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  1. Combined experimental and density functional theory (DFT) study of Pr0.75Gd0.25ScGe and its hydride (Pr0.75Gd0.25ScGeH) reveals intricacies of composition-structure-property relationships in those distinctly layered compounds. Hydrogenation of the intermetallic parent, crystalizing in a tetragonal CeScSi-type structure, leads to an anisotropic volume expansion, that is, a(=b) lattice parameter decreases while the lattice expands along the c direction, yielding a net increase of cell volume. DFT calculations predict an antiparallel coupling of localized Gd and Pr magnetic moments in both materials at the ground state. While experiments corroborate this for the parent compound, there is no conclusive experimental proof for the hydride, where Pr moments do not order down to 3 K. DFT results also reveal that rare-earth – hydrogen interactions reduce spin-polarization of the Pr and Gd 5d and Sc 3d states at the Fermi energy, disrupt indirect exchange interactions mediated by conduction electrons, dramatically reduce the magnetic ordering temperature, and open a pseudo-gap in the majority-spin channel. Both experiments and theory show evidence of Kondo-like behavior in the hydride in the absence of an applied magnetic field, whereas increasing the field promotes magnetic ordering and suppresses Kondo-like behavior. 
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    Free, publicly-accessible full text available December 1, 2024
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  4. Abstract

    The design of alloys for use in gas turbine engine blades is a complex task that involves balancing multiple objectives and constraints. Candidate alloys must be ductile at room temperature and retain their yield strength at high temperatures, as well as possess low density, high thermal conductivity, narrow solidification range, high solidus temperature, and a small linear thermal expansion coefficient. Traditional Integrated Computational Materials Engineering (ICME) methods are not sufficient for exploring combinatorially-vast alloy design spaces, optimizing for multiple objectives, nor ensuring that multiple constraints are met. In this work, we propose an approach for solving a constrained multi-objective materials design problem over a large composition space, specifically focusing on the Mo-Nb-Ti-V-W system as a representative Multi-Principal Element Alloy (MPEA) for potential use in next-generation gas turbine blades. Our approach is able to learn and adapt to unknown constraints in the design space, making decisions about the best course of action at each stage of the process. As a result, we identify 21 Pareto-optimal alloys that satisfy all constraints. Our proposed framework is significantly more efficient and faster than a brute force approach.

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  5. Free, publicly-accessible full text available July 25, 2024