023 2018 50 100 150 200 250

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Z. M. Hu China 15 519 283 152 140 110 35 907
Xiaoqiang Wang China 11 603 1.2× 92 0.3× 87 0.6× 157 1.1× 12 0.1× 15 910
Young-Chang Cho South Korea 17 482 0.9× 59 0.2× 93 0.6× 167 1.2× 142 1.3× 83 1.1k
Jang‐Chang Lee Taiwan 10 189 0.4× 40 0.1× 28 0.2× 68 0.5× 18 0.2× 27 420
Sang Myung Lee South Korea 17 384 0.7× 75 0.3× 56 0.4× 177 1.3× 3 0.0× 31 819
Carlo F. Morelli Italy 20 511 1.0× 60 0.2× 9 0.1× 230 1.6× 43 0.4× 86 1.3k
Jaecheol Kim South Korea 13 62 0.1× 60 0.2× 51 0.3× 92 0.7× 36 0.3× 114 527
Thomas Hackl Germany 17 309 0.6× 28 0.1× 20 0.1× 96 0.7× 3 0.0× 77 735
Xinjian Yan United States 20 571 1.1× 73 0.3× 15 0.1× 120 0.9× 8 0.1× 35 1.2k
Sheng-Yi Chen Taiwan 16 275 0.5× 39 0.1× 10 0.1× 79 0.6× 40 0.4× 45 691
Ji Shen China 16 269 0.5× 64 0.2× 8 0.1× 175 1.3× 34 0.3× 85 787

Countries citing papers authored by Z. M. Hu

Since Specialization
Citations

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

Fields of papers citing papers by Z. M. Hu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Z. M. Hu. 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 Z. M. Hu. The network helps show where Z. M. Hu may publish in the future.

Co-authorship network of co-authors of Z. M. Hu

This figure shows the co-authorship network connecting the top 25 collaborators of Z. M. Hu. A scholar is included among the top collaborators of Z. M. Hu 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 Z. M. Hu. Z. M. Hu 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.
Li, Jia, et al.. (2025). Investigation of hydrogen isotope effect at different atomic sites in Nano-crystalline ZrCo. International Journal of Hydrogen Energy. 118. 472–481. 1 indexed citations
2.
Liu, Xiuyu, Xiang Jiao, Ying Ma, et al.. (2023). Structure-function analysis of CYP719As involved in methylenedioxy bridge-formation in the biosynthesis of benzylisoquinoline alkaloids and its de novo production. Microbial Cell Factories. 22(1). 23–23. 8 indexed citations
3.
Hu, Z. M., Ying Ma, Jian Wang, et al.. (2023). Functional characterization of CYP81C16 involved in the tanshinone biosynthetic pathway in Salvia miltiorrhiza. Chinese Journal of Natural Medicines. 21(12). 938–949. 4 indexed citations
4.
5.
Hu, Z. M., et al.. (2022). Functional characterization of a UDP-xylose-preferring <i>C</i>-glycosyltransferase from <i>Lemna aequinoctialis</i>. SHILAP Revista de lepidopterología. 1(1). 1–6. 3 indexed citations
6.
Hu, Z. M., Li Ren, Xiuyu Liu, et al.. (2022). Functional Characterization of a 2OGD Involved in Abietane-Type Diterpenoids Biosynthetic Pathway in Salvia miltiorrhiza. Frontiers in Plant Science. 13. 947674–947674. 10 indexed citations
7.
Zhang, Jianguo, et al.. (2021). Screening and Characterization of Two Extracellular Polysaccharide-Producing Bacteria from the Biocrust of the Mu Us Desert. Molecules. 26(18). 5521–5521. 1 indexed citations
8.
Luo, Changtong, et al.. (2020). Parameter-correlation study on shock–shock interaction using a machine learning method. Aerospace Science and Technology. 107. 106247–106247. 15 indexed citations
9.
Hu, Z. M., Jun‐Bin He, Kuan Chen, et al.. (2019). Molecular cloning and biochemical characterization of a new flavonoid glycosyltransferase from the aquatic plant lotus. Biochemical and Biophysical Research Communications. 510(2). 315–321. 10 indexed citations
10.
Wang, Zilong, Shuang Wang, Zheng Xu, et al.. (2019). Highly Promiscuous Flavonoid 3-O-Glycosyltransferase from Scutellaria baicalensis. Organic Letters. 21(7). 2241–2245. 59 indexed citations
11.
He, Jun‐Bin, Peng Zhao, Z. M. Hu, et al.. (2019). Molecular and Structural Characterization of a Promiscuous C‐Glycosyltransferase from Trollius chinensis. Angewandte Chemie. 131(33). 11637–11644. 18 indexed citations
12.
He, Jun‐Bin, Zeyuan Dong, Z. M. Hu, et al.. (2018). Regio-specific prenylation of pterocarpans by a membrane-bound prenyltransferase from Psoralea corylifolia. Organic & Biomolecular Chemistry. 16(36). 6760–6766. 14 indexed citations
13.
He, Jun‐Bin, Kuan Chen, Z. M. Hu, et al.. (2018). UGT73F17, a new glycosyltransferase from Glycyrrhiza uralensis, catalyzes the regiospecific glycosylation of pentacyclic triterpenoids. Chemical Communications. 54(62). 8594–8597. 34 indexed citations
14.
Hu, Z. M., et al.. (2017). Numerical investigation of the effects of shock tube geometry on the propagation of an ideal blast wave profile. Shock Waves. 27(5). 771–779. 2 indexed citations
15.
Hu, Z. M., Boo Cheong Khoo, & Jianguo Zheng. (2013). The simulation of unsteady cavitating flows with external perturbations. Computers & Fluids. 77. 112–124. 8 indexed citations
16.
Zheng, Jianguo, Boo Cheong Khoo, & Z. M. Hu. (2012). Simulation of Wave-Flow-Cavitation Interaction Using a Compressible Homogenous Flow Method. Communications in Computational Physics. 14(2). 328–354. 18 indexed citations
17.
Hu, Z. M., Hua-Shu Dou, & Boo Cheong Khoo. (2010). On the modified dispersion-controlled dissipative (DCD) scheme for computation of flow supercavitation. Computers & Fluids. 40(1). 315–323. 20 indexed citations
18.
Hu, Z. M., et al.. (2010). Geometric criterion for RR↔MR transition in hypersonic double-wedge flows. Physics of Fluids. 22(1). 21 indexed citations
19.
Hu, Z. M., et al.. (2009). Computational confirmation of an abnormal Mach reflection wave configuration. Physics of Fluids. 21(1). 13 indexed citations
20.
Hu, Z. M., et al.. (2009). Downstream flow condition effects on the RR → MR transition of asymmetric shock waves in steady flows. Journal of Fluid Mechanics. 620. 43–62. 19 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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