Tooru Matsumiya

1.1k total citations
46 papers, 948 citations indexed

About

Tooru Matsumiya is a scholar working on Mechanical Engineering, Materials Chemistry and Aerospace Engineering. According to data from OpenAlex, Tooru Matsumiya has authored 46 papers receiving a total of 948 indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Mechanical Engineering, 18 papers in Materials Chemistry and 15 papers in Aerospace Engineering. Recurrent topics in Tooru Matsumiya's work include Metallurgical Processes and Thermodynamics (24 papers), Aluminum Alloy Microstructure Properties (12 papers) and Metallurgy and Material Forming (10 papers). Tooru Matsumiya is often cited by papers focused on Metallurgical Processes and Thermodynamics (24 papers), Aluminum Alloy Microstructure Properties (12 papers) and Metallurgy and Material Forming (10 papers). Tooru Matsumiya collaborates with scholars based in Japan, Germany and France. Tooru Matsumiya's co-authors include Hiroyuki Kajioka, Yoshiyuki Ueshima, Shozo Mizoguchi, Kazuto Kawakami, Hisao Esaka, Wataru Yamada, Atsushi Nogami, TOSHIHIKO ARIYOSHI, Jun Tanaka and Hideaki Sawada and has published in prestigious journals such as Physical review. B, Condensed matter, Acta Materialia and Review of Scientific Instruments.

In The Last Decade

Tooru Matsumiya

44 papers receiving 872 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Tooru Matsumiya Japan 16 758 500 346 175 153 46 948
Volker Mohles Germany 21 679 0.9× 871 1.7× 345 1.0× 218 1.2× 62 0.4× 55 1.1k
Hubert I. Aaronson United States 8 614 0.8× 605 1.2× 236 0.7× 134 0.8× 55 0.4× 11 882
Michael F. Henry United States 18 914 1.2× 532 1.1× 318 0.9× 293 1.7× 97 0.6× 39 1.1k
A. R. Jones United Kingdom 17 490 0.6× 453 0.9× 143 0.4× 173 1.0× 70 0.5× 48 706
E.A. Little United Kingdom 18 471 0.6× 904 1.8× 149 0.4× 128 0.7× 245 1.6× 45 1.1k
Staffan Hertzman Sweden 20 898 1.2× 554 1.1× 152 0.4× 168 1.0× 602 3.9× 41 1.1k
Yu. M. Mishin United States 14 519 0.7× 638 1.3× 144 0.4× 140 0.8× 55 0.4× 25 845
G. Saindrenan France 14 417 0.6× 309 0.6× 99 0.3× 197 1.1× 74 0.5× 46 562
Julie D. Tucker United States 16 584 0.8× 563 1.1× 220 0.6× 89 0.5× 236 1.5× 53 943

Countries citing papers authored by Tooru Matsumiya

Since Specialization
Citations

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

Fields of papers citing papers by Tooru Matsumiya

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tooru Matsumiya

This figure shows the co-authorship network connecting the top 25 collaborators of Tooru Matsumiya. A scholar is included among the top collaborators of Tooru Matsumiya 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 Tooru Matsumiya. Tooru Matsumiya 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.
Matsumiya, Tooru, et al.. (2019). Comparison between the Capability of MgO and that of TiN on the Heterogeneous Nucleation of δ-Fe Containing 0.05 mass%C. Tetsu-to-Hagane. 105(8). 803–811. 2 indexed citations
2.
Wakoh, Masamitsu, et al.. (2018). Influence of S Content and Ti Addition on Hot Ductility of Ultra Low Carbon Steels at High Temperature. Tetsu-to-Hagane. 104(12). 776–783. 3 indexed citations
3.
Yamamura, Hideaki, et al.. (2012). Bubble Formation into Flowing Liquid Through a Refractory Having Bad Wettability and Inclusion Removal in Tundish by Ar Bubbles. Tetsu-to-Hagane. 98(12). 650–657. 5 indexed citations
4.
Matsumiya, Tooru. (2012). Estimation of Activity Coefficients and Interaction Parameters of Solutes in Silicon Melts. Metallurgical and Materials Transactions B. 43(4). 726–730. 5 indexed citations
5.
Kawakami, Kazuto & Tooru Matsumiya. (2012). Numerical Analysis of Hydrogen Trap State by TiC and V4C3 in bcc-Fe. ISIJ International. 52(9). 1693–1697. 91 indexed citations
6.
Matsumiya, Tooru. (2011). Steelmaking technology for a sustainable society. Calphad. 35(4). 627–635. 20 indexed citations
7.
Yamamura, Hideaki, et al.. (2007). Influence of Substrate Surface Morphology and Thermal Diffusion on Initial Stage of Rapid Solidification for Steel. Tetsu-to-Hagane. 93(11). 673–680. 3 indexed citations
8.
Matsumiya, Tooru, Keiji Shimoda, Koji Saito, Koji Kanehashi, & Wataru Yamada. (2007). A Proposal for Evaluation Method of Energy Parameter Values in Cell Model for Thermodynamics of Refining Slag. ISIJ International. 47(6). 802–804. 5 indexed citations
9.
Matsumiya, Tooru. (2005). Analyses of diffusion-related phenomena in steel process. Journal of Phase Equilibria and Diffusion. 26(5). 494–502. 3 indexed citations
10.
Kanehashi, Koji, et al.. (2003). Structural Analysis of Slag Using Multinuclear Solid State NMR. Tetsu-to-Hagane. 89(10). 1031–1037. 5 indexed citations
11.
Harada, Hiroshi, Ken-ichi Miyazawa, & Tooru Matsumiya. (2003). Numerical modeling of columnar to equiaxed transition with consideration of molten steel flow. International Journal of Cast Metals Research. 15(3). 301–305. 7 indexed citations
12.
Toh, Takehiko, et al.. (2002). Electromagnetic Casting for High Quality of Continuously Cast Steel. 15(4). 831–834. 1 indexed citations
13.
Matsumiya, Tooru, et al.. (2002). Estimation of thermodynamic properties of solutes in silicon II. Journal of Computer-Aided Materials Design. 9(1). 81–86. 2 indexed citations
14.
Matsumiya, Tooru, et al.. (2002). State of the Art in Integrated Thermodynamic Databases. Tetsu-to-Hagane. 88(2). 51–58. 5 indexed citations
15.
Matsumiya, Tooru. (1996). Simulation of Phase Diagram and Transformation Structure Evolution by the Use of Monte Carlo Method.. Materia Japan. 35(8). 912–917. 1 indexed citations
16.
Nogami, Atsushi, et al.. (1996). A Study on Three Dimensional Monte Carlo Method for Grain Growth Simulation. Materials science forum. 204-206. 303–308. 1 indexed citations
17.
Matsumiya, Tooru, et al.. (1986). An evaluation of critical strain for internal crack formation in continuously cast slabs.. Transactions of the Iron and Steel Institute of Japan. 26(6). 540–546. 35 indexed citations
18.
Matsumiya, Tooru, et al.. (1982). Mathematical Model Analysis on the Formation Mechanism of Longitudinal, Surface Cracks in Continuously Cast Slabs. Tetsu-to-Hagane. 68(13). 1782–1791. 57 indexed citations
19.
Matsumiya, Tooru & M. C. Flemings. (1981). Modeling of continuous strip production by rheocasting. Metallurgical Transactions B. 12(1). 17–31. 18 indexed citations
20.
Yamaguchi, S., et al.. (1980). The effect of minor elements on the hot-workability of nickel-based superalloys. Philosophical Transactions of the Royal Society of London Series A Mathematical and Physical Sciences. 295(1413). 122–122. 2 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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