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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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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Electronic Structure, Spectroscopy and Correlation Effects in Novel Materials

This project was targeted on electronic structure, spectroscopic studies, and correlation effects in a variety of novel materials of great current interest. Spectroscopies resolved highly in momentum, energy or spatial dimensions are playing a key role in unraveling the nature of the ground state and excitation properties in wide classes of novel materials. The seminal insights thus obtained are of critical importance not only for answering some of the fundamental questions facing condensed matter physics and materials science today, but also for understanding and thus helping to design and develop new materials with desirable properties, which will continue to be the key to the survival of mankind and its energy needs as a technological society long into the future. However, spectroscopies do not provide a direct map of electronic states, but act as a very complex ‘filter’ or ‘mapping’ of the underlying spectrum. This connection between the electronic states and measured spectra—called the ‘matrix element effect’—is in general an extremely complex function of the phase space of the experiment (e.g. energy/polarization of photons in photoemission), presenting both a challenge and an opportunity. So motivated, this project pursued techniques for realistic treatment of electronic spectra of a wide variety of materials, which served as a prelude to formulating and implementing methodologies for making direct connection with various spectroscopies such as ARPES, STS/STM, and inelastic light scattering. Specific systems are topological materials, including 2D ultrathin films beyond graphene, novel superconductors, and nanocrystals, among others. Our goal was to exploit the strengths of various spectroscopies to piece together the most complete picture of electronic states in systems of current interest, enabling direct and sharpened confrontations with theoretical models, and also to help advance the reach of various spectroscopies.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Quantum many-body simulations of the two-dimensional Fermi-Hubbard model in ultracold optical lattices

Understanding quantum many-body states of correlated electrons is one main theme in modern condensed-matter physics. Given that the Fermi-Hubbard model, the prototype of correlated electrons, was recently realized in ultracold optical lattices, it is highly desirable to have controlled numerical methodology to provide precise finite-temperature results upon doping to directly compare with experiments. Here, we demonstrate the exponential tensor renormalization group (XTRG) algorithm [Chen et al., Phys. Rev. X 8, 031082 (2018)], complemented by independent determinant quantum Monte Carlo, offers a powerful combination of tools for this purpose. XTRG provides full and accurate access to the density matrix and thus various spin and charge correlations, down to an unprecedented low temperature of a few percent of the tunneling energy. Finally, we observe excellent agreement with ultracold fermion measurements at both half filling and finite doping, including the sign-reversal behavior in spin correlations due to formation of magnetic polarons, and the attractive hole-doublon and repulsive hole-hole pairs that are responsible for the peculiar bunching and antibunching behaviors of the antimoments.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Scanning ultrafast electron microscopy reveals photovoltage dynamics at a deeply buried $p^- \mathrm{Si/SiO_2}$ interface

The understanding and control of charge carrier interactions with defects at buried insulator/semiconductor interfaces is essential for achieving optimum performance in modern electronics. In this work, we report on the use of scanning ultrafast electron microscopy (SUEM) to remotely probe the dynamics of excited carriers at a Si surface buried below a thick thermal oxide. Our measurements illustrate a previously unidentified SUEM contrast mechanism, whereby optical modulation of the space-charge field in the semiconductor modulates the electric field in the thick oxide, thus affecting its secondary electron yield. By analyzing the SUEM contrast as a function of time and laser fluence we demonstrate the diffusion mediated capture of excited carriers by interfacial traps.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

An Ab Initio Molecular Dynamics Study of Key Thermodynamic Input Parameters for Computer Simulation of U-6Nb Solidification

The key to metallic fuel development is the fabrication of uranium metal and alloys into fuel forms. U-Nb alloys are one of the best candidates for a metallic fuel alloy with high-temperature strength sufficient to support the core, acceptable nuclear properties, good fabricability, and compatibility with usable coolant media. Melt processing has been a key component of the metallic fuel cycle, and process models require thermophysical parameters at elevated temperatures, particularly above the melting temperatures, regarding which experimental data are scarce, for accurate simulations and process development. By means of ab initio density-functional theory (DFT) quantum molecular dynamics (QMD), we have calculated the main thermophysical parameters—the density, thermal expansion coefficient, specific heat, thermal conductivity, melting temperature, latent heat of fusion, and viscosity—used in the modeling of the U-6 wt.% Nb alloy casting. The melting temperature of the U-6 wt.% Nb alloy at ambient pressure is obtained by means of QMD simulations using the Z-method. The ambient volume change and latent heat of melting of U-6 wt.% Nb are also derived from QMD simulations in conjunction with analytical fitting for the energy and pressure. The thermal conductivity for the solid U-Nb alloy is calculated from the semi-classical Boltzmann transport equation combined with an estimate of the electron relaxation time obtained from DFT simulations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Microwave Microscopy and Its Applications

Understanding the nanoscale electrodynamic properties of a material at microwave frequencies is of great interest for materials science, condensed matter physics, device engineering, and biology. With specialized probes, sensitive detection electronics, and improved scanning platforms, microwave microscopy has become an important tool for cutting-edge materials research in the past decade. In this article, we review the basic components and data interpretation of microwave imaging and its broad range of applications. In addition to the general-purpose mapping of permittivity and conductivity, microwave microscopy is now exploited to perform quantitative measurements on semiconductor devices, photosensitive materials, ferroelectric domains and domain walls, and acoustic-wave systems. Implementation of the technique in low-temperature and high-magnetic-field chambers has also led to major discoveries in quantum materials with strong correlation and topological order. We conclude the review with an outlook of the ultimate resolution, operation frequency, and future industrial and academic applications of near-field microwave microscopy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Analytic fits to atom-in-jellium shear modulus predictions

Fits to AJ shear modulus calculations from ρ0 to the limit of the corresponding AJ EOS table (usually 1000 ρ0), adjusted to reproduce STP shear modulus where possible. Fitting minimized the fractional difference, so low-pressure points would be reproduced accurately despite the wide-ranging tabulation. AJ calculations were at T=0. Isochoric variation G(T) has been small for all cases spot-tested so far, and may have either sign. The fitted equation usually matches the AJ data to within a few percent. Between numerical noise in the AJ calculation and probably-physical structure not captured by the equation, the deviation could be up to 20% in some places in most models, and 30% in a few. AJ does not capture structural phase transitions or phases stabilized by directional bonds, where the shear modulus may vary by a greater amount. Where possible, STP ρ,G were used as parameters, and low pressure AJ points were de-weighted or removed if necessary. Otherwise, such as where AJ fails to capture solid phases with a significantly different shear modulus, the AJ data were fitted as far down in pressure as possible, G0 was also fitted if necessary, and ρ0 was also adjusted if needed to keep G0>0. The resulting models are not intended for use at low pressure, though some are probably adequate for practical purposes

36 MATERIALS SCIENCE↗
DOE OSTI2021

Strain-stabilized superconductivity

Superconductivity is among the most fascinating and well-studied quantum states of matter. Despite over 100 years of research, a detailed understanding of how features of the normal-state electronic structure determine superconducting properties has remained elusive. For instance, the ability to deterministically enhance the superconducting transition temperature by design, rather than by serendipity, has been a long sought-after goal in condensed matter physics and materials science, but achieving this objective may require new tools, techniques and approaches. Here, we report the transmutation of a normal metal into a superconductor through the application of epitaxial strain. We demonstrate that synthesizing RuO 2 thin films on (110)-oriented TiO 2 substrates enhances the density of states near the Fermi level, which stabilizes superconductivity under strain, and suggests that a promising strategy to create new transition-metal superconductors is to apply judiciously chosen anisotropic strains that redistribute carriers within the low-energy manifold of d orbitals.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Quantum phase transition from superconducting to insulating-like state in a pressurized cuprate superconductor

Copper oxide superconductors continue to fascinate the communities of condensed matter physics and material sciences because they host the highest ambient-pressure superconducting transition temperature and unconventional electronic behaviour that are not fully explained. Searching for universal links between the superconducting state and its normal metallic state is believed to be an effective approach to elucidate the underlying mechanism of superconductivity. One of the common expectations for copper oxide superconductors is that a metallic phase will appear after the superconductivity is entirely suppressed by chemical doping or the application of a magnetic field9. Here we report the first observation of a quantum phase transition from a superconducting state to an insulating-like state as a function of pressure in Bi 2 Sr 2 CaCu 2 O 8+δ (Bi2212) superconductors with two CuO 2 planes in a unit cell for doping below, at and above a level that achieves the highest transition temperature. We also find the same phenomenon in related compounds with a single CuO 2 plane as well as three CuO 2 planes in a unit cell. This apparently universal phenomenon poses a challenge for achieving a unified understanding of the mechanism of high-temperature superconductivity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Machine Learning Reveals Memory of the Parent Phases in Ferroelectric Relaxors Ba(Ti$_{1-x}$,Zr x )O 3

Machine learning has been establishing its potential in multiple areas of condensed matter physics and materials science. Here, in this work, an unsupervised machine learning workflow is developed and used within a framework of first-principles-based atomistic simulations to investigate phases, phase transitions, and their structural origins in ferroelectric relaxors, Ba(Ti 1-x ,Zr x )O 3 . The applicability of the workflow is first demonstrated to identify phases and phase transitions in the parent compound, a prototypical ferroelectric BaTiO 3 . Then the workflow is applied for Ba(Ti 1-x ,Zrx)O 3 with x ≤ 0.25 to reveal i) that some of the compounds bear a subtle memory of BaTiO 3 phases beyond the point of the pinched phase transition, which could contribute to their enhanced electromechanical response; ii) the existence of peculiar phases with delocalized precursors of nanodomains—likely candidates for the controversial polar nanoregions; and iii) nanodomain phases for the largest concentrations of x.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Dislocation-position fluctuations in solid 4He as collective variables in a quantum crystal

Abstract Quantum behavior at mesoscopic length scales is of significant interest, both from a fundamental-physics standpoint, as well as in the context of technological advances. In this light, the description of collective variables comprising large numbers of atoms, but nevertheless displaying non-classical behavior, is a fundamental problem. Here, we show that an effective-Hamiltonian approach for such variables, as has been applied to describe the quantum behavior of coupled qubit/oscillator systems, can also be very useful in understanding intrinsic behavior of quantum materials. We consider lattice dislocations – naturally occurring mesoscopic line defects in crystals – in the prototypical bosonic quantum crystal, solid 4 He. For this purpose, we map fully atomistic quantum simulations onto effective one-dimensional Hamiltonians in which the collective dislocation-position variables are represented as interacting, massive quantum particles. The results provide quantitative understanding of several experimental observations in solid 4 He.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Machine learning magnetism classifiers from atomic coordinates

The determination of magnetic structure poses a long-standing challenge in condensed matter physics and materials science. Experimental techniques such as neutron diffraction are resource-limited and require complex structure refinement protocols, while computational approaches such as first-principles density functional theory (DFT) need additional semi-empirical correction, and reliable prediction is still largely limited to collinear magnetism. Here, we present a machine learning model that aims to classify the magnetic structure by inputting atomic coordinates containing transition metal and rare earth elements. By building a Euclidean equivariant neural network that preserves the crystallographic symmetry, the magnetic structure (ferromagnetic, antiferromagnetic, and nonmagnetic) and magnetic propagation vector (zero or non-zero) can be predicted with an average accuracy of 77.8% and 73.6%. In particular, a 91% accuracy is reached when predicting no magnetic ordering even if the structure contains magneticelement(s). Ourworkrepresents onestepforwardtosolvingthegrand challenge of full magnetic structure determination.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Designed metal-insulator transition in low-symmetry magnetic intermetallics

Compounds exhibiting half-metallic character and metal-insulator transitions draw considerable attention in condensed-matter and materials physics due to their potential use in spintronics. Here we show that specific electron doping plays a crucial role in tailoring thermodynamic, structural, electronic, and magnetic properties of materials derived from low-symmetry magnetic intermetallics, exemplified on triclinic Mn 4 Al 11 . Upon chemical doping of Al by Ge, we predict improved phase stability and adherence to a generalized “18-n rule” governing closed-shell configurations in intermetallic with narrow bandgaps. Validating experiments include measurements of phase stability and electronic transport properties of electron-doped Mn 4 Al 10 Ge that crystallizes in the Mn 4 Al 11 -type structure, confirming the bandgap opening as predicted by chemical analysis and density-functional theory. Here we also demonstrate theoretically that hydrostatic pressure enhances the predicted half-metallic gap in the up-spin channel, which leads to a ferrimagnetic-to-ferromagnetic transition driven by Mn-Mn charge ordering in the Mn 4 Al 11 parent. We have also discussed the generality of our approach in predicting the design of other classes of intermetallics including half and full Heusler compounds.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Nonequilibrium phonon tuning and mapping in few-layer graphene with infrared nanoscopy

Electron-phonon interactions are fundamentally important physical processes responsible for many key discoveries in condensed matter physics and material sciences. Herein, by exploiting the scattering-type scanning near-field optical microscope (s-SNOM) excited with a femtosecond infrared (IR) laser, we explored the strong coupling between IR phonons in few-layer graphene (FLG) with ultrahot electrons, which are heated up by the intense laser field enhanced by the s-SNOM tip. More specifically, we found that the intensity of the phonon resonance can be tuned systematically by varying the laser power that controls the electron temperature. Furthermore, the high spatial resolution of s-SNOM allows us to map the local phonon characteristics at sharp boundaries and nanostructures. Our results offer insights into the intriguing physics behind the electron-phonon interactions in nonequilibrium conditions and open a pathway for manipulating phonons with optical means.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Mesoscopic theory of defect ordering–disordering transitions in thin oxide films

Abstract Ordering of mobile defects in functional materials can give rise to fundamentally new phases possessing ferroic and multiferroic functionalities. Here we develop the Landau theory for strain induced ordering of defects (e.g. oxygen vacancies) in thin oxide films, considering both the ordering and wavelength of possible instabilities. Using derived analytical expressions for the energies of various defect-ordered states, we calculated and analyzed phase diagrams dependence on the film-substrate mismatch strain, concentration of defects, and Vegard coefficients. Obtained results open possibilities to create and control superstructures of ordered defects in thin oxide films by selecting the appropriate substrate and defect concentration.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

High-throughput ab initio design of atomic interfaces using InterMatch

Forming a hetero-interface is a materials-design strategy that can access an astronomically large phase space. However, the immense phase space necessitates a high-throughput approach for an optimal interface design. Here we introduce a high-throughput computational framework, InterMatch, for efficiently predicting charge transfer, strain, and superlattice structure of an interface by leveraging the databases of individual bulk materials. Specifically, the algorithm reads in the lattice vectors, density of states, and the stiffness tensors for each material in their isolated form from the Materials Project. From these bulk properties, InterMatch estimates the interfacial properties. We benchmark InterMatch predictions for the charge transfer against experimental measurements and supercell density-functional theory calculations. We then use InterMatch to predict promising interface candidates for doping transition metal dichalcogenide MoSe 2 . Finally, we explain experimental observation of factor of 10 variation in the supercell periodicity within a few microns in graphene/α-RuCl 3 by exploring low energy superlattice structures as a function of twist angle using InterMatch. We anticipate our open-source InterMatch algorithm accelerating and guiding ever-growing interfacial design efforts. Moreover, the interface database resulting from the InterMatch searches presented in this paper can be readily accessed online.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Uncovering multiscale structure-property correlations via active learning in scanning tunneling microscopy

Atomic arrangements and local sub-structures fundamentally influence emergent material functionalities. These structures are conventionally probed using spatially resolved studies and the property correlations are deciphered by a researcher based on sequential explorations, thereby limiting the efficiency and scope. Here we demonstrate a multi-scale Bayesian deep-learning based framework that automatically correlates material structure with its electronic properties using scanning tunneling microscopy (STM) measurements in real-time. Its predictions are used to autonomously direct exploration toward regions of the sample that optimize a given material property. This method is deployed on a low-temperature ultra-high vacuum STM to understand the structure-property relationship in a europium-based semimetal, EuZn 2 As 2 , a promising candidate relevant to magnetism-driven topological phenomena. The framework employs a sparse-sampling approach to efficiently construct the scalar-property space using minimal measurements, about 1–10% of the data required in standard hyperspectral methods. Moreover, we formulate the problem hierarchically across length scales, implementing autonomous workflow to locate mesoscopic and atomic structures that correspond to a target material property. This framework offers the choice to design scalar-property from the spectroscopic data to steer sample exploration. Our findings reveal correlations of the electronic properties unique to surface terminations, local defect density, and point defects.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Frustration and Atomic Ordering in a Monolayer Semiconductor Alloy

Frustrated interactions can lead to short-range ordering arising from incompatible interactions of fundamental physical quantities with the underlying lattice. The simplest example is the triangular lattice of spins with antiferromagnetic interactions, where the nearest-neighbor spin-spin interactions cannot simultaneously be energy minimized. In this work, we show that engineering frustrated interactions is a possible route for controlling structural and electronic phenomena in semiconductor alloys. Using aberration-corrected scanning transmission electron microscopy in conjunction with density functional theory calculations, we demonstrate atomic ordering in a two-dimensional semiconductor alloy as a result of the competition between geometrical constraints and nearest-neighbor interactions. Statistical analyses uncover the presence of short-range ordering in the lattice. In addition, we show how the induced ordering can be used as another degree of freedom to considerably modify the band gap of monolayer semiconductor alloys.

2-dimensional systems↗