Access to this dataset is subject to the following terms:
If you use this dataset please add this citation to your publication:
Fang, Ren; Ward, Logan; Williams, Travis; Laws, Kevin J.; Wolverton, Christopher; Hattrick-Simpers, Jason; Mehta, Apurva, "Accelerated Discovery of Metallic Glasses through Iteration of Machine Learning and High-Throughput Experiments," 2018, http://dx.doi.org/doi:10.18126/M2B06M
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DC FieldValueLanguage
dc.contributor.authorFang, Ren-
dc.contributor.authorWard, Logan-
dc.contributor.authorWilliams, Travis-
dc.contributor.authorLaws, Kevin J.-
dc.contributor.authorWolverton, Christopher-
dc.contributor.authorHattrick-Simpers, Jason-
dc.contributor.authorMehta, Apurva-
dc.date.accessioned2018-02-18T03:38:58Z-
dc.date.available2018-02-18T03:38:58Z-
dc.date.issued2018-02-16-
dc.identifier.urihttp://dx.doi.org/doi:10.18126/M2B06M-
dc.publisherMaterials Data Facilityen_US
dc.titleAccelerated Discovery of Metallic Glasses through Iteration of Machine Learning and High-Throughput Experimentsen_US
globus.shared_endpoint.name82f1b5c6-6e9b-11e5-ba47-22000b92c6ec-
globus.shared_endpoint.path/published/publication_992/-
datacite.creator.affiliationSLAC National Accelerator Laboratoryen_US
datacite.creator.affiliationUniversity of Chicagoen_US
datacite.creator.affiliationUniversity of South Carolinaen_US
datacite.creator.affiliationUniversity of New South Walesen_US
datacite.creator.affiliationNorthwestern Universityen_US
datacite.creator.affiliationNational Institute of Standards and Technologyen_US
datacite.creator.affiliationSLAC National Accelerator Laboratoryen_US
datacite.contributor.ContactPersonLogan Warden_US
mdf-base.funding_detailsAdvanced Manufacturing Office of the Department of Energy under FWP-100250en_US
mdf-base.funding_detailsCenter for Hierarchical Materials Design (CHiMaD), Award 70NANB14H012 from the U.S. Department of Commerce, National Institute of Standards and Technologyen_US
mdf-base.funding_detailsNSF IGERT Grant #1250052en_US
mdf-base.funding_detailsX-ray diffraction data was collected at the Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Laboratory, which is supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences under Contract No. DE-AC02-76SF00515en_US
mdf-base.funding_detailsWe used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation grant number ACI-1548562. Specifically, we used Jetstream at the Texas Advanced Computing Center through allocation CIE170012en_US
mdf-base.linkshttps://github.com/fang-ren/Discover_MG_CoVZren_US
mdf-base.linkshttps://citrination.com/datasets/155250en_US
mdf-base.linkshttps://citrination.com/datasets/155251en_US
mdf-base.linkshttps://citrination.com/datasets/155252en_US
mdf-base.material_typeMetallic Glassen_US
mdf-base.structureAmorphousen_US
mdf-base.material_classMetal alloysen_US
mdf-base.data_acquisition_methodX-ray diffractionen_US
mdf-base.data_acquisition_locationSLACen_US
mdf-base.primary_productX-ray diffraction dataen_US
mdf-base.descriptionThis repository contains data supporting the manuscript: "Accelerated Discovery of Metallic Glasses through Iteration of Machine Learning and High-Throughput Experiments." It includes the raw x-ray diffraction measurements and scripts used to process that data. This dataset also contains the scripts necessary to build and test the machine learning models used in the work, and the output files generated from each of those scripts.en_US
Appears in Collections:MDF Open



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