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AI-enhanced X-ray diffraction analysis: towards real-time mineral phase identification and quantific...

AI-enhanced X-ray diffraction analysis: towards real-time mineral phase identification and quantific...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_2474f477571e4120ae387a577915c5e7

AI-enhanced X-ray diffraction analysis: towards real-time mineral phase identification and quantification

About this item

Full title

AI-enhanced X-ray diffraction analysis: towards real-time mineral phase identification and quantification

Author / Creator

Publisher

England: International Union of Crystallography

Journal title

IUCrJ, 2024-09, Vol.11 (Pt 5), p.647-648

Language

English

Formats

Publication information

Publisher

England: International Union of Crystallography

More information

Scope and Contents

Contents

The use of convolutional neural networks can revolutionize XRD analysis by significantly reducing processing times. Demonstration against synthetic and real mineral mixture data provide a first assessment of the accuracy of such methods.

Alternative Titles

Full title

AI-enhanced X-ray diffraction analysis: towards real-time mineral phase identification and quantification

Authors, Artists and Contributors

Author / Creator

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_2474f477571e4120ae387a577915c5e7

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_2474f477571e4120ae387a577915c5e7

Other Identifiers

ISSN

2052-2525

E-ISSN

2052-2525

DOI

10.1107/S2052252524008157

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