Kevin Long

2.2k citations
53 papers · 1.8k · h-index 18

Impact in

Papers in

Kevin Long

52 papers receiving 1.7k citations

Peers

Kevin Long
Comparison fields: 5 of 95
  • Polymers and Plastics 861
  • Mechanical Engineering 825
  • Automotive Engineering 224
  • Biomedical Engineering 583
  • Biotechnology 88
Replace Huifeng Tan with:
Huifeng Tan China
J. Arghavani Iran
Julie Diani France
Pierre Gilormini France
Jayantha Epaarachchi‎ Australia
Qingsheng Yang China
Zaoyang Guo China
Rui Cai China
Alexander Lion Germany
Shanyi Du China
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Citations per field
00.5×1.5×1.9×
Huifeng Tan · 1×
Citations per year

Countries citing papers authored by Kevin Long

Since Specialization
Citations

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

Fields of papers citing papers by Kevin Long

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 53 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2008361
2 2012186
3 2009139
4 2019121
5 2021116
6 201494
7 202092
8 200973
9 201072
10 201338
11 201136
12 202234
13 201834
14 201733
15 202232
16 201732
17 202130
18 201818
19 201017
20 202117

About Kevin Long

Kevin Long is a scholar working on Mechanical Engineering, Polymers and Plastics, Materials Chemistry, Biomedical Engineering and Civil and Structural Engineering, having authored 53 papers that have together received 1.8k indexed citations. Recurring topics across this work include Polymer composites and self-healing (19 papers), Advanced Materials and Mechanics (11 papers), Cellular and Composite Structures (8 papers), Advanced Sensor and Energy Harvesting Materials (7 papers), High-Velocity Impact and Material Behavior (4 papers), Elasticity and Material Modeling (4 papers), Photochromic and Fluorescence Chemistry (4 papers) and Model Reduction and Neural Networks (4 papers). The work is most often cited by research in Polymers and Plastics (861 citations), Mechanical Engineering (825 citations), Automotive Engineering (224 citations), Biomedical Engineering (583 citations) and Biotechnology (88 citations). Kevin Long has collaborated with scholars based in United States, Italy and Switzerland. Frequent co-authors include H. Jerry Qi, Martin L. Dunn, Thao D. Nguyen, F. Castro, Craig M. Hamel, Timothy F. Scott, Christopher M. Yakacki, Kai Yu, Xiaodong Cui and Victor Brunini. Their work appears in journals such as Journal of the Mechanics and Physics of Solids, Mechanics of Materials, International Journal of Solids and Structures, Composites Part B Engineering and Computational Mechanics.

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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