Shuming Guo

1.3k total citations · 1 hit paper
14 papers, 1000 citations indexed

About

Shuming Guo is a scholar working on Mechanical Engineering, Electrical and Electronic Engineering and Global and Planetary Change. According to data from OpenAlex, Shuming Guo has authored 14 papers receiving a total of 1000 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Mechanical Engineering, 4 papers in Electrical and Electronic Engineering and 4 papers in Global and Planetary Change. Recurrent topics in Shuming Guo's work include Advanced machining processes and optimization (6 papers), Lubricants and Their Additives (6 papers) and Advanced Machining and Optimization Techniques (4 papers). Shuming Guo is often cited by papers focused on Advanced machining processes and optimization (6 papers), Lubricants and Their Additives (6 papers) and Advanced Machining and Optimization Techniques (4 papers). Shuming Guo collaborates with scholars based in China, United States and Japan. Shuming Guo's co-authors include Yanbin Zhang, Changhe Li, Min Yang, Yaogang Wang, Xianpeng Zhang, Guotao Liu, Benkai Li, Dongzhou Jia, Huajun Cao and Naiqing Zhang and has published in prestigious journals such as Journal of Cleaner Production, International Journal of Molecular Sciences and Applied Surface Science.

In The Last Decade

Shuming Guo

12 papers receiving 974 citations

Hit Papers

align trajectories

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.

Experimental evaluation of the lubrication performance of mixtures of castor oil with other vegetable oils in MQL grinding of nickel-based alloy

2016 337 citations Shuming Guo, Changhe Li et al. Journal of Cleaner Production profile →

Peers

Shuming Guo

EEE

Lan Dong China

Guoqiang Guo China

Xiaolong Lu China

Takashi Kuboki Japan

Zhenjing Duan China

Sakshum Khanna India

Nikhil Kumar India

A. C. Ramamurthy United States

Éanna McCarthy Ireland

D.N. Thatoi India

Lan Dong China

Shuming Guo

771 ×1.0

417 ×1.1

EEE

422 ×1.1

226 ×0.9

149 ×0.7

Citations per year, relative to Shuming Guo Shuming Guo (= 1×) peers Lan Dong

Countries citing papers authored by Shuming Guo

Since Specialization

Citations

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

Fields of papers citing papers by Shuming Guo

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shuming Guo

This figure shows the co-authorship network connecting the top 25 collaborators of Shuming Guo. A scholar is included among the top collaborators of Shuming 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 Shuming Guo. Shuming Guo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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14 of 14 papers shown

Li, Jun, Zhanwei Li, Zhen Zhao, et al.. (2025). Growth and survival of three hatchery-bred giant clams (Tridacna derasa, T. squamosa, and T. crocea) in an ocean nursery: a pilot of restocking study in China. Marine Biodiversity. 55(2). 1 indexed citations

Zhao, Zhen, Liqiang Zhao, Shuming Guo, et al.. (2025). Exploring the symbiotic resilience of boring giant clams and zooxanthellae during heatwave conditions: An investigation into strategic countermeasures. Aquaculture. 607. 742596–742596. 1 indexed citations

Zhao, Zhen, Xixi Duan, Tao Zhang, et al.. (2025). Adapting to hypo-salinity: Molecular mechanisms in giant clams and symbionts with implications for coral reef resilience under climate change. Environmental Research. 285(Pt 2). 122385–122385.

Yang, Xiaogang, Shuming Guo, Zhen Zhao, et al.. (2024). Analysis of molecular identity and function of putative serotonin receptors in the Giant clam (Tridacna crocea) and the potential role of 5-HT1D-like receptor in reproduction. Aquaculture. 593. 741247–741247.

Zhao, Zhen, Shuming Guo, Yanping Qin, et al.. (2024). A Testis-Specific DMRT1 (Double Sex and Mab-3-Related Transcription Factor 1) Plays a Role in Spermatogenesis and Gonadal Development in the Hermaphrodite Boring Giant Clam Tridacna crocea. International Journal of Molecular Sciences. 25(11). 5574–5574. 1 indexed citations

Guo, Shuming, et al.. (2024). Tribological behavior and lubrication mechanism of polyalphaolefin with added Cu-Ni bimetallic nanoparticles on a TiN coating. Applied Surface Science. 679. 161287–161287. 5 indexed citations

Guo, Shuming, et al.. (2023). Superlubricity of TiN coating using glycerol with the addition of Cu nanoparticles. Tribology International. 181. 108327–108327. 12 indexed citations

Guo, Shuming, Changhe Li, Yanbin Zhang, et al.. (2017). Analysis of volume ratio of castor/soybean oil mixture on minimum quantity lubrication grinding performance and microstructure evaluation by fractal dimension. Industrial Crops and Products. 111. 494–505. 53 indexed citations

Jia, Dongzhou, Changhe Li, Yanbin Zhang, et al.. (2017). Specific energy and surface roughness of minimum quantity lubrication grinding Ni-based alloy with mixed vegetable oil-based nanofluids. Precision Engineering. 50. 248–262. 99 indexed citations

10.

Liu, Guotao, Changhe Li, Yanbin Zhang, et al.. (2017). Process parameter optimization and experimental evaluation for nanofluid MQL in grinding Ti-6Al-4V based on grey relational analysis. Materials and Manufacturing Processes. 33(9). 950–963. 51 indexed citations

11.

Wang, Yaogang, Changhe Li, Yanbin Zhang, et al.. (2017). Comparative evaluation of the lubricating properties of vegetable-oil-based nanofluids between frictional test and grinding experiment. Journal of Manufacturing Processes. 26. 94–104. 100 indexed citations

12.

Zhang, Xianpeng, Changhe Li, Yanbin Zhang, et al.. (2016). Lubricating property of MQL grinding of Al2O3/SiC mixed nanofluid with different particle sizes and microtopography analysis by cross-correlation. Precision Engineering. 47. 532–545. 115 indexed citations

13.

Guo, Shuming, Changhe Li, Yanbin Zhang, et al.. (2016). Experimental evaluation of the lubrication performance of mixtures of castor oil with other vegetable oils in MQL grinding of nickel-based alloy. Journal of Cleaner Production. 140. 1060–1076. 337 indexed citations breakdown →

14.

Wang, Yaogang, Changhe Li, Yanbin Zhang, et al.. (2016). Experimental evaluation of the lubrication properties of the wheel/workpiece interface in MQL grinding with different nanofluids. Tribology International. 99. 198–210. 225 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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