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

ABSTRACT: 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.

SUBMITTER: Liotti E

PROVIDER: S-EPMC5898834 | biostudies-other | 2018 Apr

REPOSITORIES: biostudies-other

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

Liotti Enzo E Arteta Carlos C Zisserman Andrew A Lui Andrew A Lempitsky Victor V Grant Patrick S PS

Science advances 20180413 4

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 co ...[more]

PMID: 29662954

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