Yueqiang Liu

6.9k total citations
274 papers, 4.4k citations indexed

About

Yueqiang Liu is a scholar working on Nuclear and High Energy Physics, Astronomy and Astrophysics and Biomedical Engineering. According to data from OpenAlex, Yueqiang Liu has authored 274 papers receiving a total of 4.4k indexed citations (citations by other indexed papers that have themselves been cited), including 237 papers in Nuclear and High Energy Physics, 161 papers in Astronomy and Astrophysics and 76 papers in Biomedical Engineering. Recurrent topics in Yueqiang Liu's work include Magnetic confinement fusion research (237 papers), Ionosphere and magnetosphere dynamics (160 papers) and Superconducting Materials and Applications (75 papers). Yueqiang Liu is often cited by papers focused on Magnetic confinement fusion research (237 papers), Ionosphere and magnetosphere dynamics (160 papers) and Superconducting Materials and Applications (75 papers). Yueqiang Liu collaborates with scholars based in United States, China and United Kingdom. Yueqiang Liu's co-authors include A. Bondeson, A. Kirk, M. S. Chu, E. Nardon, T. C. Hender, I.T. Chapman, C.-M. Fransson, Bengt Lennartson, Claes Breitholtz and Li Li and has published in prestigious journals such as Physical Review Letters, Journal of Computational Physics and Chemical Engineering Journal.

In The Last Decade

Yueqiang Liu

245 papers receiving 4.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yueqiang Liu United States 33 4.0k 2.7k 1.3k 1.1k 910 274 4.4k
H. Yamada Japan 29 3.2k 0.8× 1.5k 0.6× 796 0.6× 712 0.6× 1.5k 1.6× 289 3.6k
Guosheng Xu China 25 2.6k 0.7× 1.1k 0.4× 797 0.6× 762 0.7× 1.2k 1.3× 259 3.1k
G. Serianni Italy 26 2.5k 0.6× 839 0.3× 374 0.3× 1.6k 1.5× 435 0.5× 290 3.2k
R. Jaspers Netherlands 29 1.9k 0.5× 935 0.4× 367 0.3× 406 0.4× 658 0.7× 104 2.1k
C. Silva Portugal 28 1.9k 0.5× 1.0k 0.4× 387 0.3× 381 0.3× 932 1.0× 191 2.5k
Baonian Wan China 31 4.0k 1.0× 1.5k 0.6× 1.3k 1.0× 1.4k 1.3× 1.6k 1.8× 294 4.6k
M. Yagi Japan 32 3.0k 0.8× 2.3k 0.9× 310 0.2× 285 0.3× 889 1.0× 312 4.0k
M. Kobayashi Japan 28 1.9k 0.5× 665 0.3× 536 0.4× 402 0.4× 1.2k 1.4× 281 2.9k
Y. Sakamoto Japan 30 2.8k 0.7× 1.3k 0.5× 1.0k 0.8× 825 0.8× 1.5k 1.7× 174 3.2k
D. Stutman United States 25 1.6k 0.4× 652 0.2× 421 0.3× 219 0.2× 490 0.5× 147 2.0k

Countries citing papers authored by Yueqiang Liu

Since Specialization
Citations

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

Fields of papers citing papers by Yueqiang Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yueqiang Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Yueqiang Liu. A scholar is included among the top collaborators of Yueqiang Liu 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 Yueqiang Liu. Yueqiang Liu 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.
Liu, Yueqiang, et al.. (2025). Low- n stability and plasma response to RMP in various STEP scenarios. Plasma Physics and Controlled Fusion. 67(8). 85010–85010.
2.
Kim, Charlson C., Francesco Porcelli, D. Banerjee, et al.. (2024). Simulations of vertical displacement oscillatory modes and global Alfvén Eigenmodes in JET geometry. Nuclear Fusion. 64(12). 126064–126064.
3.
Liu, Yueqiang, D. Keeling, A. Kirk, et al.. (2024). Role of electrostatic perturbation on kinetic resistive wall mode with application to spherical tokamak. Nuclear Fusion. 64(6). 66037–66037. 1 indexed citations
4.
Liu, Yueqiang, et al.. (2023). Effects of NBI-induced energetic ions on internal kink stability in HL-2M. Physics of Plasmas. 30(7). 3 indexed citations
5.
Igochine, V., A. Gude, M. Maraschek, et al.. (2023). Plasma effect on error fields correction at high βN in ASDEX Upgrade. Plasma Physics and Controlled Fusion. 65(6). 62001–62001. 4 indexed citations
6.
Akers, R., Yueqiang Liu, A. Loarte, et al.. (2022). LOCUST-GPU predictions of fast-ion transport and power loads due to ELM-control coils in ITER. Nuclear Fusion. 62(12). 126014–126014. 5 indexed citations
7.
Gu, S., C. Paz-Soldan, Yueqiang Liu, et al.. (2022). Influence of triangularity on the plasma response to resonant magnetic perturbations. Nuclear Fusion. 62(7). 76031–76031. 8 indexed citations
8.
Liu, Yueqiang, et al.. (2021). Effect of runaway electrons on tearing mode stability: with or without favorable curvature stabilization. Nuclear Fusion. 61(9). 96034–96034. 5 indexed citations
9.
Wang, Shuo, Yueqiang Liu, X. M. Song, et al.. (2021). Modeling active control of resistive wall mode with power saturation and sensor noise on HL-2M. Plasma Physics and Controlled Fusion. 63(5). 55019–55019. 4 indexed citations
10.
Ren, Jie, Youwen Sun, Huihui Wang, et al.. (2021). Penetration of n  =  2 resonant magnetic field perturbations in EAST. Nuclear Fusion. 61(5). 56007–56007. 7 indexed citations
11.
Yang, Xu, et al.. (2021). Influence of elongation and triangularity on plasma response to resonant magnetic perturbations. Nuclear Fusion. 62(1). 16013–16013. 5 indexed citations
12.
Wang, Zhirui, A. H. Glasser, D. P. Brennan, Yueqiang Liu, & Jong-Kyu Park. (2020). Modeling of resistive plasma response in toroidal geometry using an asymptotic matching approach. Physics of Plasmas. 27(12). 3 indexed citations
13.
Zheng, Guanjie, X.R. Duan, Yueqiang Liu, et al.. (2019). Hot VDE investigation of the negative triangularity plasmas based on HL-2M tokamak. Fusion Engineering and Design. 143. 48–58. 12 indexed citations
14.
Wu, Tingting, et al.. (2019). Toroidal modeling of thermal particle drift kinetic effects and sub-sonic plasma flow on internal kink mode. Physics of Plasmas. 26(10). 10 indexed citations
15.
Liu, Yueqiang, Yueqiang Liu, Yan Liu, et al.. (2018). Synthesis of 3-Aryl-1-Indanones via CsF-Promoted Coupling of Arylboronic Acids with N-Tosylhydrazones. Journal of Chemical Research. 42(1). 40–43. 8 indexed citations
16.
Gu, S., Youwen Sun, C. Paz-Soldan, et al.. (2018). Edge localized mode suppression and plasma response using mixed toroidal harmonic resonant magnetic perturbations in DIII-D. Nuclear Fusion. 59(2). 26012–26012. 12 indexed citations
17.
Berkery, J.W., Zhirui Wang, S.A. Sabbagh, et al.. (2017). Application of benchmarked kinetic resistive wall mode stability codes to ITER, including additional physics. Physics of Plasmas. 24(11). 8 indexed citations
18.
Liu, Shengqun, et al.. (2014). Effect of valproic acid on astrocyte proliferation around the central canal in rats following spinal cord injury. Zhonghua chuangshang zazhi. 30(3). 270–273. 1 indexed citations
19.
Rylander, Thomas, A. Bondeson, & Yueqiang Liu. (2004). Stability, accuracy and application of an FDTD-TDFEM algorithm. Chalmers Publication Library (Chalmers University of Technology). 1 indexed citations
20.
Liu, Yueqiang, et al.. (2003). FEM-FDTD hybrid simulation of antennas in vehicles. Chalmers Research (Chalmers University of Technology). 1 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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