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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Exploring the phase space of Zn 2 SbN 3 , a novel semiconducting nitride

The novel semiconductor Zn 2 SbN 3 is one of a growing list of ternary nitrides with promise for optoelectronic and energy applications. Previous work by Arca et al. [Materials Horizons, 2019, 6, 1669–1974] first reported synthesis of this material, but did not explore the effects of growth conditions on material formation. In this work, we present a semi-automated study of the relationship between growth conditions and crystallinity via high-throughput RF sputtering and a custom X-ray diffraction analysis routine. Zn 2 SbN 3 is found to crystallize in a wide range of growth conditions, and the formation of several contaminant phases is examined. Electron microscopy of these secondary phases, caused both by off-stoichiometry and by growth conditions, provides insight into the growth mechanisms of Zn 2 SbN 3 . Furthermore, computational work relates this material to other Zn-based ternary nitrides and offers an explanation for the difficulty of growing cation-ordered material despite the wide range of growth conditions explored.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Shock behavior of materials

The physics governing the response of materials to shock loading has many applications in various fields, ranging from Earth and planetary science to engineering and ballistics. Elucidating the behavior of materials experiencing the passage of shock waves motivates active research worldwide, including experimental developments with in situ and time-resolved measurements, modern computational approaches, and multi-scale simulations.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Nanotwinned alloys under high pressure

Nanotwinned alloys are of interest due to their high strength and ductility, but twin boundaries may not be stable under shear. Computational studies indicate that high hydrostatic pressure may suppress detwinning mechanisms. Here, in this study, we investigate the microstructural changes of nanotwinned-nanocrystalline copper-nickel and Inconel 725 alloys under quasi-hydrostatic pressures up to 50 gigapascals (GPa). The alloys are compressed in a diamond anvil cell. In-situ x-ray diffraction (XRD) and ex-situ transmission electron microscopy (TEM) were employed to monitor microstructural changes. Twin boundary deformation and grain growth occur at 11.4 GPa quasi-hydrostatic pressure in the copper-nickel alloy. Molecular dynamics (MD) simulations reveal that hydrostatic pressure causes elevated local shear stress at grain boundaries, which leads to atomic rearrangements. A superposition of hydrostatic and deviatoric pressures lead to partial dislocation mediated twin boundary migration. In contrast, the Inconel 725 alloy showed stable twin and grain boundaries up to a quasi-hydrostatic pressure of 12.7 GPa. Texture, high solid solution strengthening, and low stacking fault energy are hypothesized to the enhanced microstructural stability in Inconel 725.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Projected Multi-Agent Consensus Equilibrium (PMACE) With Application to Ptychography

Multi-Agent Consensus Equilibrium (MACE) formulates an inverse imaging problem as a balance among multiple update agents such as data-fitting terms and denoisers. However, each such agent operates on a separate copy of the full image, leading to redundant memory use and slow convergence when each agent affects only a small subset of the full image. In this article, we extend MACE to Projected Multi-Agent Consensus Equilibrium (PMACE), in which each agent updates only a projected component of the full image, thus greatly reducing memory use for some applications. We describe PMACE in terms of an equilibrium problem and an equivalent fixed-point problem and show that in most cases the PMACE equilibrium is not the solution of an optimization problem. To demonstrate the value of PMACE, we apply it to the problem of ptychography, in which a sample is reconstructed from the diffraction patterns resulting from coherent X-ray illumination at multiple overlapping spots. In our PMACE formulation, each spot corresponds to a separate data-fitting agent, with the final solution found as an equilibrium among all the agents. In conclusion, our results demonstrate that the PMACE reconstruction algorithm generates more accurate reconstructions at a lower computational cost than existing ptychography algorithms when the spots are sparsely sampled.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Au 3 -to-Ag 3 coordinate-covalent bonding and other supramolecular interactions with covalent bonding strength

An efficient strategy for designing charge-transfer complexes using coinage metal cyclic trinuclear complexes (CTCs) is described herein. Due to opposite quadrupolar electrostatic contributions from metal ions and ligand substituents, [Au(m-Pz-(i-C 3 H7) 2 )] 3 ∙[Ag(m-Tz-(n-C 3 F 7 ) 2 )] 3 (Pz = pyrazolate, Tz = triazolate) has been obtained and its structure verified by single crystal X-ray diffraction – representing the 1st crystallographically-verified M 3 @M' 3 stacked adduct of monovalent coinage metal CTCs. Abundant supramolecular interactions with aggregate covalent bonding strength arise from a combination of M–M' (Au / Ag), metal–π, π–π interactions and hydrogen bonding in this charge-transfer complex, according to density functional theory analyses, yielding a computed binding energy of 66 kcal mol -1 between the two trimer moieties – a large value for intermolecular interactions between adjacent d 10 centres (nearly doubling the value for a recently claimed Au(I) / Cu(I) polar-covalent bond: Proc. Natl. Acad. Sci. U.S.A., 2017, 114, E5042) – which becomes 87 kcal mol -1 with benzene stacking. Surprisingly, DFT analysis suggests that: (a) some other literature precedents should have attained a stacked M 3 @M' 3 product akin to the one herein, with similar or even higher binding energy; and (b) a high overall intertrimer bonding energy by inferior electrostatic assistance, underscoring genuine orbital overlap between M and M' frontier molecular orbitals in such polar-covalent M–M' bonds in this family of molecules. The Au / Ag bonding is reminiscent of classical Werner-type coordinate-covalent bonds such as H 3 N: → Ag in [Ag(NH 3 ) 2 ] + , as demonstrated herein quantitatively. Solidstate and molecular modeling illustrate electron flow from the p-basic gold trimer to the p-acidic silver trimer with augmented contributions from ligand-to-ligand’ (LL'CT) and metal-to-ligand (MLCT) charge transfer.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

The First Neptunium Dioxide Neutron Diffraction Experiment at HFIR

Here we present the first neutron diffraction experiment of a 50 mg sample of neptunium(IV) dioxide (NpO 2 ) powder at the High Flux Isotope Reactor (HFIR) using the wide-angle neutron diffractometer (WAND 2 ) HB-2C. We also provide a brief literature survey to pinpoint gaps in the crystal, electronic, and magnetic structure of NpO 2 to determine the optimum experiment to be pursued in the next HFIR user proposal cycle. Characterizing actinide materials with neutron diffraction, inelastic scattering, neutron imaging, polarized neutron studies, and small-angle neutron scattering techniques will increase our understanding of 5f electron behavior and elucidate atomic and magnetic structural properties. This strategy will help fill gaps in the literature and provide theoretical physicists with the data needed to build physical and chemical models to guide and validate computational methods. These methods may be used for predicting structural and chemical features of actinide-based materials. This proof-of-principle effort begins to uncover how to advance actinide science and technology at Oak Ridge National Laboratory (ORNL) using neutron capabilities. This effort has already sparked collaborative discussions between researchers outside the Radioisotope Science and Technology Division, including theoretical physicists from the Nuclear Nonproliferation Division and beamline scientists in the Neutron Scattering Division. We intend to continue pursuing neutron experiments and develop a scientific strategy focused on studying transuranium elements (e.g., Np, Pu, Am, and Cm) using the advanced neutron capabilities at ORNL.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Materials genome innovation for computational software (magics) center

Functional layered material (LM) architectures will dominate nanomaterials science in this century. We have developed theory, modeling, simulation, and software and data tools that enhance understanding and AI guide synthesis, enable characterization of complex structures, and improve capabilities in the predictive design and growth of LMs. Research at the Center has focused on: Computational synthesis and characterization: AI guided synthesis and experimental synthesis of stacked LMs with tailored properties via optimized chemical vapor deposition (CVD) growth and liquid-phase exfoliation; study defects, edges, grain boundaries, wrinkling of atomic layers and their effects on chemical, mechanical, electrical, and optical properties. Far-from-equilibrium processes: Joint experimental and simulation based probe of electronic processes with NAQMD and ultrafast X-ray free-electron laser (XFEL) and ultrafast electron diffraction (UED) facilities at Stanford. Experimentally validate NAQMD by ultrafast electron diffraction and X-ray spectroscopy studies of structural and excited state dynamics, shape fluctuations, and phonon dynamics. Scalable software: Simulation engines for desktop-to-exascale platforms using low-overhead, linear-scaling QMD algorithms; divide-conquer-recombine NAQMD with electronic excitations; extended-Lagrangian reactive molecular dynamics (RMD), machine learning (ML) based neural-network quantum molecular dynamics (NNQMD), and super-state accelerated molecular dynamics (AMD) and kinetic Monte Carlo codes; thermal and electrical transport software; and design 3D architectures of LMs with desired functionality using scalable software. Distribution of software and data, and training: Software and simulation-experimental data generated within the Center are distributed to the materials science community via Berkeley Materials Project (MP) framework. We have also organized three workshops for software distribution and training at USC (Nov. 2017, Mar. 2018) and Gaithersburg, MD (Nov. 2018) to train researchers, with the last one in focused on underrepresented groups, in collaboration with Howard University which is one of the largest HBCUs. The Center supported a total of 46 personnel and 6 undergraduate students. These include 14 faculty, 11 postdoctoral research associates, 20 graduate research assistants, and mentored 6 undergraduate students. This resulted in the publications of 63 research papers that include 46 publications on Reactive and Quantum Dynamics Simulations, 13 publications on Machine Learning for Quantum Materials, and 4 publications on Quantum Computing.

2D Materials↗
DOE OSTI2020

An Atomic View of Cation Diffusion Pathways from Single‐Crystal Topochemical Transformations

Abstract The diffusion pathways of Li‐ions as they traverse cathode structures in the course of insertion reactions underpin many questions fundamental to the functionality of Li‐ion batteries. Much current knowledge derives from computational models or the imaging of lithiation behavior at larger length scales; however, it remains difficult to experimentally image Li‐ion diffusion at the atomistic level. Here, by using topochemical Li‐ion insertion and extraction to induce single‐crystal‐to‐single‐crystal transformations in a tunnel‐structured V 2 O 5 polymorph, coupled with operando powder X‐ray diffraction, we leverage single‐crystal X‐ray diffraction to identify the sequence of lattice interstitial sites preferred by Li‐ions to high depths of discharge, and use electron density maps to create a snapshot of ion diffusion in a metastable phase. Our methods enable the atomistic imaging of Li‐ions in this cathode material in kinetic states and provide an experimentally validated angstrom‐level 3D picture of atomic pathways thus far only conjectured through DFT calculations.

Handy, Joseph V.↗
DOE OSTI2025

Elucidating texture and grain morphology contributions to the micromechanical response of additively manufactured Inconel 625

Microstructural variation of additively manufactured (AM) metal components in comparison to wrought counterparts makes certification for critical applications a challenge. Microscale simulations leveraging modern computational tools may be used to supplement testing of AM microstructures, thus accelerating certification by reducing the number of experiments needed. However, as micromechanical response is closely tied to critical properties like fatigue-life and fracture, utilization of these simulations with macroscale experimental data alone is insufficient. One means to attain microscale experimental data is in situ diffraction data collected from synchrotron X-ray sources. In this work, such data were collected during in situ compression of AM Inconel 625 superalloy. Interpretation of experimental results was assisted by massive (8M element) complementary micromechanical simulations performed on sets of virtual microstructures generated using cellular automata. Together, micromechanical data from diffraction experiments and simulations were used to probe the effects of textured “track” microstructures generated during laser powder bed fusion and directional strength-to-stiffness on micromechanical response. Though fiber-averaged directional strength-to-stiffness ratios were expected to dominate given the high elastic anisotropy of the material, the combination of small variations in texture and specific grain configurations unique to AM microstructures lead to significant variability in micromechanical response after yield. The findings emphasize the importance of high-fidelity microstructural representation that captures key texture components and AM-specific morphology for property prediction of AM metals.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Superlattice reflection signatures of the insulator–metal transition in V 3 O 5 thin films

Nanoelectronic systems that are inspired by the brain are increasingly looking to insulator–metal transition (IMT) materials as they can mimic the response characteristics of neurons to temperature changes so that these can be used in robotic and computational applications. V 3 O 5 has an insulator–metal transition at ∼430 or ∼80 K higher than VO 2 and provides a unique high-temperature opportunity for these types of applications. Here, in this work, we track the structural evolution of V 3 O 5 thin films across the IMT through conventional selected-area electron diffraction (SAED) and four-dimensional scanning TEM (4D-STEM), correlated with temperature-dependent resistance measurements. SAED patterns show reversible evidence of superlattice reflections associated with the IMT—present below T IMT and absent above it—consistent with the accompanying drop in resistance. At room temperature, nanobeam electron diffraction patterns further reveal three local configurations: (i) type I regions with clean patterns lacking superlattice reflections and spot splitting; (ii) type II regions exhibiting rows of superlattice reflections and split spots indicative of crystallographic variants; and (iii) type III regions with negligible superlattice reflections but larger spot splitting suggestive of overlapping domains of insulating and conducting phases likely driven by local lattice distortions. Upon heating, the superlattice reflections disappear between 413 and 453 K, concurrent with the resistance drop at T IMT , consistent with the emergence of a conducting phase. The overall diffraction geometry remains essentially unchanged up to 573 K, implying that relative domain orientations persist through the transition. These observations reveal nanoscale structural heterogeneity in V 3 O 5 thin films across the IMT and inform operation in regimes where mixed-phase textures are expected. A plausible indexing framework rationalizing the observed geometries is presented in the Discussion section, alongside its limitations and alternative interpretations.

25 ENERGY STORAGE↗
DOE OSTI2023

Direct growth of crystalline SiGe nanowires on superconducting NbTiN thin films

Novel heterostructures created by coupling one-dimensional semiconductor nanowires with a superconducting thin film show great potential toward next-generation quantum computing. Here, by growing high-crystalline SiGe nanowires on a NbTiN thin film, the resulting heterostructure exhibits Ohmic characteristics as well as a shift of the superconducting transition temperature (T c ). The structure was characterized at atomic resolution showing a sharp SiGe/NbTiN interface without atomic interdiffusion. Lattice spacing, as calculated from large-area x-ray diffraction experiments, suggests a potential preferred d-spacing matching between (200) NbTiN and (110) SiGe grains. The observed out-of-plane compressive strain within the NbTiN films coupled with SiGe nanowires explains the downward shift of the superconductivity behavior. The presented results post scientific insights toward functional heterostructures by coupling multi-dimensional materials, which could enable tunable superconductivity that benefits the quantum science applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2021

Discovery of Nb hydride precipitates in superconducting qubits

We report the first evidence of the formation of niobium hydrides within niobium films on silicon substrates in superconducting qubits fabricated at Rigetti Computing. We combine complementary techniques including room and cryogenic temperature atomic scale high-resolution and scanning transmission electron microscopy (HR-TEM and STEM), atomic force microscopy (AFM), and the time-of-flight secondary ion mass spectroscopy (TOF-SIMS) to reveal the existence of the niobium hydride precipitates directly in the Rigetti chip areas. Electron diffraction and high-resolution transmission electron microscopy (HR-TEM) analyses are performed at room and cryogenic temperatures (~106 K) on superconducting qubit niobium film areas, and reveal the formation of three types of Nb hydride domains with different crystalline orientations and atomic structures. There is also variation in their size and morphology from small (~5 nm) irregular shape domains within the Nb grains to large (~10-100 nm) Nb grains fully converted to niobium hydride. As niobium hydrides are non-superconducting and can easily change in size and location upon different cooldowns to cryogenic temperatures, our findings highlight a new previously unknown source of decoherence in superconducting qubits, contributing to both quasiparticle and two-level system (TLS) losses, and offering a potential explanation for qubit performance changes upon cooldowns. A pathway to mitigate the formation of the Nb hydrides for superconducting qubit applications is also discussed.

Lee, Jaeyel↗
DOE OSTI2024

Focused Ion Beam Tomography of Alloy 617 Corroded in Molten Chloride Salt

Materials qualification of reactor structural materials is a critical step in rapid implementation of advanced nuclear reactor technologies, particularly to assess the corrosion performance in these designs. Accelerated qualification of reactor structural materials requires incorporating powerful computational toolsets, such as phase field modelling in the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework, to predict the evolution of structural materials due to corrosion. Accordingly, computational toolsets will require experimental data generated at appropriate length scales to validate accuracy. Focused ion beam (FIB) provides a high degree of control over manipulation of materials for analytical purposes, including capturing data on the evolution in the microstructure and elemental composition of materials at the mesoscale, an appropriate length scale for phase field modelling of intergranular diffusion phenomena using the MOOSE framework. For instance, the FEI Helios G4 UX dual beam plasma FIB microscope at the Irradiated Materials Characterization Laboratory (IMCL) is capable of backscatter diffraction (EBSD) and energy-dispersive x-ray spectroscopy (EDS) documenting the evolution in the microstructure and elemental composition, respectively. The Helios can perform EDS and EBSD three-dimensionally (3D) using tomography, which is then combined using different software packages to visualize 3D volumes correlating elemental composition to microstructural data. The purpose of this investigation was to develop a streamlined characterization and data processing workflow for 3D tomography studies on the FEI Helios G4 plasma FIB. The investigation is segmented into three parts: 1) Optimizing the data collection workflow, 2) identifying appropriate data processing and visualization software (i.e. DREAM.3D, MIPAR, and VGStudioMax), and 3) establishing an infrastructure for public release. The optimization of the data collection workflow is in collaboration with members of the U220 department to setup formal training on the tomography operation of the G4, through ThermoFisher Scientific, and exploring DREAM.3D, MIPAR, and VGStudioMax data processing/visualization software packages. VGStudioMax currently demonstrates the most promise for future use. Optimization of the data collection and processing workflow is still ongoing. A collaboration with INL High Performance Computing (HPC) established an open-source license for expediting the public release of FIB tomography datasets through HPC. FIB tomography data generated by the G4 will provide comprehensive data for validating 3D phase field mesoscale modelling tools within the MOOSE framework for accelerated qualification of reactor structural materials.

Copeland-Johnson, Trishelle↗
DOE OSTI2021

Machine learning framework for quantum sampling of highly constrained, continuous optimization problems

In recent years, there is growing interest in using quantum computers for solving combinatorial optimization problems. In this work, we developed a generic, machine learning-based framework for mapping continuous-space inverse design problems into surrogate quadratic unconstrained binary optimization (QUBO) problems by employing a binary variational autoencoder and a factorization machine. The factorization machine is trained as a low-dimensional, binary surrogate model for the continuous design space and sampled using various QUBO samplers. Using the D-Wave Advantage hybrid sampler and simulated annealing, we demonstrate that by repeated resampling and retraining of the factorization machine, our framework finds designs that exhibit figures of merit exceeding those of its training set. We showcase the framework’s performance on two inverse design problems by optimizing (i) thermal emitter topologies for thermophotovoltaic applications and (ii) diffractive meta-gratings for highly efficient beam steering. This technique can be further scaled to leverage future developments in quantum optimization to solve advanced inverse design problems for science and engineering applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Learning neural representations for X-ray ptychography reconstruction with unknown probes

X-ray ptychography provides exceptional nanoscale resolution and is widely applied in materials science, biology, and nanotechnology. However, its full potential is constrained by the critical challenge of accurately reconstructing images when the illuminating probe is unknown. Conventional iterative methods and deep learning approaches are often suboptimal, particularly under the low-signal conditions inherent to low-dose and high-speed experiments. These limitations compromise reconstruction fidelity and restrict the broader adoption of the technique. In this work, we introduce the Ptychographic Implicit Neural Representation (PtyINR), a self-supervised framework that simultaneously addresses the object- and probe-recovery problem. By parameterizing both as continuous neural representations, PtyINR performs end-to-end reconstruction directly from raw diffraction patterns without requiring any pre-characterization of the probe. Extensive evaluations demonstrate that PtyINR achieves superior reconstruction quality on both simulated and experimental data, with remarkable robustness under challenging low-signal conditions. Furthermore, PtyINR offers a generalizable, physics-informed framework for addressing probe-dependent inverse problems, making it applicable to a wide range of computational microscopy problems.

36 MATERIALS SCIENCE↗
DOE OSTI2022

FAIR principles for AI models with a practical application for accelerated high energy diffraction microscopy

Abstract A concise and measurable set of FAIR (Findable, Accessible, Interoperable and Reusable) principles for scientific data is transforming the state-of-practice for data management and stewardship, supporting and enabling discovery and innovation. Learning from this initiative, and acknowledging the impact of artificial intelligence (AI) in the practice of science and engineering, we introduce a set of practical, concise, and measurable FAIR principles for AI models. We showcase how to create and share FAIR data and AI models within a unified computational framework combining the following elements: the Advanced Photon Source at Argonne National Laboratory, the Materials Data Facility, the Data and Learning Hub for Science, and funcX, and the Argonne Leadership Computing Facility (ALCF), in particular the ThetaGPU supercomputer and the SambaNova DataScale ® system at the ALCF AI Testbed. We describe how this domain-agnostic computational framework may be harnessed to enable autonomous AI-driven discovery.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Prediction of residual stresses in additively manufactured parts using lumped capacitance and classical lamination theory

Several industries are interested in Laser Powder Bed Fusion (L-PBF) Additively Manufactured (AM) metal parts because their designs can be made arbitrarily complex while retaining bulk-type material properties. However, the residual stresses (RS) and distortions caused by the heat gradients inherent to L-PBF processes are detrimental to the structural integrity of the parts and must be taken into consideration during the part design cycle. Predicting the state of stresses in as-built 3D printed parts is a difficult problem that is typically approached with the use of transient thermomechanical Finite Element Models (FEMs). However, the nonlinearities associated with AM processes are difficult to capture in these FEMs without increasing the computational cost of the simulation, limiting their ability to be incorporated into practical design cycles. This work presents a novel analytical framework that combines lumped capacitance nonlinear heat transfer with time dependent classical lamination theory to efficiently and accurately predict RS in as-built L-PBF parts without the need of FEMs. The simulation was compared to Neutron Diffraction (ND) residual strain measurements taken at Oak Ridge National Laboratories (ORNL) as well as Synchrotron X-ray Diffraction (XRD) strain data published by the National Institute of Standards and Technology (NIST). The simulation predictions and the experimental data showed excellent agreement for the in-plane strain directions, and general agreement for the out of plane strain component, highlighting an area where further development can be implemented.

42 ENGINEERING↗