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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Structural Complexities in Sodium Ion Conductive Antiperovskite Revealed by Cryogenic Transmission Electron Microscopy

Here we use low-dose cryogenic transmission electron microscopy (cryo-TEM) to investigate the atomic-scale structure of antiperovskite Na 2 NH 2 BH 4 crystals by preserving the room-temperature cubic phase and carefully monitoring the electron dose. Via quantitative analysis of electron beam damage using selected area electron diffraction, we find cryogenic imaging provides 6-fold improvement in beam stability for this solid electrolyte. Cryo-TEM images obtained from flat crystals revealed the presence of a new, long-range-ordered supercell with a cubic phase. The supercell exhibits doubled unit cell dimensions of 9.4 Å × 9.4 Å as compared to the cubic lattice structure revealed by X-ray crystallography of 4.7 Å × 4.7 Å. The comparison between the experimental image and simulated potential map indicates the origin of the supercell is a vacancy ordering of sodium atoms. This work demonstrates the potential of using cryo-TEM imaging to study the atomic-scale structure of air- and electron-beam-sensitive antiperovskite-type solid electrolytes.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Microscopic and Macroscopic Characterization of Grain Boundary Energy and Strength in Silicon Carbide via Machine-Learning Techniques

Predicting the properties of grain boundaries poses a challenge because of the complex relationships between structural and chemical attributes both at the atomic and continuum scales. Grain boundary systems are typically characterized by parameters used to classify local atomic arrangements in order to extract features such as grain boundary energy or grain boundary strength. The present work utilizes a combination of high-throughput atomistic simulations, macroscopic and microscopic descriptors, and machine-learning techniques to characterize the energy and strength of silicon carbide grain boundaries. Additionally, a diverse data set of symmetric tilt and twist grain boundaries are described using macroscopic metrics such as misorientation, the alignment of critical low-index planes, and the Schmid factor, but also in terms of microscopic metrics, by quantifying the local atomic structure and chemistry at the interface. These descriptors are used to create random-forest regression models, allowing for their relative importance to the grain boundary energy and decohesion stress to be better understood. Results show that while the energetics of the grain boundary were best described using the microscopic descriptors, the ability of the macroscopic descriptors to reasonably predict grain boundaries with low energy suggests a link between the crystallographic orientation and the resultant atomic structure that forms at the grain boundary within this regime. For grain boundary strength, neither microscopic nor macroscopic descriptors were able to fully capture the response individually. However, when both descriptor sets were utilized, the decohesion stress of the grain boundary could be accurately predicted. These results highlight the importance of considering both macroscopic and microscopic factors when constructing constitutive models for grain boundary systems, which has significant implications for both understanding the fundamental mechanisms at work and the ability to bridge length scales.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Solving the structure of “single-atom” catalysts using machine learning – assisted XANES analysis

We show that "single-atom” catalysts (SACs) have demonstrated excellent activity and selectivity in challenging chemical transformations such as photocatalytic CO 2 reduction. For heterogeneous photocatalytic SAC systems, it is essential to obtain sufficient information of their structure at the atomic level in order to understand reaction mechanisms. In this work, a SAC was prepared by grafting a molecular cobalt catalyst on a light-absorbing carbon nitride surface. Due to the sensitivity of the X-ray absorption near edge structure (XANES) spectra to subtle variances in the Co SAC structure in reaction conditions, different machine learning (ML) methods, including principal component analysis, K-means clustering, and neural network (NN), were utilized for in situ Co XANES data analysis. As a result, we obtained quantitative structural information of the SAC nearest atomic environment thereby extending the NN-XANES approach previously demonstrated for nanoparticles and size-selective clusters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Cluster spin glass correlations and dynamics in Zn 0.5⁢ Mn 0.5⁢ Te

Here, we present a combined magnetometry, muon spin-relaxation (𝜇⁢SR), and neutron-scattering study of the insulating spin glass Zn 0.5 ⁢Mn 0.5 ⁢Te, for which magnetic Mn 2+ and nonmagnetic Zn 2+ ions are randomly distributed on a face-centered cubic lattice. The magnetometry and 𝜇⁢SR results confirm a spin freezing transition around 𝑇 𝑓 ≈ 23 K, with the spin-fluctuation rate decreasing gradually and somewhat inhomogeneously through the sample volume as the temperature decreases toward 𝑇 𝑓 . Characteristic spin-correlation times well above 𝑇 𝑓 are on the order of 10 −10 s, much slower than typically observed in canonical spin glasses but in line with expectations for a cluster spin glass. Using magnetic pair distribution function (mPDF) analysis and reverse Monte Carlo (RMC) modeling of the magnetic diffuse neutron-scattering data, we show that the spin-glass ground state consists of clusters of spins exhibiting short-range-ordered type-III antiferromagnetic correlations with a locally ordered moment of 3.1⁢(1)⁢𝜇 B between nearest-neighbor spins. The type-III correlations decay exponentially as a function of spin separation distance with a correlation length of approximately 5 Å. The diffuse magnetic scattering and corresponding mPDF show no significant changes across 𝑇 𝑓 , indicating that the dynamically fluctuating short-range spin correlations in the paramagnetic state retain the same basic type-III configuration that characterizes the spin-glass state; the only change apparent from the neutron-scattering data is a gradual reduction of the correlation length and locally ordered moment with increasing temperature. Taken together, these results paint a unique and detailed picture of the local magnetic structure and dynamics in Zn 0.5 ⁢Mn 0.5⁢ Te and provide strong evidence that this material is best described as a cluster spin glass. In addition, this work showcases a statistical method for extracting diffuse scattering signals from neutron powder diffraction data, which we developed to facilitate the mPDF and RMC analysis of the neutron data. This method has the potential to be broadly useful for neutron powder diffraction experiments on a variety of materials with short-range atomic or magnetic order.

magnetism↗
DOE OSTI2021

Quantitative order-parameter measurement in lattice-mismatched AlInP using precession electron diffraction

Precession electron diffraction (PED) was used to measure the long-range order parameter in lattice-mismatched AlInP epitaxial films under investigation for solid-state-lighting applications. Both double- and single-variant films grown at 620, 650, and 680°C were analyzed in TEM cross-section. PED patterns were acquired in selected-area-diffraction mode through external microscope control using serial acquisition, which allows inline image processing. The integrated peak intensities from experimental patterns were fit using dynamical simulations of diffraction from the ordered domain structures. Included in the structure-factor calculations were mean atomic displacements of the anions (P) due to ordering, which were found by valence-force-field calculations to have a nearly linear dependence on order parameter. A maximum order parameter of S = 0.36 was measured for a double-variant specimen grown at 650°C.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Understanding how defects and dopant atoms in copper surface oxides affect reactivity

Copper and its oxides are key catalytic materials, on which reactions often occur at the metal/oxide interface. Here, in this work, we directly connect the induction period observed during methanol-driven reduction of thin-film copper oxides to their atomic-scale structural order. Using temperature-programmed desorption (TPD) methanol titrations combined with scanning tunneling microscopy, we show that highly ordered oxide phases – particularly the “29” structure with its low defect density – exhibit long induction periods and initially low reactivity. The induction period, defined as the number of methanol TPD cycles required to reach half of the maximum formaldehyde yield, scales with oxide order and oxygen coverage. Enhanced reactivity of well-ordered oxides emerges only after repeated methanol adsorption/desorption cycles generate oxygen vacancies and new Cu(111)/Cu x O interfacial sites. In contrast, disordered or sub-stoichiometric oxides, which contain more intrinsic defects and interfaces, are active from the first TPD cycle. We further examine how dilute Pt and Rh dopants influence oxide order and reactivity: 1% Pt increases defect density and catalytic activity, while 1% Rh promotes oxide ordering and longer induction periods. These findings demonstrate that dilute alloying provides a potential method for tuning the structure and reactivity of Cu(111)/Cu x O interfaces.

Cu(111)Methanol oxidation↗
DOE OSTI2022

Physically Informed Machine Learning Prediction of Electronic Density of States

The electronic structure of a material, such as its density of states (DOS), provides key insights into its physical and functional properties and serves as a valuable source of high-quality features for many materials screening and discovery workflows. Still, the computational cost of calculating the DOS, most commonly with density functional theory (DFT), becomes prohibitive for meeting high-fidelity or high-throughput requirements, necessitating a cheaper but sufficiently accurate surrogate. To fulfill this demand, we develop a general machine learning method based on graph neural networks for predicting the DOS purely from atomic positions, six orders of magnitude faster than DFT. This approach can effectively use large materials databases and be applied generally across the entire periodic table to materials classes of arbitrary compositional and structural diversity. We furthermore devise a highly adaptable scheme for physically informed learning which encourages the DOS prediction to favor physically reasonable solutions defined by any set of desired constraints. This functionality provides a means for ensuring that the predicted DOS is reliable enough to be used as an input to downstream materials screening workflows to predict more complex functional properties, which rely on accurate physical features.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Hydrodynamic conditions in laser irradiated buried layer experiments

The calculation of open shell ionization level and radiative properties of materials in Non-Local Thermal Equilibrium (NLTE) is currently still a major challenge for any atomic model. The predictions of various NLTE atomic codes at these conditions still differ significantly. In recent years, a new buried layer platform was developed at the Lawrence Livermore National Laboratory and the Laboratory for Laser Energetics. This platform is used to measure ionization distribution and emission of open L-shell, mid-Z ions and open M-shell, high-Z ions at NLTE conditions that are relevant in many laser plasma applications. These experiments offer a unique chance for benchmarking the atomic models. In order to perform these experiments, a uniform well characterized plasma source is required. In this work, we present one-dimensional (1D) and two-dimensional simulations of the experimental platform. These simulations were used for both the design and the analysis of the experiments. The simulations demonstrate the different phases of hydrodynamic evolution of the target and identify the time windows in which uniform conditions can be achieved. A 1D expansion of the target was found to be adequate to describe the target's evolution for most of the experiment duration. The fast 1D simulations were compared with recent experimental results from the Omega laser facility. The sensitivity of the results to several modeling parameters such as the electron flux limiter and laser resonant absorption is reported.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Multiscale electric-field imaging of polarization vortex structures in PbTiO 3 /SrTiO 3 superlattices

In ferroelectric heterostructures, the interaction between intrinsic polarization and the electric field generates a rich set of localized electrical properties. The local electric field is determined by several connected factors, including the charge distribution of individual unit cells, the interfacial electromechanical boundary conditions, and chemical composition of the interfaces. However, especially in ferroelectric perovskites, a complete description of the local electric field across micro-, nano-, and atomic-length scales is missing. Here, by applying four-dimensional scanning transmission electron microscopy (4D STEM) with multiple probe sizes matching the size of structural features, we directly image the electric field of polarization vortices in (PbTiO 3 ) 16 /(SrTiO 3 ) 16 superlattices and reveal different electric field configurations corresponding to the atomic scale electronic ordering and the nanoscale boundary conditions. The separability of two different fields probed by 4D STEM offers the possibility to reveal how each contributes to the electronic properties of the film.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Superconductivity in undoped BaFe 2 As 2 by tetrahedral geometry design

Fe-based superconductors exhibit a diverse interplay between charge, orbital, and magnetic ordering. Variations in atomic geometry affect electron hopping between Fe atoms and the Fermi surface topology, influencing magnetic frustration and the pairing strength through changes of orbital overlap and occupancies. Here, we experimentally demonstrate a systematic approach to realize superconductivity without chemical doping in BaFe 2 As 2 , employing geometric design within an epitaxial heterostructure. We control both tetragonality and orthorhombicity in BaFe 2 As 2 through superlattice engineering, which we experimentally find to induce superconductivity when the As−Fe−As bond angle approaches that in a regular tetrahedron. This approach to superlattice design could lead to insights into low-dimensional superconductivity in Fe-based superconductors.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

ANDiE the Autonomous Neutron Diffraction Explorer

Here, we developed the Autonomous Neutron Diffraction Explorer (ANDiE) to autonomously perform neutron diffraction measurements to discover the magnetic ordering behavior in a material. Neutron diffraction is one of the few techniques that can directly probe the magnetic ordering of the atoms in a material. As such beamtime at neutron diffraction facilities is in high demand.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

Lattice dynamics of 119 Sn impurity in a bcc-Cr crystal

The chromium crystal doped with 119 Sn isotope was studied using the nuclear resonance inelastic x-ray scattering and first principles calculations. The Sn partial phonon density of states (PDOS) was obtained for three temperatures that correspond to different magnetic states of Cr. At all temperatures, the energy spectrum consists of a broad band around 18 meV and a narrow peak at 43 meV. The additional peak around 39 meV is observed only in the magnetically ordered phases, indicating the influence of magnetic order in chromium on lattice dynamics. The partial PDOS calculated with the antiferromagnetic order on Cr atoms show a very good agreement with the experimental data. It is revealed that the high-energy peak is lying above the phonon spectra of the pure bcc-Cr crystal. These are the local modes with the increased energies due to a strongly reduced distance between Sn and the nearest-neighbor Cr atoms.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Exact solution of the frustrated Potts model with next-nearest-neighbor interactions in one dimension via AI bootstrapping

The one-dimensional (1D) 𝐽 1 −𝐽 2 𝑞-state Potts model is solved exactly for arbitrary 𝑞 by analytically block-diagonalizing the original 𝑞 2 ×𝑞 2 transfer matrix into a simple 2 × 2 maximally symmetric subspace, based on using OpenAI's reasoning model o3-mini-high to exactly solve the 𝑞 = 3 case. Furthermore, by matching relevant subspaces, we map the Potts model onto a simpler effective 1D 𝑞-state Potts model, where 𝐽 2 acts as the nearest-neighbor interaction and 𝐽 1 as an effective magnetic field, nontrivially generalizing a 56-year-old theorem previously limited to the simplest case (𝑞 = 2, the Ising model). Our exact results provide insights to phenomena such as atomic or electronic order stacking in layered materials and the emergence of dome-shaped phases in complex phase diagrams. In conclusion, this work is anticipated to fuel both research in 1D frustrated magnets for recently discovered finite-temperature application potentials and the fast moving topic area of AI in science.

1-dimensional spin chains↗
DOE OSTI2021

Boson Fermion Nucleus Polynuclear Structure: Monograph #11

The boson fermion nucleus (BFN) structure indicates the possibility of stable, nonradioactive polynuclear structures bound by the strong nuclear force. In the process of making polynuclear structures, BFN self-ordering on the nuclear level as a stable structure resembles the self-ordering of carbon atoms at the atomic level into buckminsterfullerene, graphene sheet, or graphene nanotubes. This natural assembly derives from the modulation of electron orbital collapse, which decreases coulomb repulsion between atoms and allows a natural reordering among nuclear structures by modulating the permeability of free space. Polynuclear material would be unearthly in tensile strength, thermal and electrical conductivity, and heat of disassociation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

A Quantum Mechanical MP2 Study of the Electronic Effect of Nonplanarity on the Carbon Pyramidalization of Fullerene C 60

Among C 60 ’s diverse functionalities, its potential application in CO 2 sequestration has gained increasing interest. However, the processes involved are sensitive to the molecule’s electronic structure, aspects of which remain debated and require greater precision. To address this, we performed structural optimization of fullerene C 60 using the QM MP2/6–31G* method. The nonplanarity of the optimized icosahedron is characterized by two types of dihedral angles: 138° and 143°. The 120 dihedrals of 138° occur between two hexagons intersecting at C–C bonds of 1.42 Å, while the 60 dihedrals of 143° are observed between hexagons and pentagons at C–C bonds of 1.47 Å. NBO analysis reveals less pyramidal sp 1.78 hybridization for carbons at the 1.42 Å bonds and more pyramidal sp 2.13 hybridization for the 1.47 Å bonds. Electrostatic potential charges range from -0.04 a.u. to 0.04 a.u. on the carbon atoms. Second-order perturbation analysis indicates that delocalization interactions in the C–C bonds of 1.42 Å (143.70 kcal/mol) and 1.47 Å (34.98 kcal/mol) are 22% and 38% higher, respectively, than those in benzene. MP2/Def2SVP calculations yield a correlation energy of 13.49 kcal/mol per electron for C 60 , slightly higher than the 11.68 kcal/mol for benzene. However, the results from HOMO-LUMO calculations should be interpreted with caution. This study may assist in the rational design of fullerene C 60 derivatives for CO 2 reduction systems.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Beam-Based Target Alignment for Mu2e

The Mu2e Experiment is a precision experiment at Fermi National Accelerator Laboratory, searching for charged lepton flavor violation (CLFV) in the conversion of a muon to an electron in the presence of an atomic nucleus. In order to achieve the expected single-event sensitivity of $3\times 10^{-17}$ , Mu2e will require an intense muon beam, generated via pion decay. These pions are the product of a proton beam striking a radiatively-cooled tungsten target. In order to maximize pion production and prevent target failure, the beam will have to be aligned with the target center to within 0.5 mm. The production target monitor (PTM) will ensure this alignment. The PTM consists of a series of proportional wire chambers (PWC’s) upstream and downstream of the production target. In this dissertation, I explain the requirements of this detector system and derive the decisions about which detector model to use and how they should be arranged from these requirements. After this, I describe my e xperience building the detectors and show an early use for them in the Mu2e proton beam. I also performed a study of the sensitivity and time resolution of this model of PWC and its electronics, and give the results here. I then describe a series of simulation campaigns which shed light on the interactions between the beam and the target, and how these interactions manifest on the downstream detectors. Finally, I give the target scanning procedure to be used to align the beam and target during experiment start up.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Inherent Anharmonicity of Harmonic Solids

Atomic vibrations, in the form of phonons, are foundational in describing the thermal behavior of materials. The possible frequencies of phonons in materials are governed by the complex bonding between atoms, which is physically represented by a spring-mass model that can account for interactions (spring forces) between the atoms (masses). The lowest-order, harmonic , approximation only considers linear forces between atoms and is thought incapable of explaining phenomena like thermal expansion and thermal conductivity, which are attributed to nonlinear, anharmonic , interactions. Here, we show that the kinetic energy of atoms in a solid produces a pressure much like the kinetic energy of atoms in a gas does. This vibrational or phonon pressure naturally increases with temperature, as it does in a gas and therefore results in a thermal expansion. Because thermal expansion thermodynamically defines a Grüneisen parameter γ , which is a typical metric of anharmonicity, we show that even a harmonic solid will necessarily have some anharmonicity. A consequence of this phonon pressure model is a harmonic estimation of the Grüneisen parameter as γ ≈ 3 / 2 3 − 4 x 2 / 1 + 2 x 2 , where x = v t / v l is the ratio of the transverse and longitudinal speeds of sound. We demonstrate the immediate utility of this model by developing a high-throughput harmonic estimate of lattice thermal conductivity that is comparable to other state-of-the-art estimations. By linking harmonic and anharmonic properties explicitly, this study provokes new ideas about the fundamental nature of anharmonicity, while also providing a basis for new material engineering design metrics.

42 ENGINEERING↗