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“…Further combining this effect with the preferred growth orientation and grain boundary segregation stabilizing the surrounding nanostructure provides an explanation for the abnormal grain growth event, which is consistent with the behavior of other nanocrystalline alloys containing solute clusters at grain boundaries [33,60] and heterogeneous grain boundary segregation. [38,61] Beyond the metastable region, the presence of large Au clusters results in destabilization of grain boundaries, exacerbating grain growth and promoting nanophase separation as observed previously in these materials [54] and now captured in the LMC models.…”
Section: Microstructural Evolution In the Presence Of Solute Clusteringmentioning
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“…Further combining this effect with the preferred growth orientation and grain boundary segregation stabilizing the surrounding nanostructure provides an explanation for the abnormal grain growth event, which is consistent with the behavior of other nanocrystalline alloys containing solute clusters at grain boundaries [33,60] and heterogeneous grain boundary segregation. [38,61] Beyond the metastable region, the presence of large Au clusters results in destabilization of grain boundaries, exacerbating grain growth and promoting nanophase separation as observed previously in these materials [54] and now captured in the LMC models.…”
Section: Microstructural Evolution In the Presence Of Solute Clusteringmentioning
“…[27] Theoretical formalisms further parameterized to capture the energetics of grain boundaries have been employed in mapping stable nanocrystalline configurations in binary alloys [9,13,[28][29][30] and extended to address competing phases such as solid solutions and ordered compounds. [11,30,31] Guided by thermodynamic predictions, stable nanocrystalline phases are being realized in a myriad of W, [32] Cu, [6,33,34] Fe, [35,36] Ni, [37,38] Pt, [2,39] Pd, [40] and Al [41] alloys and driving extraordinary advances in the design, processing, and technological applications of bulk nanocrystalline materials.…”
Section: Introductionmentioning
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“…Through this type of cross-correlation method, we increase our confidence of the GB identification process by ML in the experimental APT data because the ML generated images can be directly compared to an independent means of microscopy imaging. The details of this cross-correlation method and sample preparation of the Ni-P sample are found in [13,99].…”
Section: Grain Boundary Specific Segregationmentioning