Haiyang Niu

5.0k citations
47 papers · 4.0k indexed · 1 hit paper · h-index 21
Topics
Machine Learning in Materials Science (11 papers)High-pressure geophysics and materials (9 papers)Boron and Carbon Nanomaterials Research (8 papers)
Partner nations
ChinaUnited StatesRussia

In The Last Decade

Haiyang Niu

41 papers receiving 3.9k citations

Hit Papers

Modeling hardness of polycrystalline materials and bulk m...2011202620162021201150010001.5k2.0k

Peers

Haiyang Niu
Comparison fields: 5 of 82
  • Materials Chemistry 3.2k
  • Mechanical Engineering 1.2k
  • Mechanics of Materials 978
  • Condensed Matter Physics 419
  • Electrical and Electronic Engineering 386
Replace A. Iwase with:
A. Iwase Japan
Vladimir L. Solozhenko France
H. Aourag France
S. V. Khare United States
Oleksandr O. Kurakevych France
B. Johansson Sweden
Paul Saxe United States
R. I. Taylor United States
Xiaohui Yu China
Е. А. Екимов Russia
Haiyang Niu relative to A. Iwase Japan A. Iwase's profile →
Citations per field
00.5×
A. Iwase · 1×
Citations per year

Countries citing papers authored by Haiyang Niu

Since Specialization
Citations

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

Fields of papers citing papers by Haiyang Niu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Haiyang Niu

This figure shows the co-authorship network connecting the top 25 collaborators of Haiyang Niu. A scholar is included among the top collaborators of Haiyang Niu 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 Haiyang Niu. Haiyang Niu 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
#WorkIndexed citations
1 0
2 0
3 2
4 0
5 4
6 0
7 16
8 2
9 13
10 9
11 9
12 146
13 73
14
Novel stable compounds in the Mg-Si-O system under exoplanet pressures and their implications in planetary science
2
15 32
16 7
17 26
18 53
19 171
20 8

About Haiyang Niu

Haiyang Niu is a scholar working on Materials Chemistry, Geophysics and Atmospheric Science, having authored 47 papers that have together received 4.0k indexed citations. Recurring topics across this work include Machine Learning in Materials Science (11 papers), High-pressure geophysics and materials (9 papers) and Boron and Carbon Nanomaterials Research (8 papers). The work is most often cited by research in Materials Chemistry (3.2k citations), Ceramics and Composites (347 citations) and Mechanics of Materials (978 citations). Haiyang Niu has collaborated with scholars based in China, United States and Russia. Frequent co-authors include Xing‐Qiu Chen, Dianzhong Li, Yiyi Li, Michele Parrinello, Artem R. Oganov, Pablo M. Piaggi, Cesare Franchini, Luigi Bonati, Yi Yang and Peitao Liu. Their work appears in journals such as Nature, Proceedings of the National Academy of Sciences and Physical Review Letters.

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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