Hailang Wan

1.0k total citations
32 papers, 736 citations indexed

About

Hailang Wan is a scholar working on Mechanics of Materials, Mechanical Engineering and Computational Mechanics. According to data from OpenAlex, Hailang Wan has authored 32 papers receiving a total of 736 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Mechanics of Materials, 16 papers in Mechanical Engineering and 8 papers in Computational Mechanics. Recurrent topics in Hailang Wan's work include Advanced Welding Techniques Analysis (9 papers), Mechanical Behavior of Composites (8 papers) and Laser Material Processing Techniques (7 papers). Hailang Wan is often cited by papers focused on Advanced Welding Techniques Analysis (9 papers), Mechanical Behavior of Composites (8 papers) and Laser Material Processing Techniques (7 papers). Hailang Wan collaborates with scholars based in China, United States and Japan. Hailang Wan's co-authors include Junying Min, Jianping Lin, Chengcheng Sun, Blair E. Carlson, Shuang Wang, Shanglu Yang, Hao Teng, Jiahao Hu, Chuanmin Zhu and Shuangshuang Li and has published in prestigious journals such as ACS Applied Materials & Interfaces, Applied Surface Science and Composites Part B Engineering.

In The Last Decade

Hailang Wan

27 papers receiving 720 citations

Peers

Hailang Wan
Comparison fields: 5 of 59
  • Mechanics of Materials 390
  • Mechanical Engineering 342
  • Computational Mechanics 194
  • Surfaces, Coatings and Films 148
  • Materials Chemistry 148
Replace Chiara Mandolfino with:
Chiara Mandolfino Italy
Enrico Lertora Italy
Guoqing Wu China
Guotao Zhang China
C. Gambaro Italy
Harald Riegel Germany
Hongbo Xia China
T.C. Bor Netherlands
A. Buchman Israel
B.J. Abdul Aleem Saudi Arabia
Chiara Mandolfino Italy View profile →
Citations per field, relative to Hailang Wan
Hailang Wan · 1×
Citations per year, relative to Hailang Wan
Hailang Wan · 1×

Countries citing papers authored by Hailang Wan

Since Specialization
Citations

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

Fields of papers citing papers by Hailang Wan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hailang Wan

This figure shows the co-authorship network connecting the top 25 collaborators of Hailang Wan. A scholar is included among the top collaborators of Hailang Wan 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 Hailang Wan. Hailang Wan 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
# Work Indexed citations
1 0
2 0
3 0
4 1
5 0
6 3
7 5
8 3
9 0
10 1
11 6
12 2
13 17
14 51
15 3
16 22
17 101
18 17
19 31
20 86

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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