Dalong Chen

1.3k citations
65 papers · 559 · h-index 14

Impact in

Papers in

Dalong Chen

58 papers receiving 548 citations

Peers

Dalong Chen
Comparison fields: 5 of 48
  • Nuclear and High Energy Physics 381
  • Astronomy and Astrophysics 109
  • Aerospace Engineering 144
  • Artificial Intelligence 100
  • Materials Chemistry 112
Replace A. Pau with:
A. Pau Switzerland
Kevin Montes United States
D. Alves Portugal
D. Valcárcel Portugal
O. Barana Italy
M. Zilker Germany
C. Taliercio Italy
Alexey Svyatkovskiy United States
A. Pereira Spain
J. Schacht Germany
Dalong Chen relative to A. Pau Switzerland A. Pau's profile →
Citations per field
00.5×1.5×2.2×
A. Pau · 1×
Citations per year

Countries citing papers authored by Dalong Chen

Since Specialization
Citations

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

Fields of papers citing papers by Dalong Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Dalong Chen, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Dalong Chen Line = papers co-authored together Dalong Chen links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 65 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201980
2 202142
3 201639
4 202034
5 202132
6 202328
7 201720
8 201619
9 201219
10 201518
11 201916
12 202116
13 202315
14 202113
15 201513
16 201410
17 201610
18 20239
19 20209
20 20158

About Dalong Chen

Dalong Chen is a scholar working on Nuclear and High Energy Physics, Biomedical Engineering, Materials Chemistry, Astronomy and Astrophysics and Electrical and Electronic Engineering, having authored 65 papers that have together received 559 indexed citations. Recurring topics across this work include Magnetic confinement fusion research (48 papers), Superconducting Materials and Applications (16 papers), Ionosphere and magnetosphere dynamics (16 papers), Fusion materials and technologies (16 papers), Particle accelerators and beam dynamics (7 papers), Anomaly Detection Techniques and Applications (5 papers), Plasma Diagnostics and Applications (5 papers) and Network Security and Intrusion Detection (5 papers). The work is most often cited by research in Nuclear and High Energy Physics (381 citations), Astronomy and Astrophysics (109 citations), Aerospace Engineering (144 citations), Artificial Intelligence (100 citations) and Materials Chemistry (112 citations). Dalong Chen has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Bingjia Xiao, R. Granetz, Biao Shen, Youwen Sun, Long Zeng, Cristina Rea, J.P. Qian, Kevin Montes, Bin Shen and Keith Erickson. Their work appears in journals such as Nuclear Fusion, Plasma Physics and Controlled Fusion, Fusion Engineering and Design, Measurement and IEEE Transactions on Plasma Science.

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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