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Text mining facilitates materials discovery

Computer algorithms can be used to analyse text to find semantic relationships between words without human input. This method has now been adopted to identify unreported properties of materials in scientific papers.
  1. Olexandr Isayev

    1. Olexandr Isayev is in the Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA.

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The total number of materials that can potentially be made — sometimes referred to as materials space — is vast, because there are countless combinations of components and structures from which materials can be fabricated. The accumulation of experimental data that represent pockets of this space has created a foundation for the emerging field of materials informatics, which integrates high-throughput experiments, computations and data-driven methods into a tight feedback loop that enables rational materials design. Writing in Nature, Tshitoyan et al.1 report that knowledge of materials science ‘hidden’ in the text of published papers can be mined effectively by computers without any guidance from humans.

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Nature 571, 42-43 (2019)

doi: https://doi.org/10.1038/d41586-019-01978-x

References

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