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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Laser Powder Bed Fusion Manufactured Alloys 625 and 282 and Properties Relevant to Advanced Nuclear Components

Under the Advanced Materials and Manufacturing Technologies program, two Ni-based alloys fabricated by laser powder bed fusion (LPBF) have been evaluated: γ′-strengthened Haynes 282 and solution-strengthened Inconel 625. Large printing defects were observed in the LPBF 282 alloy fabricated using a Renishaw AM250 machine, likely due to particle spattering during printing. Annealing at 1,180°C for 1 h followed by 4 h at 800°C in a high density of 50 nm γ′-strengthening precipitates as well as partial recrystallization resulted in a bimodal grain distribution. Creep testing performed at 750°C revealed lower creep life and ductility for the LPBF 282 compared with wrought 282. X-ray computed tomography combined with optical and scanning electron microscopy microstructural characterization revealed crack formation during creep testing, initiated either from printing defects or from creep cavitation at grain boundaries. Printing defects were the likely reason for the lower creep performance of LPBF 282 and could be suppressed by optimizing the build configuration. Printing 625 on an EOS M290 machine using the recommended EOS parameters resulted in a very low defect density. Superior creep strength at 725°C was observed for the as-printed LPBF 625 along the build direction when compared with wrought 625. No defect larger than ~50 µm could be detected by X-ray computed tomography in the as-printed conditions and after creep testing for 1,000 h at 725°C and 150 MPa. Small, needle-like δ-phase precipitates were observed after creep testing for 100 h at 725°C and 200 MPa. The rapid formation of the γ phase is directly related to the initial Nb and Mo segregation in the LPBF 625 cell walls, and its effect on the alloy’s high-temperature performance will be evaluated. Solution annealing was carried out at 1,150°C for 1 h and led to full recrystallization of the alloy. A decrease in strength and increase in ductility were observed after solution annealing, and the alloy recrystallization resulted in isotropic tensile properties at room temperature, contrary to what was observed for the as-printed LPBF 625.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Spinning metasurface stack for spectro-polarimetric thermal imaging

Spectro-polarimetric imaging in the long-wave infrared (LWIR) region plays a crucial role in applications from night vision and machine perception to trace gas sensing and thermography. However, the current generation of spectro-polarimetric LWIR imagers suffers from limitations in size, spectral resolution, and field of view (FOV). While meta-optics-based strategies for spectro-polarimetric imaging have been explored in the visible spectrum, their potential for thermal imaging remains largely unexplored. In this work, we introduce an approach for spectro-polarimetric decomposition by combining large-area stacked meta-optical devices with advanced computational imaging algorithms. The co-design of a stack of spinning dispersive metasurfaces along with compressive sensing and dictionary learning algorithms allows simultaneous spectral and polarimetric resolution without the need for bulky filter wheels or interferometers. Our spinning-metasurface-based spectro-polarimetric stack is compact (<10×10×10cm) and robust, and it offers a wide field of view (20.5°). We show that the spectral resolving power of our system substantially enhances performance in machine learning tasks such as material classification, a challenge for conventional panchromatic thermal cameras. Our approach represents a significant advance in the field of thermal imaging for a wide range of applications including heat-assisted detection and ranging (HADAR).

Optics↗
DOE OSTI2024

Super Resolving Unrolled Neural Networks for Remote Sensing

In remote sensing systems, the capabilities of the system are constrained by the complex interactions between size, weight, and power (SWAP) of potential designs. In electro-optical (EO) systems, examples of these critical parameters include the system’s sensitivity and resolution. Those parameters can be increased by ever larger optical apertures and focal planes but at the cost of more SWAP. Multi-image super resolution (MISR) techniques allow resolution to be enhanced via computation rather than more sophisticated optical hardware. These algorithms combine multiple images together into a single, higher resolution image, trading temporal resolution and computation for spatial resolution. Fielded MISR techniques, such as Drizzle, can require several hundred images to create a single super resolved image, implying reduced temporal resolution, increased data acquisition load, and limiting mission applications. Iterative techniques, such as model-based image reconstruction and compressive sensing, have been shown to create super resolved images using fewer images than Drizzle. They do this by posing an optimization problem that balances accuracy between a highly accurate physical model and an image model. In the case of super resolution, the physical model is defined by the relation between low resolution input images and the desired high resolution output image. The image model encodes some assumptions about the super resolved image. These assumptions are meant to suppress reconstruction artifacts that arise due to deterministic physical model error, stochastic measurement noise, and potential undersampling. In practice, the performance of iterative methods are limited by imaging models compatible with optimization. Deep learning-based methods can effectively learn image models of arbitrary complexity, but lack the theoretical explainability and robustness of iterative techniques. Consensus equilibrium (CE) generalizes the iterative techniques beyond optimization, enabling blackbox algorithms such as traditional and neural image denoisers to be used as the image model. CE-based approaches retain much of the explainability and robustness of iterative techniques while allowing the expressiveness of machine learning image models to be used. Additionally, by unrolling iterations of CE with an embedded image denoiser, the image denoiser can be further trained and specialized to the specific application with potentially higher quality reconstructions. Under this project, we demonstrated the feasibility of training an unrolled neural network based upon CE. While we didn’t train one, we showed that the CE process is differentiable and its gradient can be tractably computed. We also explored the usage of a variants of CE akin to generative neural works. Most importantly, we applied the CE framework to a number of problems including non-blind deconvolution, upsampling, single-image super resolution, MISR, event-based sensing, and saturated deconvolution. Our MISR prototype creates high quality reconstructions with an order of magnitude fewer images than previous approaches and, critically, produces these reconstructions fast enough for practical usage.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Stochastic optimization of a uranium oxide reaction mechanism using plasma flow reactor measurements

Abstract In this work, a coupled Monte Carlo Genetic Algorithm (MCGA) approach is used to optimize a gas phase uranium oxide reaction mechanism based on plasma flow reactor (PFR) measurements. The PFR produces a steady Ar plasma containing U, O, H, and N species with high temperature regions (3000–5000 K) relevant to observing UO formation via optical emission spectroscopy. A global kinetic treatment is used to model the chemical evolution in the PFR and to produce synthetic emission signals for direct comparison with experiments. The parameter space of a uranium oxide reaction mechanism is then explored via Monte Carlo sampling using objective functions to quantify the model-experiment agreement. The Monte Carlo results are subsequently refined using a genetic algorithm to obtain an experimentally corroborated set of reaction pathways and rate coefficients. Out of 12 reaction channels targeted for optimization, four channels are found to be well constrained across all optimization runs while another three channels are constrained in select cases. The optimized channels highlight the importance of the OH radical in oxidizing uranium in the PFR. This study comprises a first step toward producing a comprehensive experimentally validated reaction mechanism for gas phase uranium molecular species formation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Non-resonant Raman optical activity from phase-space electronic structure theory

In order to model experimental non-resonant Raman optical activity, chemists must compute a host of second-order response tensors (e.g., the electric-dipole–magnetic-dipole polarizability) and their nuclear derivatives along a set of vibrational modes. While these response functions are almost always computed within a Born–Oppenheimer (BO) framework, here we provide a natural interpretation of the electric-dipole–magnetic-dipole polarizability within phase space electronic structure theory, a beyond-BO model whereby the electronic structure depends on nuclear momentum (P) in addition to nuclear position (R). By coupling to nuclear momentum, phase space electronic structure theory is able to capture the asymmetric response of the electronic properties to an external field, in so far as for a vibrating (non-stationary) molecule, $\frac{∂μ}{∂B}$≠$\frac{∂m}{∂F}$, where μ and m are the electrical linear and magnetic dipoles, and F and B are electric and magnetic fields. As an example, for a prototypical methyloxirane molecule, we show that phase space electronic structure theory is able to deliver a reasonably good match with experimental results in a manner that is formally invariant to gauge origin G 0 —provided that one uses a complete basis or, alternatively, gauge invariant atomic orbitals.

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

Ab initio leading order effective potential for elastic proton scattering based on the symmetry-adapted no-core shell model

Calculating microscopic optical potentials for elastic scattering at intermediate energies from light nuclei in an ab initio fashion within the Watson expansion has been established within the last few years. Based on the Watson expansion of the multiple scattering series, we employ a nonlocal translationally invariant nuclear density derived within the symmetry-adapted no-core shell model (SA-NCSM) framework from a chiral next-to-next-to-leading order (NNLO) nucleon-nucleon interaction and the very same interaction for a consistent full-folding calculation of the effective (optical) potential for nucleon-nucleus scattering for medium-heavy nuclei. The leading order effective (optical) folding potential is computed by integrating over a translationally invariant SA-NCSM one-body scalar density, spin-projected momentum distribution, and the Wolfenstein amplitudes 𝐴, 𝐶, and 𝑀. The resulting nonlocal potentials serve as input for a momentum space Lippmann-Schwinger equation. In the SA-NCSM, the model space is systematically up-selected using Sp⁡(3,ℝ) symmetry considerations. For the light nucleus of 6 He, we establish a systematic selection scheme in the SA-NCSM for scattering observables. Then, we apply this scheme to calculations of scattering observables, such as differential cross sections, analyzing powers, and spin rotation functions for elastic proton scattering from 20 Ne and 40 Ca in the energy regime between 65 and 200 MeV, and compare to available data. Furthermore, our calculations show that the leading order effective nucleon-nucleus potential in the Watson expansion of multiple scattering theory obtained from an up-selected SA-NCSM model space describes 40 Ca elastic scattering observables reasonably well to about 60 degrees in the center-of-mass frame, which coincides roughly with the validity of the NNLO chiral interaction used to calculate both the nucleon-nucleon amplitudes and the one-body scalar and spin nuclear densities.

Ab initio calculations↗
DOE OSTI2024

Effect of laminae count and manufacturing methods on mechanical properties of thin‐ply woven composites

Abstract Thin‐ply woven composites exhibit exceptional mechanical performance by delaying the onset of damage, making them suitable for high‐performance structural applications. This study outlines the impact of manufacturing techniques (vacuum bagging and hot pressing), ply count, and fiber waviness on the mechanical properties of aromatic thermosetting copolyester/carbon‐fiber (ATSP/CF) composites. The analysis encompasses several different ply counts, evaluating their effects on the in‐plane elastic modulus (0°–90°) and tensile strength. Results demonstrate that reducing the waviness (or crimp) ratio significantly enhances the in‐plane elastic modulus, with improvements up to 188%, highlighting the importance of fiber alignment. Vacuum bagging produced ply thicknesses from 128 to 58 μm for 1–36 plies, with in‐plane elastic moduli from 30.3 to 87.2 GPa, and 4‐ and 8‐ply samples showed approximately 40% higher stiffness than those made by hot pressing. ATSP resin with high thermal stability (up to 400°C) and recyclability was used. Furthermore, this study highlights the microstructural enhancements achieved through vacuum bagging, as revealed by scanning electron and optical microscopy, and micro‐computed tomography imaging. This paper provides insights into damage mitigation and achieving enhanced mechanical properties by controlling fiber waviness using vacuum bagging and higher ply count in thin‐ply ATSP/CF composites. Highlights Crimp ratio reduction enhances elastic in‐plane elastic modulus up to 188%. Vacuum bagging increases modulus over the hot pressing manufacturing method by 40%. Lowering thickness‐per‐ply increases failure strain from 0.8% to 1.2%. Explored the performance of a novel ATSP matrix with high recyclability and thermal stability.

Kushwaha, Shashank [The Grainger College of Engine↗
DOE OSTI2023

Toggling Stereochemical Activity through Interstitial Positioning of Cations between 2D V 2 O 5 Double Layers

The 5/6s 2 lone-pair electrons of p-block cations in their lower oxidation states are a versatile electronic and geometric structure motif that can underpin lattice anharmonicity and often engender electronic and structural instabilities that underpin the function of active elements in nonlinear optics, thermochromics, thermoelectrics, neuromorphic computing, and photocatalysis. In contrast to periodic solids where lone-pair-bearing cations are part of the structural framework, installing lone-pair-bearing cations in the interstitial sites of intercalation hosts provides a means of a systematically modulating electronic structure through the choice of the group and the period of the inserted cation while preserving the overall framework connectivity. The extent of stereochemical activity and the energy positioning of lone-pair-derived mid-gap states depend on the cation identity, stoichiometry, and strength of anion hybridization. V 2 O 5 polymorphs are versatile insertion hosts that can accommodate a broad range of s-, p-, and d-block cations. However, the insertion of lone-pair-bearing cations remains largely underexplored. In this article, we examine the implications of varying the 6s 2 cations situated in interlayer sites between condensed [V 4 O 10 ] n double layers. Systematic modulations of lattice distortions, electronic structure, and magnetic ordering are observed with increasing strength of stereochemical activity from group 12 to group 14 cations. We compare and contrast p-block-layered M x V 2 O 5 (M = Hg, Tl, and Pb) compounds and map the significance of local off-centering arising from the stereochemical activity of lone-pair cations to the emergence of filled antibonding lone-pair 6s 2 –O 2p-hybridized mid-gap states mediated by second-order Jahn–Teller distortions. Crystallographic studies of cation coordination environments and the resulting modulation of V–V interactions have been used in conjunction with variable-energy hard X-ray photoelectron spectroscopy measurements, first-principles electronic structure calculations, and crystal orbital Hamilton population analyses to decipher the origins of stereochemical activity. Magnetic susceptibility measurements reveal antiferromagnetic signatures for all the three compounds. However, the differences in V–V interactions significantly affect the energy balance of the superexchange interactions, resulting in an ordering temperature of 160 and 260 K for Hg 0.5 V 2 O 5 and δ-Tl 0.5 V 2 O 5 , respectively, as compared to 7 K for δ-Pb 0.5 V 2 O 5 . In δ-Pb 0.5 V 2 O 5 , the strong stereochemical activity of electron lone pairs and the resulting electrostatic repulsions enforce superlattice ordering, which strongly modifies the electronic localization patterns along the [V 4 O 10 ] slabs, resulting in disrupted magnetic ordering and an anomalously low ordering temperature. The results demonstrate a versatile strategy for toggling the stereochemical activity of electron lone pairs to modify the electronic structure near the Fermi level and to mediate superexchange interactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Exotic Carbonate Mineralization Recovered from a Deep Basalt Carbon Storage Demonstration

Mitigating climate change require transformational advances for carbon dioxide removal, including geologic carbon sequestration in reactive subsurface environments. The Wallula Basalt Carbon Storage Pilot Project demonstrated that CO 2 injected into >800 m deep Columbia River Basalt Group flow top reservoirs mineralizes on month-year timescales. Herein, we present new optical petrography, micro-computed X-ray tomography, and electron microscopy results sidewall cores collected two years after CO 2 injection. As no other anthropogenic carbonates from geologic carbon storage field studies have been recovered, this world-unique sample suite provides unparalleled insight for subsurface carbon mineralization products and paragenesis. Chemically-zoned nodules with Ca/Mn-rich cores and Fe-dominant outer rims are prominent examples of the neoformed carbonate assemblages with ankerite-siderite compositions and exotic divalent cation correlations. Further, paragenetic insights for the timing of aragonite, silica, and fibrous zeolites are clarified based on mineral texture and spatial relationships, along with time-resolved downhole fluid sampling. Collectively, these results clarify the mineralogy, chemistry, and paragenesis of carbon mineralization, providing insight into the ultimate fate and transport of CO 2 in reactive mafic-ultramafic reservoirs

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Open-Source and FAIR Research Software for Proteomics

Scientific discovery relies on innovative software as much as experimental methods, especially in proteomics, where computational tools are essential for mass spectrometer setup, data analysis, and interpretation. Since the introduction of SEQUEST, proteomics software has grown into a complex ecosystem of algorithms, predictive models, and workflows, but the field faces challenges, including the increasing complexity of mass spectrometry data, limited reproducibility due to proprietary software, and difficulties integrating with other omics disciplines. Closed-source, platform-specific tools exacerbate these issues by restricting innovation, creating inefficiencies, and imposing hidden costs on the community. Open-source software (OSS), aligned with the FAIR Principles (Findable, Accessible, Interoperable, Reusable), offers a solution by promoting transparency, reproducibility, and community-driven development, which fosters collaboration and continuous improvement. In this manuscript, we explore the role of OSS in computational proteomics, its alignment with FAIR principles, and its potential to address challenges related to licensing, distribution, and standardization. Drawing on lessons from other omics fields, we present a vision for a future where OSS and FAIR principles underpin a transparent, accessible, and innovative proteomics community.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Probing itinerant carrier dynamics at the diamond surface using single nitrogen vacancy centers

Color centers in diamond are widely explored for applications in quantum sensing, computing, and networking. Their optical, spin, and charge properties have extensively been studied, while their interactions with itinerant carriers are relatively unexplored. Here, we show that NV centers situated 10 ± 5 nm of the diamond surface can be converted to the neutral charge state via hole capture. By measuring the hole capture rate, we extract the capture cross section, which is suppressed by proximity to the diamond surface. The distance dependence is consistent with a carrier diffusion model, indicating that the itinerant carrier lifetime can be long, even at the diamond surface. Measuring dynamics of near-surface NV centers offers a tool for characterizing the diamond surface and investigating charge transport in diamond devices.

Physics↗
DOE OSTI2024

Adiabatic light guide with S-shaped strips

A light guide is an essential part of many scintillator counters and light collection systems. Our main interest is a light guide for a thin, wide scintillator that has high light transmission while converting the area of the light source to the shape of a photo-detector. Here, we propose a variation of the light guide that avoids a 90° twist of the strips, reduces the length of the light pipe, and reduces the complexity of production. Detailed Monte Carlo simulation studies have been performed for a three-strip S-shaped light-guide system.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Simulating lossy Gaussian boson sampling with matrix-product operators

Gaussian boson sampling, a computational model that is widely believed to admit quantum supremacy, has already been experimentally demonstrated and is claimed to surpass the classical simulation capabilities of even the most powerful supercomputers today. However, whether the current approach limited by photon loss and noise in such experiments prescribes a scalable path to quantum advantage is an open question. Here, to understand the effect of photon loss on the scalability of Gaussian boson sampling, we analytically derive the asymptotic operator entanglement entropy scaling, which relates to the simulation complexity. As a result, we observe that efficient tensor network simulations are likely possible under the N out ∝ √N scaling of the number of surviving photons N out in the number of input photons N. We numerically verify this result using a tensor network algorithm with U⁡(1) symmetry, and we overcome previous challenges due to the large local Hilbert-space dimensions in Gaussian boson sampling with hardware acceleration. Additionally, we observe that increasing the photon number through larger squeezing does not increase the entanglement entropy significantly. Finally, we numerically find the bond dimension necessary for fixed accuracy simulations, providing more direct evidence for the complexity of tensor networks.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Spoofing Cross-Entropy Measure in Boson Sampling

Cross-entropy (XE) measure is a widely used benchmark to demonstrate quantum computational advantage from sampling problems, such as random circuit sampling using superconducting qubits and boson sampling (BS). We present a heuristic classical algorithm that attains a better XE than the current BS experiments in a verifiable regime and is likely to attain a better XE score than the near-future BS experiments in a reasonable running time. The key idea behind the algorithm is that there exist distributions that correlate with the ideal BS probability distribution and that can be efficiently computed. The correlation and the computability of the distribution enable us to postselect heavy outcomes of the ideal probability distribution without computing the ideal probability, which essentially leads to a large XE. Our method scores a better XE than the recent Gaussian BS experiments when implemented at intermediate, verifiable system sizes. Much like current state-of-the-art experiments, we cannot verify that our spoofer works for quantum-advantage-size systems. However, we demonstrate that our approach works for much larger system sizes in fermion sampling, where we can efficiently compute output probabilities. Finally, we provide analytic evidence that the classical algorithm is likely to spoof noisy BS efficiently.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Entanglement Generation in Weakly Driven Arrays of Multilevel Atoms via Dipolar Interactions

We investigate the driven-dissipative dynamics of multilevel atomic arrays interacting via dipolar interactions at subwavelength spacings. Unlike two-level atoms in the weakly excited regime, multilevel atoms can become strongly entangled. Here, the entanglement manifests as the growth of spin waves in the ground-state manifold and survives after turning off the drive. We propose the 2.9 μ⁢m transition between 3 P 2 ↔ 3 D 3 in 88 Sr with 389 nm trapping light as a platform to test our predictions and explore many-body physics with light-matter interactions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Phase stability in the Hf-N and Zr-N systems

Hf and Zr nitrides are promising compounds for many technologically important areas, including high-temperature structural applications, quantum computing, and solar and optical applications. Here, this article reports on a comprehensive first-principles statistical mechanics study of phase stability in the Hf-N and Zr-N binary systems. A high solubility of nitrogen in the hcp forms of Hf and Zr is predicted. The rocksalt forms of HfN and ZrN can also tolerate a high degree of off-stoichiometry through the introduction of nitrogen and metal vacancies. The Hf-N binary favors a family of stacking faulted parent crystal structures at intermediate nitrogen concentrations that host a unique form of short-range order among nitrogen interstitials and vacancies. These phases can accommodate some degree of configurational entropy and remain ordered to temperatures as high as 1200 K.

Monte Carlo methods↗
DOE OSTI2022

Impacts of the Additive Manufacturing Process on the Roughness of Engine Scale Vanes and Cooling Channels

Abstract By leveraging the additive manufacturing (AM) platform, development time and costs for turbine component testing can be reduced relative to traditional investment casting. Surface roughness is a key characteristic of the additive manufacturing process that can impact flow, heat transfer, and mechanical integrity of printed components. There are multiple design and build considerations that result in variability in surface roughness, especially when additively fabricating complicated three-dimensional vanes and internal cooling passages. This study characterizes the surface roughness of internal cooling passages, vanes, and flat external surface samples made using additive manufacturing, specifically the direct metal laser sintering process. The samples were manufactured with various wall thicknesses, layer thicknesses, build locations, build directions, and on different AM machines. A combination of computed tomography scanning and optical profilometry was used to evaluate surface roughness levels. The data indicate that the dominant factors in roughness for a given layer thickness are a function of wall thickness, build location, and build direction.

Engineering↗