Hai‐Jun Jin

3.1k citations
67 papers · 2.6k · h-index 28

Impact in

Papers in

Hai‐Jun Jin

64 papers receiving 2.6k citations

Peers

Hai‐Jun Jin
Comparison fields: 5 of 60
  • Renewable Energy, Sustainability and the Environment 1.3k
  • Materials Chemistry 2.4k
  • Electronic, Optical and Magnetic Materials 700
  • Structural Biology 31
  • Ceramics and Composites 65
Replace Mahdi Ghorbani‐Asl with:
Mahdi Ghorbani‐Asl Germany
Eun Ju Moon United States
Taizo Sasaki Japan
Doug D. Perovic Canada
Sandeep Gorantla Germany
Hakim Iddir United States
Dmitry G. Kvashnin Russia
Mitsutaka Haruta Japan
Vincent Mauchamp France
Riad Nechache Canada
Hai‐Jun Jin relative to Mahdi Ghorbani‐Asl Germany Mahdi Ghorbani‐Asl's profile →
Citations per field
00.5×2.5×
Mahdi Ghorbani‐Asl · 1×
Citations per year

Countries citing papers authored by Hai‐Jun Jin

Since Specialization
Citations

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

Fields of papers citing papers by Hai‐Jun Jin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hai‐Jun Jin. 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 Hai‐Jun Jin. The network helps show where Hai‐Jun Jin may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 67 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2009282
2 2009273
3 2009200
4 2011169
5 2010115
6 2016111
7 2008106
8 201892
9 201479
10 201568
11 200761
12 201456
13 201753
14 201848
15 201348
16 201344
17 202042
18 200341
19 201940
20 201239

About Hai‐Jun Jin

Hai‐Jun Jin is a scholar working on Materials Chemistry, Renewable Energy, Sustainability and the Environment, Electronic, Optical and Magnetic Materials, Mechanical Engineering and Organic Chemistry, having authored 67 papers that have together received 2.6k indexed citations. Recurring topics across this work include Nanoporous metals and alloys (57 papers), Anodic Oxide Films and Nanostructures (35 papers), Electrocatalysts for Energy Conversion (35 papers), Supercapacitor Materials and Fabrication (14 papers), Nanocluster Synthesis and Applications (8 papers), Metallic Glasses and Amorphous Alloys (6 papers), Material Dynamics and Properties (5 papers) and Nanomaterials for catalytic reactions (4 papers). The work is most often cited by research in Renewable Energy, Sustainability and the Environment (1.3k citations), Materials Chemistry (2.4k citations), Electronic, Optical and Magnetic Materials (700 citations), Structural Biology (31 citations) and Ceramics and Composites (65 citations). Hai‐Jun Jin has collaborated with scholars based in China, Germany and United States. Frequent co-authors include Jörg Weißmüller, Liu L, Smrutiranjan Parida, Yulia Ivanisenko, Andrèa M. Hodge, Roger Newman, Jeffrey W. Kysar, Masahiro Seo, Ke Wang and Hui Xie. Their work appears in journals such as Acta Materialia, Scripta Materialia, Advanced Engineering Materials, Applied Physics Letters and Journal of The Electrochemical Society.

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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