Lauri Himanen

1.4k total citations · 1 hit paper
12 papers, 859 citations indexed

About

Lauri Himanen is a scholar working on Materials Chemistry, Information Systems and Information Systems and Management. According to data from OpenAlex, Lauri Himanen has authored 12 papers receiving a total of 859 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Materials Chemistry, 2 papers in Information Systems and 2 papers in Information Systems and Management. Recurrent topics in Lauri Himanen's work include Machine Learning in Materials Science (7 papers), X-ray Diffraction in Crystallography (4 papers) and Research Data Management Practices (2 papers). Lauri Himanen is often cited by papers focused on Machine Learning in Materials Science (7 papers), X-ray Diffraction in Crystallography (4 papers) and Research Data Management Practices (2 papers). Lauri Himanen collaborates with scholars based in Finland, Germany and Japan. Lauri Himanen's co-authors include Eiaki V. Morooka, Adam S. Foster, Filippo Federici Canova, Patrick Rinke, Yashasvi S. Ranawat, David Gao, Milica Todorović, Laijun Liu, Nan Zhang and Zhijun Jiang and has published in prestigious journals such as The Journal of Chemical Physics, Advanced Science and Computer Physics Communications.

In The Last Decade

Lauri Himanen

8 papers receiving 843 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

DScribe: Library of descriptors for machine learning in materials science

2019 570 citations Lauri Himanen, Eiaki V. Morooka et al. Computer Physics Communications profile →

Peers

Lauri Himanen

MC

CTM

EEE

RESE

AMPO

Eiaki V. Morooka Finland

Yashasvi S. Ranawat Finland

Alexander Lindmaa Sweden

Jan Kaczmarczyk Poland

James Chapman United States

Christian Künkel Germany

Tsz Wai Ko United States

Mathias Jørgensen Denmark

Eric Gossett United States

Tobias Morawietz United States

Eiaki V. Morooka Finland

Lauri Himanen

744 ×1.0

MC

187 ×1.0

CTM

161 ×1.0

EEE

132 ×1.2

RESE

76 ×1.0

AMPO

Citations per year, relative to Lauri Himanen Lauri Himanen (= 1×) peers Eiaki V. Morooka

Countries citing papers authored by Lauri Himanen

Since Specialization

Citations

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

Fields of papers citing papers by Lauri Himanen

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lauri Himanen

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

All Works

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12 of 12 papers shown

1.

Himanen, Lauri, et al.. (2025). Automated identification of bulk structures, two-dimensional materials, and interfaces using symmetry-based clustering. npj Computational Materials. 11(1).

2.

Schumann, Julia, Hampus Näsström, Miriam Götte, et al.. (2025). Towards a new era for open and FAIR data in catalysis research – A catalysis plugin for NOMAD. ChemRxiv.

3.

Himanen, Lauri, et al.. (2023). Updates to the DScribe library: New descriptors and derivatives. The Journal of Chemical Physics. 158(23). 47 indexed citations

4.

Kühbach, Markus, Markus Scheidgen, Lauri Himanen, et al.. (2022). Development of a FAIR Data Management Infrastructure. Microscopy and Microanalysis. 28(S1). 2930–2932.

5.

Chen, Chi, Shyue Ping Ong, Logan Ward, & Lauri Himanen. (2020). materialsvirtuallab/megnet: v1.2.3. Zenodo (CERN European Organization for Nuclear Research).

6.

Himanen, Lauri, et al.. (2019). Database-driven high-throughput study of coating materials for hybrid perovskites. New Journal of Physics. 21(8). 83018–83018. 8 indexed citations

7.

Himanen, Lauri, et al.. (2019). 5th Anniversary Article: Data‐Driven Materials Science: Status, Challenges, and Perspectives (Adv. Sci. 21/2019). Advanced Science. 6(21). 3 indexed citations

8.

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 →

9.

Liu, J., Li Jin, Zhijun Jiang, et al.. (2018). Understanding doped perovskite ferroelectrics with defective dipole model. The Journal of Chemical Physics. 149(24). 244122–244122. 18 indexed citations

10.

Himanen, Lauri, Patrick Rinke, & Adam S. Foster. (2018). Materials structure genealogy and high-throughput topological classification of surfaces and 2D materials. npj Computational Materials. 4(1). 9 indexed citations

11.

Morooka, Eiaki V., et al.. (2018). Machine learning hydrogen adsorption on nanoclusters through structural descriptors. npj Computational Materials. 4(1). 202 indexed citations

12.

Hynninen, Teemu, et al.. (2015). An object oriented Python interface for atomistic simulations. Computer Physics Communications. 198. 230–237. 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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