Xianglin Tu

35 papers receiving 1.0k citations

Peers

Xianglin Tu
Comparison fields: 5 of 75
  • Pollution 473
  • Geochemistry and Petrology 237
  • Geophysics 322
  • Health, Toxicology and Mutagenesis 237
  • Artificial Intelligence 376
Replace Todor Serafimovski with:
Todor Serafimovski North Macedonia
Yasumasa Ogawa Japan
Christian Ihlenfeld United Kingdom
Jean M. Morrison United States
J B Percival Canada
Chuanwei Zhu China
S.E. Church United States
Arí Roisenberg Brazil
Chongguang Luo China
Leticia Rosales-Hoz Mexico
Xianglin Tu relative to Todor Serafimovski North Macedonia Todor Serafimovski's profile →
Citations per field
00.5×1.5×2.0×
Todor Serafimovski · 1×
Citations per year

Countries citing papers authored by Xianglin Tu

Since Specialization
Citations

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

Fields of papers citing papers by Xianglin Tu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Xianglin Tu, 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 Xianglin Tu Line = papers co-authored together Xianglin Tu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 36 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2008287
2 2013111
3 201095
4 201370
5 200146
6 201441
7 201134
8 200834
9 200033
10 201232
11 200928
12 202127
13 201126
14 201023
15 201219
16 200918
17 201817
18 201914
19 200313
20 201110

About Xianglin Tu

Xianglin Tu is a scholar working on Artificial Intelligence, Pollution, Geophysics, Geochemistry and Petrology and Ecology, having authored 36 papers that have together received 1.0k indexed citations. Recurring topics across this work include Geochemistry and Geologic Mapping (17 papers), Heavy metals in environment (14 papers), Geological and Geochemical Analysis (13 papers), Geochemistry and Elemental Analysis (8 papers), Radioactive element chemistry and processing (6 papers), Environmental Quality and Pollution (4 papers), earthquake and tectonic studies (4 papers) and Geology and Paleoclimatology Research (4 papers). The work is most often cited by research in Pollution (473 citations), Geochemistry and Petrology (237 citations), Geophysics (322 citations), Health, Toxicology and Mutagenesis (237 citations) and Artificial Intelligence (376 citations). Xianglin Tu has collaborated with scholars based in China, Australia and Sweden. Frequent co-authors include Ruilian Yu, Xing Yuan, Gongren Hu, Xirong Liang, Fangyue Wang, Xiaoyong Yang, Ming‐Xing Ling, Bo Peng, Bo Gao and Haidong Zhou. Their work appears in journals such as Environmental Earth Sciences, Environmental Science and Pollution Research, Geochimica et Cosmochimica Acta, Journal of Analytical Atomic Spectrometry and Science Bulletin.

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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