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5th Anniversary Article: Data‐Driven Materials Science: Status, Challenges, and Perspectives (Adv. Sci. 21/2019)

Data‐driven science is heralded as the new paradigm in materials science. Data infrastructures store vast amounts of materials data. Machine learning algorithms systematically extract knowledge from materials data streams to discover new materials for future technologies and the well‐being of societ...

Täydet tiedot

Tallennettuna:
Bibliografiset tiedot
Julkaisussa:Adv Sci (Weinh)
Päätekijät: Himanen, Lauri, Geurts, Amber, Foster, Adam Stuart, Rinke, Patrick
Aineistotyyppi: Artigo
Kieli:Inglês
Julkaistu: John Wiley and Sons Inc. 2019
Aiheet:
Linkit:https://ncbi.nlm.nih.gov/pmc/articles/PMC6839620/
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/advs.201970125
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