Crystal nucleation in metallic alloys using x-ray radiography and machine learning | Zendy

Enzo Liotti | Zendy; Carlos Arteta | Zendy; Andrew Zisserman | Zendy; Andrew Lui | Zendy; Victor Lempitsky | Zendy; Patrick S. Grant | Zendy

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Crystal nucleation in metallic alloys using x-ray radiography and machine learning

Author(s) -

Enzo Liotti,

Carlos Arteta,

Andrew Zisserman,

Andrew Lui,

Victor Lempitsky,

Patrick S. Grant

Publication year - 2018

Publication title -

science advances

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 5.928

H-Index - 146

ISSN - 2375-2548

DOI - 10.1126/sciadv.aar4004

Subject(s) - radiography , nucleation , x ray , synchrotron , crystal (programming language) , materials science , alloy , metal , synchrotron radiation , crystallography , computer science , optics , metallurgy , medicine , physics , chemistry , radiology , programming language , thermodynamics

The crystallization of solidifying Al-Cu alloys over a wide range of conditions was studied in situ by synchrotron x-ray radiography, and the data were analyzed using a computer vision algorithm trained using machine learning. The effect of cooling rate and solute concentration on nucleation undercooling, crystal formation rate, and crystal growth rate was measured automatically for thousands of separate crystals, which was impossible to achieve manually. Nucleation undercooling distributions confirmed the efficiency of extrinsic grain refiners and gave support to the widely assumed free growth model of heterogeneous nucleation. We show that crystallization occurred in temporal and spatial bursts associated with a solute-suppressed nucleation zone.

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