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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Unlocking the NaCl-AlCl3 phase diagram for low-cost, long-duration Na-Al batteries
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A modern reappraisal of the U-Zr phase diagram
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Efficient Phase Diagram Sampling by Active Learning
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Phase Diagram and Conductivity of Zn(TFSI)(2)-H2O Electrolytes
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Phase Diagrams of Alloys and Their Hydrides via On-Lattice Graph Neural Networks and Limited Training Data
Efficient prediction of sampling-intensive thermodynamic properties is needed to evaluate material performance and permit high-throughput materials modeling for a diverse array of technology applications. To alleviate the prohibitive computational expense of high-throughput configurational sampling with density functional theory (DFT), surrogate modeling strategies like cluster expansion are many orders of magnitude more efficient but can be difficult to construct in systems with high compositional complexity. We therefore employ minimal-complexity graph neural network models that accurately predict and can even extrapolate to out-of-train distribution formation energies of DFT-relaxed structures from an ideal (unrelaxed) crystallographic representation. This enables the large-scale sampling necessary for various thermodynamic property predictions that may otherwise be intractable and can be achieved with small training data sets. Two exemplars, optimizing the thermodynamic stability of low-density high-entropy alloys and modulating the plateau pressure of hydrogen in metal alloys, demonstrate the power of this approach, which can be extended to a variety of materials discovery and modeling problems.
A refined phase diagram of the tert -butanol–water system and implications on lyophilization process optimization of pharmaceuticals
In TBA–water mixtures, using DSC and XRD, the eutectic temperature (-8 °C) and composition (22.5% w/w TBA) were determined.
Properties and phase diagram of (H[subscript 2]S)[subscript 2]H[subscript 2]
Abstract not provided
Néel-type antiferromagnetic order and magnetic field–temperature phase diagram in the spin-1/2 rare-earth honeycomb compound YbCl 3
Most of the searches for Kitaev materials deal with 4 d / 5 d magnets with spin-orbit-coupled J = 1 / 2 local moments such as iridates and α - RuCl 3 . Here we propose the monoclinic YbCl 3 with a Yb 3 + honeycomb lattice for the exploration of Kitaev physics. We perform thermodynamic, a c susceptibility, angle-dependent magnetic torque, and neutron diffraction measurements on YbCl 3 single crystal. We find that the Yb 3 + ion exhibits a Kramers doublet ground state that gives rise to an effective spin J eff = 1 / 2 local moment. Additionally, the compound exhibits short-range magnetic order below 1.20 K, followed by a long-range Néel-type antiferromagnetic order at 0.60 K, below which the ordered Yb 3 + spins lie in the a c plane with an angle of 16(11) ° away from the a axis. These orders can be suppressed by in-plane and out-of-plane magnetic fields at around 6 and 10 T, respectively. Moreover, the Néel temperature varies nonmonotonically under the out-of-plane magnetic fields, suggesting a reduced spin dimensionality. Finally, together with the strong in-plane magnetic anisotropy and the reduced order moment 0.8(1) μ B at 0.25 K, all indicate that YbCl 3 could be a two-dimensional spin system to proximate the Kitaev physics.
Evolution of lattice, spin, and charge properties across the phase diagram of FeSe 1 − x S x
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Evolution of plasmon excitations across the phase diagram of the cuprate superconductor La 2 − x Sr x CuO 4
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Fe substitution in URu 2 Si 2 : Singlet magnetism in an extended Doniach phase diagram
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Generic Mott-Hubbard phase diagram for extended Hubbard models without Umklapp scattering
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Chiral spin liquid and quantum phase diagram of spin- 1 2 J 1 − J 2 − J χ model on the square lattice
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Tunably polarized driving light controls the phase diagram of one-dimensional quasicrystals and two-dimensional quantum Hall matter
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