So Takamoto

768 total citations
11 papers, 170 citations indexed

About

So Takamoto is a scholar working on Electrical and Electronic Engineering, Materials Chemistry and Atomic and Molecular Physics, and Optics. According to data from OpenAlex, So Takamoto has authored 11 papers receiving a total of 170 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Electrical and Electronic Engineering, 6 papers in Materials Chemistry and 4 papers in Atomic and Molecular Physics, and Optics. Recurrent topics in So Takamoto's work include Semiconductor materials and devices (4 papers), Machine Learning in Materials Science (3 papers) and Silicon Carbide Semiconductor Technologies (3 papers). So Takamoto is often cited by papers focused on Semiconductor materials and devices (4 papers), Machine Learning in Materials Science (3 papers) and Silicon Carbide Semiconductor Technologies (3 papers). So Takamoto collaborates with scholars based in Japan and United States. So Takamoto's co-authors include Satoshi IZUMI, Ju Li, Asuka Hatano, Qing‐Jie Li, Daisuke Okanohara, Takahisa Ohno, Chioko Kaneta, Takahiro Yamasaki, Tomohisa Kumagai and Youichi Murakami and has published in prestigious journals such as Journal of Applied Physics, Scientific Reports and Journal of Chemical Theory and Computation.

In The Last Decade

So Takamoto

9 papers receiving 164 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
So Takamoto Japan 7 111 77 26 24 16 11 170
Thomas A. R. Purcell Germany 9 182 1.6× 58 0.8× 4 0.2× 11 0.5× 26 1.6× 15 238
William J. Baldwin United Kingdom 4 78 0.7× 50 0.6× 2 0.1× 12 0.5× 10 0.6× 8 93
Dominic Waldhoer Austria 10 111 1.0× 241 3.1× 6 0.2× 6 0.3× 19 1.2× 40 288
Jaesun Kim South Korea 9 42 0.4× 193 2.5× 12 0.5× 5 0.2× 107 6.7× 25 239
Yun Teng China 7 233 2.1× 195 2.5× 19 0.7× 32 2.0× 18 296
Chang Woo Oh South Korea 10 132 1.2× 450 5.8× 10 0.4× 4 0.2× 29 1.8× 34 546
Izaac Mitchell Australia 9 138 1.2× 32 0.4× 3 0.1× 22 1.4× 12 165
Zih‐Yu Lin United States 8 122 1.1× 181 2.4× 5 0.2× 22 1.4× 9 228
Xue Gong Singapore 6 385 3.5× 201 2.6× 7 0.3× 23 1.4× 9 443
Pinghui Mo China 6 67 0.6× 42 0.5× 1 0.0× 3 0.1× 14 0.9× 8 90

Countries citing papers authored by So Takamoto

Since Specialization
Citations

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

Fields of papers citing papers by So Takamoto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of So Takamoto

This figure shows the co-authorship network connecting the top 25 collaborators of So Takamoto. A scholar is included among the top collaborators of So Takamoto 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 So Takamoto. So Takamoto is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

11 of 11 papers shown
1.
Hayashi, Akihide, So Takamoto, Ju Li, Yuta Tsuboi, & Daisuke Okanohara. (2025). Generative Model for Constructing Reaction Path from Initial to Final States. Journal of Chemical Theory and Computation. 21(3). 1292–1305.
2.
3.
Takamoto, So, Daisuke Okanohara, Qing‐Jie Li, & Ju Li. (2023). Towards universal neural network interatomic potential. Journal of Materiomics. 9(3). 447–454. 36 indexed citations
4.
Takamoto, So, Satoshi IZUMI, & Ju Li. (2022). TeaNet: Universal neural network interatomic potential inspired by iterative electronic relaxations. Computational Materials Science. 207. 111280–111280. 63 indexed citations
5.
Takamoto, So, et al.. (2020). Temperature-dependent stacking fault energies of 4H-SiC: A first-principles study. Journal of Applied Physics. 127(12). 17 indexed citations
6.
Takamoto, So, et al.. (2019). Reaction pathway analysis for the conversion of perfect screw basal plane dislocation to threading edge dislocation in 4H-SiC. Japanese Journal of Applied Physics. 58(8). 81005–81005. 11 indexed citations
7.
Takamoto, So, et al.. (2018). Development of a method to evaluate the stress distribution in 4H-SiC power devices. Japanese Journal of Applied Physics. 57(10). 106602–106602. 14 indexed citations
8.
Takamoto, So, Takahiro Yamasaki, Jun Nara, et al.. (2018). Atomistic mechanism of graphene growth on a SiC substrate: Large-scale molecular dynamics simulations based on a new charge-transfer bond-order type potential. Physical review. B.. 97(12). 13 indexed citations
9.
10.
Takamoto, So, Tomohisa Kumagai, Takahiro Yamasaki, et al.. (2016). Charge-transfer interatomic potential for investigation of the thermal-oxidation growth process of silicon. Journal of Applied Physics. 120(16). 14 indexed citations
11.
Takamoto, So, et al.. (2014). Analytical method for estimating the thermal expansion coefficient of metals at high temperature. Modelling and Simulation in Materials Science and Engineering. 23(1). 15010–15010. 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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2026