The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Materials science with large-scale data and informatics: Unlocking new opportunities
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Cites
Commentary: The Materials Project: A materials genome approach to accelerating materials innovation
Jain, A., Ong, S. P., Hautier, G., Chen, W., Richards, W. D., Dacek, S., Cholia, S., Gunter, D., Skinner, D., Ceder, G., et al. (2013) · APL Materials · doi:10.1063/1.4812323 · Cited by 13,094
Self-citationPython Materials Genomics (pymatgen): A robust, open-source python library for materials analysis
Ong, S. P., Richards, W. D., Jain, A., Hautier, G., Kocher, M., Cholia, S., Gunter, D., Chevrier, V. L., Persson, K. A., & Ceder, G. (2013) · Computational Materials Science · doi:10.1016/j.commatsci.2012.10.028 · Cited by 4,534
Self-citationBelsky, A., Hellenbrandt, M., Karen, V. L., & Luksch, P. (2002) · Acta Crystallographica Section B Structural Science · doi:10.1107/s0108768102006948 · Cited by 1,379
Cited by
Machine learning for molecular and materials science
Butler, K. T., Davies, D. W., Cartwright, H., Isayev, O., & Walsh, A. (2018) · Nature · doi:10.1038/s41586-018-0337-2 · Cited by 4,968
Materials discovery and design using machine learning
Liu, Y., Zhao, T., Ju, W., & Shi, S. (2017) · Journal of Materiomics · doi:10.1016/j.jmat.2017.08.002 · Cited by 1,276
Unsupervised word embeddings capture latent knowledge from materials science literature
Tshitoyan, V., Dagdelen, J., Weston, L., Dunn, A., Rong, Z., Kononova, O., Persson, K. A., Ceder, G., & Jain, A. (2019) · Nature · doi:10.1038/s41586-019-1335-8 · Cited by 1,123
Self-citationFrom DFT to machine learning: recent approaches to materials science–a review
Schleder, G. R., Padilha, A. C. M., Acosta, C. M., Costa, M., & Fazzio, A. (2019) · Journal of Physics: Materials · doi:10.1088/2515-7639/ab084b · Cited by 852
Lookman, T., Balachandran, P. V., Xue, D., & Yuan, R. (2019) · npj Computational Materials · doi:10.1038/s41524-019-0153-8 · Cited by 832
Metadata
- Authors
- Hill, J., Mulholland, G., Persson, K., Seshadri, R., Wolverton, C., & Meredig, B.
- Venue
- MRS Bulletin
- Published
- 2016-05
- Volume
- 41
- Issue
- 5
- Pages
- 399-409
- ISSN
- 0883-7694 (ISSN-L)
- 1938-1425
- OpenAlex
- W2346180883
- Cited by
- 237
- References
- 3
- FWCI
- 14.26
- Type
- journal article
- Language
- en
- Open access
- hybrid
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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- CoChat. (2026). Citation check: Materials science with large-scale data and informatics: Unlocking new opportunities. https://app.cochat.ai/papers/10.1557/mrs.2016.93
- The paper
- Hill, J., Mulholland, G., Persson, K., Seshadri, R., Wolverton, C., & Meredig, B. (2016). Materials science with large-scale data and informatics: Unlocking new opportunities. MRS Bulletin. https://doi.org/10.1557/mrs.2016.93
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
