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In oxide materials, an increase in oxygen vacancy concentration often results in lattice expansion, a phenomenon known as chemical expansion that can introduce detrimental stresses and lead to potential device failure. One factor often implicated in the chemical expansion of materials is the degree of localization of the multivalent cation electronic states. When an oxygen is removed from the lattice and a vacancy forms, it is believed that the two released electrons reduce multivalent cations and expand the lattice, with more localized cation states resulting in larger expansion. In this work, we computationally and experimentally studied the chemical expansion of two Pr-based perovskites that exhibit ultra-low chemical expansion, PrGa 1− x Mg x O 3− δ and BaPr 1− x Y x O 3− δ , and their parent compounds PrGaO 3− δ and BaPrO 3− δ . Using density functional theory, the degree of localization of the Pr-4f electrons was varied by adjusting the Hubbard U parameter. We find that the relationship between Pr-4f electron localization and chemical expansion exhibits more complexity than previously established. This relationship depends on the nature of the states filled by the two electrons, which may not necessarily involve the reduction of Pr. Fmore »′-center defects can form if the reduction of Pr is unfavorable, leading to smaller chemical expansions. If hole states are present in the material, the states filled by the electrons can be Pr-4f and/or O-2p hole states depending on the degree of Pr-4f localization. The O-2p holes are more delocalized than the Pr-4f holes, resulting in smaller chemical expansions when the O-2p holes are filled. X-ray photoelectron spectroscopy reveals low concentrations of Pr 4+ in PrGa 0.9 Mg 0.1 O 3− δ and BaPr 0.9 Y 0.1 O 3− δ , supporting the possible role of O-2p holes in the low chemical expansions exhibited by these materials. This work highlights the non-trivial effects of electron localization on chemical expansion, particularly when hole states are present, pointing to design strategies to tune the chemical expansion of materials.« less

While machine learning has emerged in recent years as a useful tool for the rapid prediction of materials properties, generating sufficient data to reliably train models without overfitting is often impractical. Towards overcoming this limitation, we present a general framework for leveraging complementary information across different models and datasets for accurate prediction of data-scarce materials properties. Our approach, based on a machine learning paradigm called mixture of experts, outperforms pairwise transfer learning on 14 of 19 materials property regression tasks, performing comparably on four of the remaining five. The approach is interpretable, model-agnostic, and scalable to combining an arbitrary number of pre-trained models and datasets to any downstream property prediction task. We anticipate the performance of our framework will further improve as better model architectures, new pre-training tasks, and larger materials datasets are developed by the community.

The discovery of unconventional superconductivity in magic-angle twisted bilayer graphene (tBLG) supported the twist-angle-induced flat band structure predictions made a decade earlier. Numerous physical properties have since been linked to the interlayer twist angle using the flat band prediction as a guideline. However, some key observations like the nematic phase and striped charge order behind the superconductivity are missing in this initial model. Here we show that a thermodynamically stable large out-of-plane displacement, or corrugation of the bilayer, induced by the interlayer twist, demonstrates partially filled states of the flat band structure, accompanied by a broken symmetry, in the magic-angle regime and the presence of symmetry breaking associated with the superconductivity in tBLG. The distinction between low and high corrugation can also explain the observed evolution of the vibrational spectra of tBLG as a function of twist angle. Our observation that large out-of-plane deformation modes enable partial filling of states near the Fermi energy may lead to a strategy for offsetting the effects of disorder in the local twist angle, which suppresses unconventional superconductivity and correlated insulator behavior in magic-angle tBLG.

Germanium telluride is a high performing thermoelectric material that additionally serves as a base for alloys such as GeTe–AgSbTe 2 and GeTe–PbTe. Such performance motivates exploration of other GeTe alloys in order understand the impact of site substitution on electron and phonon transport. In this work, we consider the root causes of the high thermoelectric performance material Ge 1− x Mn x Te. Along this alloy line, the crystal structure, electronic band structure, and electron and phonon scattering all depend heavily on the Mn content. Structural analysis of special quasirandom alloy structures indicate the thermodynamic stability of the rock salt phase over the rhombohedral phase with increased Mn incorporation. Effective band structure calculations indicate band convergence, the emergence of new valence band maxima, and strong smearing at the band edge with increased Mn content in both phases. High temperature measurements on bulk polycrystalline samples show a reduction in hole mobility and a dramatic increase in effective mass with respect to increasing Mn content. In contrast, synthesis as a function of tellurium chemical potential does not significantly impact electronic properties. Thermal conductivity shows a minimum near the rhombohedral to cubic phase transition, while the Mn Ge point defect scattering is weakmore »as indicated by the low K L dependence on the Ge–Mn fraction (Fig. 10). From this work, alloys near this phase transition show optimal performance due to low thermal conductivity, moderate effective mass, and low scattering rates compared to Mn-rich compositions.« less