Ge Xiong

152 total papers · 2.2k total citations
80 papers, 1.8k citations indexed

About

Ge Xiong is a scholar working on Condensed Matter Physics, Electronic, Optical and Magnetic Materials and Surgery. According to data from OpenAlex, Ge Xiong has authored 80 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Condensed Matter Physics, 27 papers in Electronic, Optical and Magnetic Materials and 24 papers in Surgery. Recurrent topics in Ge Xiong's work include Magnetic and transport properties of perovskites and related materials (25 papers), Physics of Superconductivity and Magnetism (22 papers) and Orthopedic Surgery and Rehabilitation (20 papers). Ge Xiong is often cited by papers focused on Magnetic and transport properties of perovskites and related materials (25 papers), Physics of Superconductivity and Magnetism (22 papers) and Orthopedic Surgery and Rehabilitation (20 papers). Ge Xiong collaborates with scholars based in China, United States and United Kingdom. Ge Xiong's co-authors include T. Venkatesan, H. L. Ju, R. L. Greene, Qi Li, J. Gopalakrishnan, J. L. Peng, Quan Li, R. L. Greene, S. E. Lofland and X. X. Xi and has published in prestigious journals such as Physical Review Letters, Physical review. B, Condensed matter and Applied Physics Letters.

In The Last Decade

Ge Xiong

73 papers receiving 1.8k citations

Hit Papers

Dependence of giant magne... 1995 2026 2005 2015 1995 100 200 300 400

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Ge Xiong 1.4k 1.2k 627 98 93 80 1.8k
Midori Tanaka 801 0.6× 630 0.5× 551 0.9× 35 0.4× 118 1.3× 111 1.6k
Satoshi Koyama 502 0.4× 848 0.7× 173 0.3× 117 1.2× 68 0.7× 109 1.5k
B. Hensel 505 0.4× 1.2k 0.9× 297 0.5× 27 0.3× 39 0.4× 85 2.0k
Toshihiko Maeda 433 0.3× 642 0.5× 148 0.2× 143 1.5× 371 4.0× 126 2.1k
Giancarlo Trimarchi 404 0.3× 334 0.3× 759 1.2× 68 0.7× 109 1.2× 82 1.6k
Hideaki Sakata 581 0.4× 533 0.4× 400 0.6× 36 0.4× 64 0.7× 138 1.5k
Kunihiko Osaka 325 0.2× 182 0.1× 299 0.5× 134 1.4× 93 1.0× 52 1.3k
Toshiya Doi 605 0.4× 1000 0.8× 349 0.6× 74 0.8× 87 0.9× 156 2.0k
Kazuki Iida 707 0.5× 754 0.6× 192 0.3× 61 0.6× 78 0.8× 80 1.3k
Ingyu Kim 663 0.5× 375 0.3× 460 0.7× 58 0.6× 495 5.3× 28 1.3k

Countries citing papers authored by Ge Xiong

Since Specialization
Citations

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

Fields of papers citing papers by Ge Xiong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ge Xiong

This figure shows the co-authorship network connecting the top 25 collaborators of Ge Xiong. A scholar is included among the top collaborators of Ge Xiong 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 Ge Xiong. Ge Xiong is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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