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High-resolution Digital Image Correlation (HR-DIC) was performed on an Inconel 718 specimen, which was subjected to a heat treatment to form a fully solutionized system. In-situ measurements in the small strain regime were made through SEM imaging, followed by HR-DIC to extract quantitative representations of the strain and in-plane displacement induced by deformation events during plastic deformation. 

A nickel-based superalloy is examined during monotonic deformation at cryogenic temperatures, reaching as low as liquid helium temperature. A detailed multimodal analysis of the microstructure and plasticity is conducted to discern changes in deformation mechanisms and plastic deformation localization under cryogenic conditions. This study employs high-resolution digital image correlation to identify the deformation mechanisms and understand their influence on plastic deformation localization as the temperature varies. At cryogenic temperatures, unusual plastic deformation localization processes are observed, attributed to the competing activation of a range of deformation processes. Furthermore, a mechanism of slip delocalization, i.e., local plastic deformation homogenization through closely spaced slip, is noted at these extreme temperatures. Ultimately, the impact of the microstructure is identified across the temperature range, from room to cryogenic temperatures. 

Abstract This paper develops a Bayesian inference-based probabilistic crack nucleation model for the Ni-based superalloy René 88DT under fatigue loading. A data-driven, machine learning approach is developed, identifying underlying mechanisms driving crack nucleation. An experimental set of fatigue-loaded microstructures is characterized near crack nucleation sites using scanning electron microscopy and electron backscatter diffraction images for correlating the grain morphology and crystallography to the location of crack nucleation sites. A concurrent multiscale model, embedding experimental polycrystalline microstructural representative volume elements (RVEs) in a homogenized material, is developed for fatigue simulations. The RVE domain is modeled by a crystal plasticity finite element model. An anisotropic continuum plasticity model, obtained by homogenization of the crystal plasticity model, is used for the exterior domain. A Bayesian classification method is introduced to optimally select informative state variable predictors of crack nucleation. From this principal set of state variables, a simple scalar crack nucleation indicator is formulated. 

Refractory multiprincipal element alloys (MPEAs) are promising materials to meet the demands of aggressive structural applications, yet require fundamentally different avenues for accommodating plastic deformation in the body-centered cubic (bcc) variants of these alloys. We show a desirable combination of homogeneous plastic deformability and strength in the bcc MPEA MoNbTi, enabled by the rugged atomic environment through which dislocations must navigate. Our observations of dislocation motion and atomistic calculations unveil the unexpected dominance of nonscrew character dislocations and numerous slip planes for dislocation glide. This behavior lends credence to theories that explain the exceptional high temperature strength of similar alloys. Our results advance a defect-aware perspective to alloy design strategies for materials capable of performance across the temperature spectrum.