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Deep learning approach for an interface structure analysis with a large statistical noise in neutron...

Deep learning approach for an interface structure analysis with a large statistical noise in neutron...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_d168e5a353f1460c89ea1c0ecd10bf71

Deep learning approach for an interface structure analysis with a large statistical noise in neutron reflectometry

About this item

Full title

Deep learning approach for an interface structure analysis with a large statistical noise in neutron reflectometry

Publisher

London: Nature Publishing Group UK

Journal title

Scientific reports, 2021-11, Vol.11 (1), p.22711-22711, Article 22711

Language

English

Formats

Publication information

Publisher

London: Nature Publishing Group UK

More information

Scope and Contents

Contents

Neutron reflectometry (NR) allows us to probe into the structure of the surfaces and interfaces of various materials such as soft matters and magnetic thin films with a contrast mechanism dependent on isotopic and magnetic states. The neutron beam flux is relatively low compared to that of other sources such as synchrotron radiation; therefore, the...

Alternative Titles

Full title

Deep learning approach for an interface structure analysis with a large statistical noise in neutron reflectometry

Authors, Artists and Contributors

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_d168e5a353f1460c89ea1c0ecd10bf71

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_d168e5a353f1460c89ea1c0ecd10bf71

Other Identifiers

ISSN

2045-2322

E-ISSN

2045-2322

DOI

10.1038/s41598-021-02085-6

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