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.

中文翻译：

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使用X射线射线照相术和机器学习技术在金属合金中进行晶体成核。

通过同步加速器X射线射线照相技术在原位研究了各种条件下凝固的Al-Cu合金的结晶，并使用经过机器学习训练的计算机视觉算法对数据进行了分析。对于数千个独立的晶体，自动测量了冷却速率和溶质浓度对成核过冷，晶体形成速率和晶体生长速率的影响，这是无法手动实现的。成核过冷分布证实了外在晶粒细化剂的效率，并为广泛假定的异质成核的自由生长模型提供了支持。我们表明结晶发生在与溶质抑制成核区相关的时间和空间爆发。