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Matminer: An open source toolkit for materials data mining

Open access
Ward, Logan, Dunn, Alexander, Faghaninia, Alireza, Zimmermann, Nils E.R., Bajaj, Saurabh, Wang, Qi, Montoya, Joseph, Chen, Jiming, Bystrom, Kyle, Dylla, Maxwell, Chard, Kyle, Asta, Mark, Persson, Kristin A., Snyder, G. Jeffrey, Foster, Ian, Jain, Anubhav·2018·Computational Materials Science
DOI 10.1016/j.commatsci.2018.05.018
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Abstract

Abstract As materials data sets grow in size and scope, the role of data mining and statistical learning methods to analyze these materials data sets and build predictive models is becoming more important. This manuscript introduces matminer, an open-source, Python-based software platform to facilitate data-driven methods of analyzing and predicting materials properties. Matminer provides modules for retrieving large data sets from external databases such as the Materials Project, Citrination, Materials Data Facility, and Materials Platform for Data Science. It also provides implementations for an extensive library of feature extraction routines developed by the materials community, with 47 featurization classes that can generate thousands of individual descriptors and combine them into mathematical functions. Finally, matminer provides a visualization module for producing interactive, shareable plots. These functions are designed in a way that integrates closely with machine learning and data analysis packages already developed and in use by the Python data science community. We explain the structure and logic of matminer, provide a description of its various modules, and showcase several examples of how matminer can be used to collect data, reproduce data mining studies reported in the literature, and test new methodologies.

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Metadata

Authors
Ward, L., Dunn, A., Faghaninia, A., Zimmermann, N. E. R., Bajaj, S., Wang, Q., Montoya, J., Chen, J., Bystrom, K., Dylla, M., Chard, K., Asta, M., Persson, K. A., Snyder, G. J., Foster, I., & Jain, A.
Venue
Computational Materials Science
Publisher
Elsevier BV
Published
2018-09
Volume
152
Pages
60-69
ISSN
0927-0256 (ISSN-L)
DOI
10.1016/j.commatsci.2018.05.018
OpenAlex
W2804431384
Cited by
1,069
References
9
FWCI
18.89
Type
journal article
Language
en
Open access
bronze
Licence
Funders
  • U.S. Department of Energy, Office of Basic Energy Sciences
  • Department of Commerce, National Institute of Standards and Technology as part of the Center for Hierarchical Material Design (70NANB14H012)
  • National Science Foundation as part of the Midwest Big Data Hub under NSF (1636950)
  • Department of Energy (DE-AC02-06CH11357)
  • U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, Materials Sciences and Engineering Division (DE-AC02-05-CH11231, KC23MP)
  • NSF, United States (1541450)
  • University of California, Berkeley College of Chemistry
  • NSF DMR (1334713, 1333335)
  • Office of Science of the U.S. Department of Energy (DE-AC02-05CH11231)

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CoChat. (2026). Citation check: Matminer: An open source toolkit for materials data mining. https://app.cochat.ai/papers/10.1016/j.commatsci.2018.05.018
The paper
Ward, L., Dunn, A., Faghaninia, A., Zimmermann, N. E. R., Bajaj, S., Wang, Q., Montoya, J., Chen, J., Bystrom, K., Dylla, M., Chard, K., Asta, M., Persson, K. A., Snyder, G. J., Foster, I., & Jain, A. (2018). Matminer: An open source toolkit for materials data mining. Computational Materials Science. https://doi.org/10.1016/j.commatsci.2018.05.018

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