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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Insights on the dissolution of water in an albite melt at high pressures and temperatures from a direct structural analysis

The water dissolution mechanism in silicate melts under high pressures is not well understood. Here we present the first direct structure investigation of a water-saturated albite melt to monitor the interactions between water and the network structure of silicate melt at the molecular level. In situ high-energy X-ray diffraction was carried out on the NaAlSi 3 O 8 -H 2 O system at 800 °C and 300 MPa, at the Advanced Photon Source synchrotron facility. The analysis of the X-ray diffraction data was augmented with classical Molecular Dynamics simulations of a hydrous albite melt, incorporating accurate water-based interactions. The results show that metal–oxygen bond breaking at the bridging sites occurs overwhelmingly at the Si site upon reaction with H 2 O, with subsequent Si–OH bond formation and negligible Al–OH formation. Furthermore, we see no evidence for the dissociation of the Al 3+ ion from the network structure upon breaking of the Si–O bond in the hydrous albite melt. The results also indicate that the Na + ion is an active participant in the modifications of the silicate network structure of the albite melt upon water dissolution at high P–T conditions. We do not find evidence for the Na + ion dissociating from the network structure upon depolymerization and subsequent formation of NaOH complexes. Instead, our results show that the Na + ion persists as a structure modifier with a shift away from Na–BO bonding to an increase in the extent of Na-NBO bonding, in parallel with pronounced depolymerization of the network. Our MD simulations show that the Si–O and Al–O bond lengths are expanded by about 6% in the hydrous albite melt compared to those of the dry melt at high P–T conditions. The changes in the network silicate structure of a hydrous albite melt at high pressure and temperature, as revealed in this study, must be considered in the advancement of water dissolution models of hydrous granitic (or alkali aluminosilicate) melts.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Microstructural and preliminary optical and microwave characterization of erbium-doped CaMoO 4 thin films

This work explores erbium-doped calcium molybdate (Er:CaMoO4) thin films grown on silicon and yttria stabilized zirconia (YSZ) substrates, as a potential solid state system for C-band (utilizing the ∼1.5 μm Er 3+ 4f–4f transition) quantum emitters for quantum network applications. Through molecular beam epitaxial growth experiments and electron microscopy, X-ray diffraction, and reflection electron diffraction studies, we identify an incorporation limited deposition regime that enables a 1:1 Ca:Mo ratio in the growing film leading to single phase CaMoO 4 formation that can be in situ doped with Er (typically 2–100 ppm). We further show that growth on silicon substrates is single phase but polycrystalline in morphology, while growth on YSZ substrates leads to high-quality epitaxial single crystalline CaMoO 4 films. We perform preliminary optical and microwave characterization on the suspected Y 1 –Z 1 transition of 2 ppm, 200 nm epitaxial Er:CaMoO 4 annealed thin films and extract an optical inhomogeneous linewidth of 9.1(1) GHz, an optical excited state lifetime of 6.7(2) ms, a spectral diffusion-limited homogeneous linewidth of 6.7(4) MHz, and an EPR linewidth of 1.10(2) GHz.

Masiulionis, Ignas [Univ. of Chicago, IL (United S↗
NASA NTRS1993

Self-Amplified Optical Pattern Recognizer

Self-amplified optical pattern recognizers developed for use in recognition of patterns, in optical computing, and in optoelectronic neural networks. In recognizer, photorefractive crystal serves as medium in which one holographically records diffraction-grating filter representing pattern with which recognition sought. Apparatus "self-amplified" because signal amplified within filter to many orders of magnitude greater than in prior optical pattern recognizers. Basic principle of operation applicable to many types of correlation filters, including (but not limited to) Vander Lugt matched filters, joint-transform filters, and phase-only filters.

Liu, Hua-Kuang↗
DOE OSTI2023

Machine Learning Automated Analysis of Enormous Synchrotron X-ray Diffraction Datasets

X-ray diffraction (XRD) data analysis can be a time-consuming and laborious task. Deep neural network (DNN) based models trained with synthetic XRD patterns have been proven to be a highly efficient, accurate, and automated method for analyzing common XRD data collected from solid samples in ambient environments. However, it remains unclear whether synthetic XRD-based models can be effective in solving micro(μ)-XRD mapping data for in situ experiments involving liquid phases, which always have lower quality and significant artifacts. In this study, we collected μ-XRD mapping data from a LaCl 3 -calcite hydrothermal fluid system and trained two categories of models to analyze the experimental XRD patterns. Here, the models trained solely with synthetic XRD patterns showed low accuracy (as low as 64%) when solving experimental μ-XRD mapping data. However, the accuracy of the DNN models significantly improved (90% or above) when we trained them with a data set containing both synthetic and a small number of labeled experimental μ-XRD patterns. This study highlights the importance of labeled experimental patterns in training DNN models to solve μ-XRD mapping data from in situ experiments involving liquid phases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2003

Spatial Light Modulators as Optical Crossbar Switches

A proposed method of implementing cross connections in an optical communication network is based on the use of a spatial light modulator (SLM) to form controlled diffraction patterns that connect inputs (light sources) and outputs (light sinks). Sources would typically include optical fibers and/or light-emitting diodes; sinks would typically include optical fibers and/or photodetectors. The sources and/or sinks could be distributed in two dimensions; that is, on planes. Alternatively or in addition, sources and/or sinks could be distributed in three dimensions -- for example, on curved surfaces or in more complex (including random) three-dimensional patterns.

Juday, Richard↗
DOE OSTI2022

Defect identification in simulated Bragg coherent diffraction imaging by automated AI

X-ray Bragg coherent diffraction imaging is a powerful technique for operando and in situ materials characterization and provides a unique means of quantifying the influence of one-dimensional (1D) and two-dimensional (2D) material defects on material response. However, obtaining full images from raw x-ray diffraction data is nontrivial and computationally intensive, precluding real-time experimental feedback. Here, we present a machine learning approach to identify the presence of crystalline line defects (edge and screw) in samples from the raw, 2D, coherent diffraction data without the need for image reconstruction through iterative phase retrieval. Further, we compare different approaches to designing neural networks for this application and demonstrate the potential of automated ML (autoML) approaches.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Behavior of strain stripe networks in barium titanate nanocrystals on crossing its ferroelectric phase transition

Nanoscale strain networks are reported in BaTi O 3 (BTO) crystals of 300 nm size using Bragg coherent diffractive imaging. BTO nanocrystals with clear facets were chosen to identify the crystallographic directions, allowing the strain field direction and periodicity to be studied in detail. Stripes of strain were observed, which were both stable and preserved in tetragonal and cubic phases at elevated temperatures, above the tetragonal-to-cubic phase transition. A finite element analysis approach was used to simulate the domain structures inside a BTO crystal and to understand the origins of the strain stripes as piezoelectric blocks. A 180 ∘ domain model gives a better qualitative match to the experimental images. Published by the American Physical Society 2024

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

Complex Structure of Molten FLiBe (2 Li F – Be F 2 ) Examined by Experimental Neutron Scattering, X-Ray Scattering, and Deep-Neural-Network Based Molecular Dynamics

The use of molten salts as coolants, fuels, and tritium breeding blankets in the next generation of fission and fusion nuclear reactors benefits from furthering the characterization of the molecular structure of molten halide salts, paving the way to predictive capability of the chemical and thermophysical properties of molten salts. Due to its neutronic, chemical, and thermochemical properties, 2 Li F - Be F 2 is a candidate molten salt for several fusion- and fission-reactor designs. We performed neutron and x-ray total-scattering measurements to determine the atomic structure of liquid 2 Li F - Be F 2 . We also performed and neural-network molecular-dynamics simulations to predict the structure obtained by neutron- and x-ray-diffraction experiments. The use of machine learning provides improvements to the efficiency in predicting the structure at a longer length scales than is achievable with simulations at significantly lower computational expense while retaining near accuracy. We found that the NNMD simulations accurately predicted the Be F 4 2 − oligomer formations seen in the experimental first-structure-factor peak. Our combination of high-resolution measurements with large-scale molecular dynamics provided an avenue to explore and experimentally verify the intermediate-range ordering beyond the first-nearest neighbor that has posed too many experimental and computational challenges in previous works. With a deeper understanding of the salt structure and ion ordering, the evolution of salt chemistry over the lifetime of a reactor can be better predicted, which is crucial to the licensing and operation of advanced fission and fusion reactors that employ molten salts. To this end, this work will serve as a reference for future studies of salt structure and macroscopic properties with and without the addition of solutes. Published by the American Physical Society 2024

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

AUTOIGNITION DELAY TIMES FOR REFORMATE GAS MIXTURES FROM METHANE GAS ENGINES

Methane slip is a prominent issue in natural gas reciprocating engines that are used in transportation and marine applications. The incomplete combustion that results in methane slip can be resolved with the introduction of hydrogen within the combustion mixture to improve methane oxidation and further enable combustion within the engine crevices where methane has previously remained unreacted. Steam methane reforming (SMR) is a common method used to produce hydrogen and can be used to design an onboard device to reduce methane slip from reciprocating engines. The development of this reformer device requires the validation of high-fidelity chemical kinetic models at the low temperatures of the crevice volumes of these engines. In this work, auto-ignition data is obtained using a shock tube at lean (φ—0.714 or λ—1.4) and stoichiometric (φ, λ = 1) equivalence ratios spanning a temperature range of 1042–1234 K at the 80-bar operating pressure of the test engine. Blends of methane, hydrogen, and reformate products from the SMR reaction are shock-heated in synthetic air, with the ignition delay time measured using an OH* chemiluminescence detector at 310 nm and a CH* detector at 430 nm. The experimental results are compared to several state-of-the-art chemical kinetic mechanisms from the literature. In general, most of the mechanisms show very good agreement with experiments at higher temperatures, with simulation results showing little deviation from experiments at lower temperatures. A sensitivity analysis was conducted, and the results reveal that the reaction H2 + CH3O2 = H + CH3O2H has a very significant role in determining low-temperature ignition delay times (IDTs) of SMR mixtures. These findings provide valuable insights into the chemical kinetics governing methane reformate combustion and contribute to the optimization of onboard reformer designs aimed at mitigating methane slip in natural gas-fueled engines.

Fraze, Matthew↗
DOE OSTI2022

Crystal structure of halofuginone hydrobromide, C 16 H 18 BrClN 3 O 3 Br

The crystal structure of one form of halofuginone hydrobromide has been solved and refined using synchrotron X-ray powder diffraction data, and optimized using density functional theory techniques. Halofuginone hydrobromide crystallizes in space group P2 1 (#4) with a = 8.87398(13), b = 14.25711(20), c = 15.0153(3) Å, β = 91.6867(15)°, V = 1898.87(4) Å 3 , and Z = 4. The crystal structure consists of alternating layers (parallel to the ab-plane) of planar and nonplanar portions of the cations. N–H∙∙∙Br and O–H∙∙∙Br hydrogen bonds link the protonated piperidine rings and bromide anions into a two-dimensional network parallel to the ab-plane. The powder pattern has been submitted to ICDD for inclusion in the Powder Diffraction File™ (PDF®).

36 MATERIALS SCIENCE↗
DOE OSTI2022

Novel Class of Rhenium Borides Based on Hexagonal Boron Networks Interconnected by Short B 2 Dumbbells

Transition metal borides are known due to their attractive mechanical, electronic, refractive, and other properties. A new class of rhenium borides was identified by synchrotron single-crystal X-ray diffraction experiments in laser-heated diamond anvil cells between 26 and 75 GPa. Recoverable to ambient conditions, compounds rhenium triboride (ReB 3 ) and rhenium tetraboride (ReB 4 ) consist of close-packed single layers of rhenium atoms alternating with boron networks built from puckered hexagonal layers, which link short bonded (~ 1.7 angstrom) axially oriented B 2 dumbbells. The short and incompressible Re-B and B-B bonds oriented along the hexagonal c-axis contribute to low axial compressibility comparable with the linear compressibility of diamond. Sub-millimeter samples of ReB 3 and ReB 4 were synthesized in a large-volume press at pressures as low as 33 GPa and used for material characterization. Crystals of both compounds are metallic and hard (Vickers hardness, H V = 34(3) GPa). Geometrical, crystal-chemical, and theoretical analysis considerations suggest that potential ReB x compounds with x > 4 can be based on the same principle of structural organization as in ReB 3 and ReB 4 and possess similar mechanical and electronic properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Rigidity‐Driven Structural Isomers in the NaCl–Ga 2 S 3 System: Implications for Energy Storage

Alternative energy sources require the search for innovative materials with promising functionalities. Systems with unusual chemical properties represent an insufficiently explored domain, concealing unexpected features. Using diffraction and Raman spectroscopy over a wide temperature range, supported by first‐principles simulations, a rare phenomenon is unveiled: phase‐dependent chemical interactions between binary components in the NaCl–Ga 2 S 3 system. In this unique occurrence, previously intact binary crystalline species transform upon melting into mixed liquid structural isomers, forming bonds with new partners. The chemical combinatorics appears to be fully reversible for stable crystals and liquids. Despite this, rapidly frozen glasses out of thermodynamic equilibrium remain in a metastable isomeric state, offering remarkable properties, particularly a high room‐temperature Na + conductivity, comparable to the best sodium halide superionic conductors and therefore encouraging for sodium solid‐state batteries and energy applications. A rigidity paradigm is responsible for the observed phenomenon, as the extremely constrained Ga 2 S 3 crystal lattice does not survive viscous flow, breaking up at a short‐range level. The removal of rigidity constraints and dense packing leads to a significant increase in empty space, which is the origin of high sodium diffusivity. Broadly, the rigidity‐driven structural isomerism opens up an inspiring path to the discovery of atypical materials.

25 ENERGY STORAGE↗
DOE OSTI2026

Decoding THz‐Driven Dynamic Fingerprints of Ferroelectric Nanotwin Networks

Ultrafast polarization dynamics in ferroelectrics are of considerable interest for high-speed tunable dielectrics and electro-optics. Extended domain wall networks formed in ferroelectric twin nanodomains can support collective dynamics in the terahertz regime but require techniques that track polarization and strain evolution driven by ultrafast stimulus. Here, we use multi-modal probing of THz-pulse-driven excitations in PbTiO 3 /SrTiO 3 superlattices by combining X-ray free electron laser measurements that directly tracks lattice changes, with optical second harmonic generation that tracks the electronic potential coupled with the lattice potential. Dynamical phase-field modeling enables fingerprinting of these collective modes as superpositions of domain “breathing” through wall oscillations and polarization “rotations” with still walls. Ultrafast domain wall motion at 0.1–0.5 THz is observed at practical fields of 100 kV/cm with wall velocities of >4000 m/s, approaching typical speed of sound in PbTiO 3 . A unique “charging” mode is discovered that can electrically charge and discharge domain walls on ∼4 ps time scale thus dynamically tuning wall conductivity. Integrated experimental and theoretical fingerprinting of the dynamical landscape presented here enables ultrafast control of ferroics for high-speed microelectronics and optical applications.

THz dynamics↗
NASA NTRS1990

Silicon carbon alloy thin film depositions using electron cyclotron resonance microwave plasmas

Amorphous and microcrystalline silicon carbon films (a-SiC:H, micro-c-SiC:H) have been deposited using SiH4, CH4 and H2 mixed gas ECR (electron cyclotron resonance) plasmas. The optical bandgap of a-SiC:H films is not dependent on the hydrogen dilution in the ECR plasma. The deposition rate of a-SiC:H films is found to be strongly dependent on the ECR magnetic field and the hydrogen dilution. The hydrogen dilution effect on the deposition rate indicates that the etching in ECR hydrogen plasmas plays an important role in the deposition of a-SiC:H films. The optical constants n and k of ECR-deposited a-SiC:H films in the wavelength region of 0.4 to 1.0 micron are determined to be 2.03-1.90 and 0.04-0.00, respectively. The microstructures of ECR-deposited micro-c-SiC:H films are shown by X-ray diffraction and SEM (scanning electron microscopy) to be composed of 1000-A alpha-SiC microcrystallites and amorphous network structures.

Shing, Y. H.↗
DOE OSTI2024

Investigation of fast and efficient lossless compression algorithms for macromolecular crystallography experiments

Structural biology experiments benefit significantly from state-of-the-art synchrotron data collection. One can acquire macromolecular crystallography (MX) diffraction data on large-area photon-counting pixel-array detectors at framing rates exceeding 1000 frames per second, using 200 Gbps network connectivity, or higher when available. In extreme cases this represents a raw data throughput of about 25 GB s −1 , which is nearly impossible to deliver at reasonable cost without compression. Our field has used lossless compression for decades to make such data collection manageable. Many MX beamlines are now fitted with DECTRIS Eiger detectors, all of which are delivered with optimized compression algorithms by default, and they perform well with current framing rates and typical diffraction data. However, better lossless compression algorithms have been developed and are now available to the research community. Here one of the latest and most promising lossless compression algorithms is investigated on a variety of diffraction data like those routinely acquired at state-of-the-art MX beamlines.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Deep learning of structural morphology imaged by scanning X-ray diffraction microscopy

Scanning X-ray nanodiffraction microscopy is a powerful technique for spatially resolving nanoscale structural morphologies by diffraction contrast. One of the critical challenges in experimental nanodiffraction data analysis is posed by the convergence angle of nanoscale focusing optics which creates simultaneous dependency of the far-field scattering data on three independent components of the local strain tensor-corresponding to dilation and two potential rigid body rotations of the unit cell. All three components are in principle resolvable through a spatially mapped sample tilt series; however, traditional data analysis is computationally expensive and prone to artifacts. In this study, we implement NanobeamNN, a convolutional neural network specifically tailored to the analysis of scanning probe X-ray microscopy data. NanobeamNN learns lattice strain and rotation angles from simulated diffraction of a focused X-ray nanobeam by an epitaxial thin film and can directly make reasonable predictions on experimental data without the need for additional fine-tuning. We demonstrate that this approach represents a significant advancement in computational speed over conventional methods, as well as a potential improvement in accuracy over the current standard.

Luo, Aileen [Cornell Univ., Ithaca, NY (United Sta↗
DOE OSTI2023

Local structural investigation of non-crystalline materials at high pressure: the case of GeO 2 glass

Abstract Local structures play a crucial role in the structural polyamorphism and novel electronic properties of amorphous materials, but their accurate measurement at high pressure remains a formidable challenge. In this article, we use the local structure of network-forming GeO 2 glass as an example, to present our recent approaches and advances in high-energy x-ray diffraction, high-pressure x-ray absorption fine structure, and ab initio first-principles density functional theory calculations and simulations. Although GeO 2 glass is one of the best studied materials in the field of high pressure research due to its importance in glass theory and geophysical significance, there are still some long-standing puzzles, such as the existence of appreciable distinct fivefold [5] Ge coordination at low pressure and the sixfold-plus [6+] Ge coordination at ultrahigh pressure. Our work sheds light on the origin of pressure-induced polyamorphism of GeO 2 glass, and the [5] Ge polyhedral units may be the dominant species in the densification mechanism of network-forming glasses from tetrahedral to octahedral amorphous structures.

Physics↗
DOE OSTI2024

Navigating high-dimensional process-structure–property relations in nanocrystalline Pt-Au alloys with machine learning

For decades, materials scientists have relied on the process-structure–property paradigm to guide investigations into material behaviors. Traditional studies often examine a limited number of process-structure–property variables, striving to elucidate mechanisms governing material response. However, this approach is time consuming and can limit exploration, as well as the discovery of process-structure–property relations in novel materials. In this paper, we combined combinatorial sputter deposition and multi-modal high-throughput materials characterization with feedforward neural networks to establish high-dimensional process-structure–property relations in Pt-Au alloys, yielding nanocrystalline alloys with high hardness and low resistivity relevant to electrical contact switch applications. We mapped three indicators of process conditions (composition and two atomic deposition characteristics) onto four indicators of material structure (X-ray diffraction, film thickness, density, and surface roughness) and two indicators of material properties (hardness and resistivity), resulting in 784 unique combinations evaluated over a 13-dimensional space. The neural networks predicted Pt-Au alloys with 18–24 at.% Au, when deposited at specific conditions, to have a nanoindentation hardness up to 7.2 GPa. This high hardness value, comparable to some steels, represents a 3-fold improvement in hardness over “hard gold”, a commonly used electrical contact alloy, while maintaining requisite electrical conductivity. The neural network models provide an avenue to identify expected process windows capable of maximizing material performance.

Electrical contact materials↗