Neutron diffraction detects intrinsic chemical short-range order in CoCrNi via a diffuse peak at 1.85 Å^{-1}, enhanced by aging, with simulations and SANS confirming nanoscale Ni-rich domains.
De Fontaine, Configurational Thermodynamics of Solid Solutions, in: 1979: pp
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Hybrid phase-field and attention-based deep learning model predicts microstructure evolution in ternary alloys up to 400 timesteps with generalization to new compositions.
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Direct Observation of Chemical Short-Range Order in CoCrNi Alloy Using Neutron Diffraction
Neutron diffraction detects intrinsic chemical short-range order in CoCrNi via a diffuse peak at 1.85 Å^{-1}, enhanced by aging, with simulations and SANS confirming nanoscale Ni-rich domains.
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Bridging Phase-Field Model and Deep Learning for Predicting 2D and 3D Microstructure Evolution in Ternary Alloys
Hybrid phase-field and attention-based deep learning model predicts microstructure evolution in ternary alloys up to 400 timesteps with generalization to new compositions.