Junya Inoue

2.5k total citations
111 papers, 2.0k citations indexed

About

Junya Inoue is a scholar working on Mechanical Engineering, Materials Chemistry and Mechanics of Materials. According to data from OpenAlex, Junya Inoue has authored 111 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 81 papers in Mechanical Engineering, 42 papers in Materials Chemistry and 30 papers in Mechanics of Materials. Recurrent topics in Junya Inoue's work include Microstructure and Mechanical Properties of Steels (37 papers), Microstructure and mechanical properties (21 papers) and Aluminum Alloys Composites Properties (14 papers). Junya Inoue is often cited by papers focused on Microstructure and Mechanical Properties of Steels (37 papers), Microstructure and mechanical properties (21 papers) and Aluminum Alloys Composites Properties (14 papers). Junya Inoue collaborates with scholars based in Japan, China and United States. Junya Inoue's co-authors include Toshihiko Koseki, Shoichi Nambu, Takafumi Koseki, S. Nambu, M. Michiuchi, Tadashi Kasuya, Kentaro Asakura, M. Ojima, Alireza Sadeghi and Satoshi Noguchi and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Geophysical Research Atmospheres and Acta Materialia.

In The Last Decade

Junya Inoue

99 papers receiving 1.9k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Junya Inoue Japan 23 1.6k 1.0k 501 260 196 111 2.0k
Ankit Srivastava United States 26 1.4k 0.9× 1.4k 1.3× 732 1.5× 165 0.6× 163 0.8× 91 2.1k
Anand K. Kanjarla India 20 1.3k 0.8× 1.4k 1.3× 808 1.6× 126 0.5× 151 0.8× 53 1.9k
Jaber Rezaei Mianroodi Germany 23 870 0.5× 718 0.7× 384 0.8× 90 0.3× 294 1.5× 43 1.5k
B.P.C. Rao India 22 990 0.6× 257 0.2× 548 1.1× 195 0.8× 84 0.4× 98 1.3k
P.F. Thomson Australia 26 1.5k 0.9× 1.1k 1.1× 848 1.7× 59 0.2× 405 2.1× 102 2.1k
Veera Sundararaghavan United States 34 1.3k 0.8× 1.4k 1.3× 1.4k 2.8× 116 0.4× 198 1.0× 127 2.9k
Yuksel C. Yabansu United States 19 638 0.4× 864 0.8× 508 1.0× 124 0.5× 156 0.8× 21 1.5k
Chongmin Kim South Korea 20 1.2k 0.7× 426 0.4× 670 1.3× 54 0.2× 125 0.6× 58 1.4k
Laurent Babout Poland 21 960 0.6× 578 0.6× 473 0.9× 140 0.5× 213 1.1× 66 1.6k
Li Niu China 21 528 0.3× 596 0.6× 433 0.9× 71 0.3× 79 0.4× 82 1.3k

Countries citing papers authored by Junya Inoue

Since Specialization
Citations

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

Fields of papers citing papers by Junya Inoue

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Junya Inoue

This figure shows the co-authorship network connecting the top 25 collaborators of Junya Inoue. A scholar is included among the top collaborators of Junya Inoue 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 Junya Inoue. Junya Inoue 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
1.
2.
Qiao, Ling, et al.. (2025). Grain growth and oxidation resistance of Fe2.5Ni2.5CrAl multi-principal elements alloy at high temperature. Vacuum. 233. 114020–114020. 3 indexed citations
3.
Qiao, Ling, Junya Inoue, & Jingchuan Zhu. (2025). Artificial intelligence and molecular dynamics assisted analysis of wear behavior of high entropy alloys. Materials & Design. 257. 114379–114379. 1 indexed citations
4.
Zhang, Meng, et al.. (2024). In-situ electron channeling contrast imaging of local deformation behavior of lath martensite in low-carbon-steel. Acta Materialia. 280. 120337–120337. 3 indexed citations
5.
Qiao, Ling, Jingchuan Zhu, & Junya Inoue. (2024). Machine learning assisted design of Fe-Ni-Cr-Al based multi-principal elements alloys with ultra-high microhardness and unexpected wear resistance. Journal of Materials Research and Technology. 33. 8222–8231. 9 indexed citations
6.
Qiao, Ling, R.V. Ramanujan, Junya Inoue, & Jingchuan Zhu. (2024). Superior oxidation behavior, good electrical conductivity, and thermophysical properties of FeCr1.2Ni1.5Al multi-principal element alloys. Journal of Alloys and Compounds. 1010. 178025–178025. 4 indexed citations
7.
Zhang, Meng, et al.. (2023). GPU-accelerated artificial neural network potential for molecular dynamics simulation. Computer Physics Communications. 285. 108655–108655. 10 indexed citations
8.
Noguchi, Satoshi, et al.. (2023). Microstructure Estimation by Combining Deep Learning and Phase Transformation Model. ISIJ International. 64(1). 142–153. 3 indexed citations
9.
Noguchi, Satoshi, Hui Wang, & Junya Inoue. (2022). Identification of microstructures critically affecting material properties using machine learning framework based on metallurgists’ thinking process. Scientific Reports. 12(1). 14238–14238. 7 indexed citations
10.
11.
Inoue, Junya, et al.. (2020). Unsupervised microstructure segmentation by mimicking metallurgists’ approach to pattern recognition. Scientific Reports. 10(1). 17835–17835. 45 indexed citations
12.
Ito, Shin‐ichi, Hiromichi Nagao, Takashi Kurokawa, Tadashi Kasuya, & Junya Inoue. (2019). Bayesian inference of grain growth prediction via multi-phase-field models. Japan Geoscience Union. 1 indexed citations
13.
Inoue, Junya, et al.. (2018). NEMERICAL EXPERIMENTS BY SATURATED-UNSATURATED FLOW INVERSION FOR PERMEABILITY AND BOUNDARY CONDITIONS OF MULTI-LAYERS AQUIFER. Journal of Japan Society of Civil Engineers Ser A2 (Applied Mechanics (AM)). 74(2). I_55–I_64.
14.
Nambu, S., et al.. (2012). Fracture Toughness Evaluation of Thin Fe-Al Intermetallic Compound Layer at Reactive Interface between Dissimilar Metals. Journal of the Japan Institute of Metals and Materials. 76(4). 272–277. 17 indexed citations
15.
Nambu, Shoichi, et al.. (2012). Effect of Stress on Variant Selection of Lath Martensite in Low-carbon Steel. Tetsu-to-Hagane. 98(8). 425–433. 2 indexed citations
16.
Koseki, Toshihiko & Junya Inoue. (2012). Toughness Evaluation of Dissimilar Material Interface and Reaction Layer Formed at the Interface. Journal of The Surface Finishing Society of Japan. 63(12). 725–727. 1 indexed citations
17.
Nambu, Shoichi, et al.. (2010). Transformation Behavior of Ferrite at Steel/B1 Compounds Interface. Tetsu-to-Hagane. 96(3). 123–128. 15 indexed citations
18.
Nambu, Shoichi, et al.. (2009). Transient Liquid Phase Bonding of Mg Alloy to Steel. 2009. 105–105. 1 indexed citations
19.
Asakura, Kentaro, et al.. (2008). In-situ Observation of Ferrite Plate Formation in Low Carbon Steel during Continuous Cooling Process. Tetsu-to-Hagane. 94(9). 363–368. 6 indexed citations
20.
Chun, Pang‐jo & Junya Inoue. (2006). MECHANISM AND NUMERICAL SIMULATION OF ANOMALOUS TRANSPORT IN VISCOUS FLUID. Doboku Gakkai Ronbunshuu C. 62(1). 85–96. 1 indexed citations

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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