Eiaki V. Morooka

1.2k total citations · 1 hit paper
6 papers, 861 citations indexed

About

Eiaki V. Morooka is a scholar working on Materials Chemistry, Renewable Energy, Sustainability and the Environment and Electronic, Optical and Magnetic Materials. According to data from OpenAlex, Eiaki V. Morooka has authored 6 papers receiving a total of 861 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Materials Chemistry, 2 papers in Renewable Energy, Sustainability and the Environment and 2 papers in Electronic, Optical and Magnetic Materials. Recurrent topics in Eiaki V. Morooka's work include Machine Learning in Materials Science (5 papers), X-ray Diffraction in Crystallography (2 papers) and Electrocatalysts for Energy Conversion (2 papers). Eiaki V. Morooka is often cited by papers focused on Machine Learning in Materials Science (5 papers), X-ray Diffraction in Crystallography (2 papers) and Electrocatalysts for Energy Conversion (2 papers). Eiaki V. Morooka collaborates with scholars based in Finland, Japan and Sweden. Eiaki V. Morooka's co-authors include Filippo Federici Canova, Adam S. Foster, Lauri Himanen, Patrick Rinke, Yashasvi S. Ranawat, David Gao, Milica Todorović, Alex Aperis, Peter M. Oppeneer and Hiroaki Kusunose and has published in prestigious journals such as The Journal of Chemical Physics, Computer Physics Communications and Annals of Physics.

In The Last Decade

Eiaki V. Morooka

6 papers receiving 847 citations

Hit Papers

DScribe: Library of descriptors for machine learning in m... 2019 2026 2021 2023 2019 100 200 300 400 500

Peers

Eiaki V. Morooka
James Chapman United States
Tsz Wai Ko United States
Eric Gossett United States
Jacob R. Boes United States
Eiaki V. Morooka
Citations per year, relative to Eiaki V. Morooka Eiaki V. Morooka (= 1×) peers Lauri Himanen

Countries citing papers authored by Eiaki V. Morooka

Since Specialization
Citations

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

Fields of papers citing papers by Eiaki V. Morooka

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Eiaki V. Morooka. 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 Eiaki V. Morooka. The network helps show where Eiaki V. Morooka may publish in the future.

Co-authorship network of co-authors of Eiaki V. Morooka

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

All Works

6 of 6 papers shown
1.
Himanen, Lauri, et al.. (2023). Updates to the DScribe library: New descriptors and derivatives. The Journal of Chemical Physics. 158(23). 47 indexed citations
2.
Suzuki, Michi‐To, Takuya Nomoto, Eiaki V. Morooka, Yuki Yanagi, & Hiroaki Kusunose. (2023). High-performance descriptor for magnetic materials: Accurate discrimination of magnetic structure. Physical review. B.. 108(1). 2 indexed citations
3.
Aperis, Alex, Eiaki V. Morooka, & Peter M. Oppeneer. (2020). Influence of electron–phonon coupling strength on signatures of even and odd-frequency superconductivity. Annals of Physics. 417. 168095–168095. 5 indexed citations
4.
Ranawat, Yashasvi S., et al.. (2020). Efficient Machine-Learning-Aided Screening of Hydrogen Adsorption on Bimetallic Nanoclusters. ACS Combinatorial Science. 22(12). 768–781. 35 indexed citations
5.
Himanen, Lauri, Eiaki V. Morooka, Filippo Federici Canova, et al.. (2019). DScribe: Library of descriptors for machine learning in materials science. Computer Physics Communications. 247. 106949–106949. 570 indexed citations breakdown →
6.
Morooka, Eiaki V., et al.. (2018). Machine learning hydrogen adsorption on nanoclusters through structural descriptors. npj Computational Materials. 4(1). 202 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026