R. Maekawa

437 total citations
41 papers, 241 citations indexed

About

R. Maekawa is a scholar working on Biomedical Engineering, Aerospace Engineering and Nuclear and High Energy Physics. According to data from OpenAlex, R. Maekawa has authored 41 papers receiving a total of 241 indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Biomedical Engineering, 26 papers in Aerospace Engineering and 15 papers in Nuclear and High Energy Physics. Recurrent topics in R. Maekawa's work include Superconducting Materials and Applications (31 papers), Particle accelerators and beam dynamics (14 papers) and Magnetic confinement fusion research (12 papers). R. Maekawa is often cited by papers focused on Superconducting Materials and Applications (31 papers), Particle accelerators and beam dynamics (14 papers) and Magnetic confinement fusion research (12 papers). R. Maekawa collaborates with scholars based in Japan, France and United States. R. Maekawa's co-authors include T. Mito, A. Iwamoto, O. Motojima, F. Sumiyoshi, H. Chikaraishi, N. Yanagi, M. Chalifour, Luigi Serio, S.W. Van Sciver and K. Takahata and has published in prestigious journals such as Nuclear Fusion, Physica C Superconductivity and IEEE Transactions on Applied Superconductivity.

In The Last Decade

R. Maekawa

38 papers receiving 236 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
R. Maekawa Japan 10 174 111 95 58 50 41 241
A. Bonito Oliva Spain 9 278 1.6× 192 1.7× 109 1.1× 77 1.3× 92 1.8× 56 317
Seungtae Oh South Korea 11 123 0.7× 34 0.3× 72 0.8× 127 2.2× 57 1.1× 35 273
F. Wüchner Germany 9 262 1.5× 160 1.4× 129 1.4× 100 1.7× 58 1.2× 34 308
K. Seo Japan 11 232 1.3× 106 1.0× 67 0.7× 138 2.4× 88 1.8× 39 287
E.Yu. Klimenko Russia 11 219 1.3× 124 1.1× 60 0.6× 132 2.3× 60 1.2× 33 292
A. Martínez France 10 212 1.2× 150 1.4× 139 1.5× 50 0.9× 40 0.8× 28 267
K. Chow United States 10 128 0.7× 124 1.1× 56 0.6× 43 0.7× 102 2.0× 27 237
J.S. Bak South Korea 10 234 1.3× 192 1.7× 144 1.5× 29 0.5× 69 1.4× 55 300
F. Hurd Germany 12 271 1.6× 187 1.7× 288 3.0× 76 1.3× 62 1.2× 24 460
Piyush Joshi United States 9 164 0.9× 95 0.9× 42 0.4× 90 1.6× 109 2.2× 28 216

Countries citing papers authored by R. Maekawa

Since Specialization
Citations

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

Fields of papers citing papers by R. Maekawa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of R. Maekawa

This figure shows the co-authorship network connecting the top 25 collaborators of R. Maekawa. A scholar is included among the top collaborators of R. Maekawa 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 R. Maekawa. R. Maekawa 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.
Liu, Fei, et al.. (2024). Dynamic systems modeling of the spallation neutron source cryogenic moderator system to optimize transient control and prepare for power upgrades. IOP Conference Series Materials Science and Engineering. 1301(1). 12088–12088.
2.
Liu, Frank, et al.. (2023). Data-Driven Modeling of a High Capacity Cryogenic System for Control Optimization. IFAC-PapersOnLine. 56(2). 3986–3993. 2 indexed citations
3.
Maekawa, R., et al.. (2020). Dynamic simulation of ITER cryogenic system under D-T operation. IOP Conference Series Materials Science and Engineering. 755(1). 12082–12082. 4 indexed citations
4.
Maekawa, R., et al.. (2016). Optimization of the ITER Cryodistribution for an Efficient Cooling of the Magnet System. IEEE Transactions on Applied Superconductivity. 26(4). 1–4. 11 indexed citations
5.
Maekawa, R., et al.. (2014). Dynamic Simulation of a Forced-flow SHe Test Loop. TEION KOGAKU (Journal of Cryogenics and Superconductivity Society of Japan). 49(6). 311–318. 1 indexed citations
6.
7.
Maekawa, R., et al.. (2012). Dynamic Simulation of Sub-Scale ITER CS/STR Cooling Loop. IEEE Transactions on Applied Superconductivity. 22(3). 4704004–4704004. 8 indexed citations
8.
Maekawa, R., et al.. (2011). Feasibility Studies of the ITER Cryogenic System at KSTAR. IEEE Transactions on Applied Superconductivity. 22(3). 4703804–4703804. 10 indexed citations
9.
Imagawa, S., T. Mito, K. Takahata, et al.. (2010). Overview of LHD Superconducting Magnet System and Its 10-Year Operation. Fusion Science & Technology. 58(1). 560–570. 4 indexed citations
10.
Iwamoto, A., Taku Fujimura, M. Nakai, et al.. (2010). Study on possible fuel layering sequence for FIREX target. Journal of Physics Conference Series. 244(3). 32039–32039. 4 indexed citations
11.
Iwamoto, A., R. Maekawa, T. Mito, et al.. (2007). Preliminary Results of Fuel Layering on the Cryogenic Target for the FIREX Project. Fusion Science & Technology. 51(4). 753–757. 3 indexed citations
12.
Imagawa, S., N. Yanagi, S. Hamaguchi, et al.. (2007). Achievement of high availability in long-term operation and upgrading plan of the LHD superconducting system. Nuclear Fusion. 47(4). 353–360. 10 indexed citations
13.
Iwamoto, A., R. Maekawa, T. Mito, et al.. (2006). Cool-down performance of the apparatus for the cryogenic target of the FIREX project. Fusion Engineering and Design. 81(8-14). 1647–1652. 14 indexed citations
14.
Maekawa, R.. (2006). Characterization of a Co-axial Pulse Tube Cryocooler Applied as a Current Lead. AIP conference proceedings. 823. 1711–1718.
15.
Mito, T., A. Kawagoe, H. Chikaraishi, et al.. (2005). Prototype Development of a Conduction-Cooled LTS Pulse Coil for UPS-SMES. IEEE Transactions on Applied Superconductivity. 15(2). 1935–1938. 7 indexed citations
16.
Haruyama, T., Takakazu Shintomi, H. Nakai, et al.. (2001). The Superfluid Helium Technology for Superconducting Application. Database Development for He II-cooled Superconducting Magnet System Design.. TEION KOGAKU (Journal of Cryogenics and Superconductivity Society of Japan). 36(12). 671–674. 2 indexed citations
17.
Mito, T., R. Maekawa, A. Iwamoto, et al.. (2000). Performance of the LHD cryogenic system during cooling and excitation tests. IEEE Transactions on Applied Superconductivity. 10(1). 1507–1510. 3 indexed citations
18.
Mito, T., K. Takahata, A. Iwamoto, et al.. (1998). Extra AC losses for a CICC coil due to the non-uniform current distribution in the cable. Cryogenics. 38(5). 551–558. 24 indexed citations
19.
Mito, T., et al.. (1997). Superconducting System for the Large Helical Device. Cryogenic System for the Large Helical Device. Cryogenic System.. TEION KOGAKU (Journal of Cryogenics and Superconductivity Society of Japan). 32(11). 608–616. 1 indexed citations
20.
Maekawa, R., et al.. (1993). Characterization of flow in sub-scale cable-in-conduit conductors. IEEE Transactions on Applied Superconductivity. 3(1). 500–502. 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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