Additive manufacturing promises a major transformation of the production of high economic value metallic materials, enabling innovative, geometrically complex designs with minimal material waste. The overarching challenge is to design alloys that are compatible with the unique additive processing conditions while maintaining material properties sufficient for the challenging environments encountered in energy, space, and nuclear applications. Here we describe a class of high strength, defect-resistant 3D printable superalloys containing approximately equal parts of Co and Ni along with Al, Cr, Ta and W that possess strengths in excess of 1.1 GPa in as-printed and post-processed forms and tensile ductilities of greater than 13% at room temperature. These alloys are amenable to crack-free 3D printing via electron beam melting (EBM) with preheat as well as selective laser melting (SLM) with limited preheat. Alloy design principles are described along with the structure and properties of EBM and SLM CoNi-base materials.

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Exposure to high heat can cause polymer matrix composites (PMC) to fail under mechanical loads easily sustained at room temperature. However, heat is removed and temperature reduced in PMCs by active cooling through an internal vascular network. Here we compare structural survival of PMCs under thermomechanical loading with and without active cooling. Microchannels are incorporated into autoclave-cured carbon fiber/epoxy composites using sacrificial fibers. Time-tofailure, material temperature, and heat removal rates are measured during simultaneous heating on one face (5-75 kW/m 2 ) and compressive loading (100-250 MPa). The effects of applied compressive load, heat flux, channel spacing, coolant flow rate, and channel distance from the heated surface are examined. Actively cooled composites containing 0.33% channel volume fraction survive without structural failure for longer than 30 minutes under 200 MPa compressive loading and 60 kW/m 2 heat flux. In dramatic comparison, non-cooled composites fail in less than a minute under the same loading conditions.

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Bayesian inference is employed to precisely evaluate single crystal elastic properties of novel c À c 0 Co-and CoNi-based superalloys from simple and non-destructive resonant ultrasound spectroscopy (RUS) measurements. Nine alloys from three Co-, CoNi-, and Ni-based alloy classes were evaluated in the fully aged condition, with one alloy per class also evaluated in the solution heat-treated condition. Comparisons are made between the elastic properties of the three alloy classes and among the alloys of a single class, with the following trends observed. A monotonic rise in the c 44 (shear) elastic constant by a total of 12 pct is observed between the three alloy classes as Co is substituted for Ni. Elastic anisotropy (A) is also increased, with a large majority of the nearly 13 pct increase occurring after Co becomes the dominant constituent. Together the five CoNi alloys, with Co:Ni ratios from 1:1 to 1.5:1, exhibited remarkably similar properties with an average A 1.8 pct greater than the Ni-based alloy CMSX-4. Custom code demonstrating a substantial advance over previously reported methods for RUS inversion is also reported here for the first time. CmdStan-RUS is built upon the open-source probabilistic programing language of Stan and formulates the inverse problem using Bayesian methods. Bayesian posterior distributions are efficiently computed with Hamiltonian Monte Carlo (HMC), while initial parameterization is randomly generated from weakly informative prior distributions. Remarkably robust convergence behavior is demonstrated across multiple independent HMC chains in spite of initial parameterization often very far from actual parameter values. Experimental procedures are substantially simplified by allowing any arbitrary misorientation between the specimen and crystal axes, as elastic properties and misorientation are estimated simultaneously.

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