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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

Chemical composition based machine learning model to predict defect formation in additive manufacturing

With a goal of exploiting additive manufacturing to improve the manufacturing of existing reactor materials, we developed a chemical composition-based machine learning model to predict the printability of any given alloy in laser powder bed fusion (L-PBF) using experimental data from peer-reviewed literature. We defined printability as the ability to avoid defects like cracking, balling, porosity, and lack of fusion, that are caused by thermal stresses (during solidification or liquation), molten pool disintegration into disconnected small beads or lack of heat input respectively. Our models predict the tendency of balling defect formation and porosity percentage for a given composition, under a given set of processing conditions. To predict the likelihood of balling defect, three models: a random forest classifier, a gradient boost regressor and a neural network were trained on a dataset containing both traditional alloys and high entropy alloys. The neural network model showed the highest accuracy of 92.3 % in predicting the balling defect formation. A random forest regressor, gradient boost regressor and neural network were trained and tested on a dataset of various alloys to predict porosity. The random forest regressor showed the best predictions with an R 2 score of 0.97. The models also revealed the relative importance of the input descriptors on defect-formation tendency. Of particular significance was the identification of carbon as an important element in determining the occurrence of balling and percent porosity in alloys like steel, as well as being moderately important to the percentage porosity in other alloys as well as steel. Manganese was also identified as a key descriptor for the percentage of porosity in steel and other alloys. Manganese’s low thermal conductivity and consistent presence in the dataset is the likely cause for its contribution. Carbon’s role is attributable to its relatively high specific heat and high melting temperature. In conclusion, our model serves as a swift, chemistry-based tool to design experiments and find modified compositions better suited for additive manufacturing.

36 MATERIALS SCIENCE↗

Concentric core-shell tracks and spectroscopic properties of SrTiO 3 under intense electronic excitation

A deeper understanding of the intrinsic link between the irradiation-induced microstructures and the corresponding spectroscopic properties is becoming increasingly attractive for the research fields of materials science, physics, and information technology. In this work, the structural damage response, spectroscopic features, and associated physical mechanisms of SrTiO 3 single crystals under swift heavy ion irradiation were comparatively analyzed using a combination of experimental and theoretical approaches. Corresponding to 0.11–5.00 MeV/u ion irradiation with electronic energy loss ranging from 4.0 to 29.3 keV/nm, the inelastic thermal spike calculations combined with molecular dynamics simulations are compared with the experimental observations, revealing the track fine structures (individual spherical defects with a disordered region, and discontinuous and continuous tracks consisting of an amorphous core and a disordered outer shell) and demonstrating the dominant effects of the deposition energy and lattice temperature on track damage formation and evolution; thus, two essential thresholds for defect formation of ~0.60 eV/atom and amorphous region formation of ~1.81 eV/atom were identified to better describe the concentric core-shell track structure. The enhanced nanohillock formation in the surface region is attributed to the combined action of kinetic and potential energy depositions, and the fluence dependence in regulating the hillock dimensions is also presented. The measured refractive index profiles along different crystal axes further indicate the anisotropy of irradiation-induced lattice expansion. With increasing ion fluence and damage level, the intrinsic bandgap gradually decreased, and the concentration of additional radiative recombination centers (1.81 eV, 2.31 eV, and 2.42 eV) accordingly increased in the SrTiO 3 crystal, providing the possibility of regulating related defects to achieve tunable/selective photon emission for more critical technological applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Dynamic response of a freely rotating butterfly valve in the advanced test reactor – dynamic fluid-body interaction modeling

To regulate primary coolant flow in the Advanced Test Reactor (ATR), a butterfly valve was installed between the primary coolant pumps and the reactor core. If the mechanical connection between the valve's disk and its shaft ever fails, the disk will rotate freely. Rapid disk rotation may induce pressure surges that could damage upstream pipes. In the present work, the rotational trajectory and pressure evolution during a disk free-rotation scenario were analyzed via the dynamic fluid-body interaction (DFBI) approach in STAR-CCM+, with the movement of a solid being driven by the forces and moment/torque imposed by its surrounding fluid. Assuming a large initial opening angle, the disk accelerates slowly, but swiftly passes the closed position. As a result of the sudden valve closure, a pressure surge occurs in the upstream pipes, exceeding their maximum allowable pressure. Furthermore, the disk does not stabilize at the closed position but continually oscillates due to the unsteady nature of the coolant flow. Because of the significant and continuous water hammer effect, a fix to the butterfly valve is being implemented to prevent rapid valve closure due to failure at the valve's disk/shaft mechanical connection.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Characterization of a platform for the gas transport, collection, and identification of fission products in the high-intensity laser environment

Recent progress in the production of laser accelerated high flux proton beams opens new possibilities for the study of fission in unique environments. To this end, we are currently pursuing the development of a platform for the swift gas transport, collection, and identification of fission products. Fission is induced in targets fixed inside a sealed chamber through which a carrier gas flows, transporting fission products to a carbon filter for collection and online spectroscopy. This has been recently demonstrated using target normal sheath accelerated protons at the PHELIX laser facility. There were large discrepancies between measured rates and those expected based on established fission yields and measured beam parameters. These discrepancies prompted a large number of tests at the Idaho Accelerator Center (IAC), where fission in uranium is induced by bremsstrahlung photons generated by 21 MeV electrons from a linear electron accelerator. Here, the results are compared to a series of models that account for the slowing of energetic fission fragments in the carrier gas and the fluid dynamics of the gas flow that transports fission products to the collection filter. Characterization of the apparatus reveals a few mechanisms that together account for a portion of the previously observed discrepancies at the PHELIX laser facility. However, additional research is necessary before high-accuracy experiments can be performed with the apparatus. Work performed under the auspices of the U.S. Department of Energy by LLNL under contract DE-AC52-07NA27344.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

High-throughput multimodal exploration of a nanocrystalline Cu-Ag library

Sputter-deposited, nanocrystalline Cu-Ag thin films produced across a broad compositional and deposition-parameter space were evaluated to unravel the process-structure-property relationships important for creating hard, conductive electrical contacts and coatings. Combinatorial deposition involving pulsed direct current magnetron sputtering of elemental targets enabled swift examination of nearly the full range of alloy compositions and a relevant portion of deposition atomistics. Several high-throughput characterization modalities were employed to evaluate the chemistry, structure, and properties of the films. The resultant hardness, modulus, film density, crystal texture, and resistivity were analyzed in terms of key deposition characteristics (incident atom kinetic energy and incidence angle) predicted by binary-collision, kinematic Monte Carlo simulations. The study revealed improved hardness, parabolic resistivity dependence on composition, and compositional and process dependencies of film tarnishing. The results are discussed in the context of variations in microstructure and film density. Transmission electron microscopy and X-ray diffraction demonstrate several forms of compositional variation including solute segregation to grain boundaries as well as periodic, intragranular compositional modulations. Annealing of a Cu-rich alloy film exhibiting grain boundary segregation showed that this as-deposited, compositional variation is not stable above 100 °C. Finally, the Cu-Ag system is shown to have potential for hard, conductive, tarnish-resistant and room temperature-stable nanocrystalline thin films across the composition space.

36 MATERIALS SCIENCE↗

Funding a Just Transition Away from Coal in the U.S. Considering Avoided Damage from Air Pollution

Abstract Coal is declining in the U.S. as part of the clean energy transition, resulting in remarkable air pollution benefits for the American public and significant costs for the industry. Using the AP3 integrated assessment model, we estimate that fewer emissions of sulfur dioxide, nitrogen oxides, and primary fine particulate matter driven by coal’s decline led to $300 billion in benefits from 2014 to 2019. Conversely, we find that job losses driven by less coal plant and mining activity resulted in $7.84 billion in foregone wages over the same timeframe. While the benefits were greatly distributed (mostly throughout the East), costs were highly concentrated in coal communities. Transferring a small fraction of the benefits to workers could cover these costs while maintaining societal net benefits. Forecasting coal fleet damages from 2020 to 2035, we find that buying out or replacing these plants would result in $589 billion in air quality benefits, which considerably outweigh the costs. The return on investment increases when policy targets the most damaging capacity, and net benefits are maximized when removing just facilities where marginal benefits exceed marginal costs. Evaluating competitive reverse auction policy designs akin to Germany’s Coal Exit Act, we find that adjusting bids based on monetary damages rather than based only on carbon dioxide emissions – the German design – provides a welfare advantage. Our benefit–cost analyses clearly support policies that drive a swift and just transition away from coal, thereby clearing the air while supporting communities needing assistance.

Dennin, Luke R. (ORCID:0000000205405520)↗

Biodiesel Ethers: Fatty Acid-Derived Alkyl Ether Fuels as Improved Bioblendstocks for Mixing-Controlled Compression Ignition Engines

In the last 20 years, biodiesel consumption in the United States has swiftly increased to ~2 billion gallons per year as a renewable supplement to fossil fuel. However, further expansion of biodiesel use is currently limited in part by poor cold weather performance, which prevents year-round blending and necessitates blend walls ≤5% v/v. In order to provide a diesel fuel blendstock with improved cold weather performance (cloud point, pour point, and cold filter plug point), while at the same time maintaining other required fuel performance specifications, several biodiesel redox analogues were synthesized and tested. The best performing candidate fuels from this class showed improvement in the derived cetane number (29.3% shorter ignition delay), lower heating value (+4.7 MJ/kg), relative sooting tendency (–7.4 YSI/MJ), and cloud point (15 °C lower) when compared to a B100 biodiesel composed of an identical fatty acid profile. It was observed as a general trend that the reduced form of biodiesel, fatty alkyl ethers (FAEs), shows performance improvements in all fuel property metrics. The suite of improved properties provided by FAEs gives biodiesel producers the opportunity to diversify their portfolio of products derived from lipid and alcohol feedstocks to include long-chain alkyl ethers, a biodiesel alternative with particular applicability for winter weather conditions across the US.

09 BIOMASS FUELS↗

Structure–Property Correlation of Hierarchically Porous Carbons for Fluorocarbon Adsorption

Although traditional commercially available porous carbon-fluorocarbon working pairs have shown promising applicability for adsorption cooling, advancements in synthetic carbons may further improve performance. Moreover, insights into structure-property relationships that target higher sorption capacities within these synthesized carbons may guide such materials' future design. We utilized hierarchically porous synthetic carbons (HPCs) with colossal microporous and mesoporous characterized by high surface areas (up to 2689 m 2 /g) and pore volumes (up to 10.31 cm 3 /g) towards fluorocarbon R134a adsorption. This unique pore topology leads to exceptional R134a uptake, ~250 wt.%, outperforming the highest uptake carbon material to date, Maxsorb III (~220 wt.%). Additionally, material characterizations reveal that the outstanding R134a capacity may be attributed to textural properties and oxygen-terminated functional groups more than graphitization of the material. Most importantly, HPCs are efficiently utilized in a two-bed model chiller device, where the performance shows excellent working capacity (105 wt%, ~1.5 times the value of reported carbon materials/R134a). Fluorocarbons adsorption on HPCs also displays fast kinetics (equilibrium time: ~2 min) mainly driven by physical adsorption (Qst: ~27 kJ/mol), characteristic of swiftly reversible behavior adsorption-desorption behaviors. This work provides a fundamental understanding of the applicability of HPCs/R134a working pair for adsorption cooling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Assessing Adaptive Irrigation Impacts on Water Scarcity in Nonstationary Environments—A Multi‐Agent Reinforcement Learning Approach

Abstract One major challenge in water resource management is to balance the uncertain and nonstationary water demands and supplies caused by the changing anthropogenic and hydroclimate conditions. To address this issue, we developed a reinforcement learning agent‐based modeling (RL‐ABM) framework where agents (agriculture water users) are able to learn and adjust water demands based on their interactions with the water systems. The intelligent agents are created by a reinforcement learning algorithm adapted from the Q‐learning algorithm. We illustrated this framework in a case study where the RL‐ABM is two‐way coupled with the Colorado River Simulation System (CRSS), a long‐term planning model used for the administration of the Colorado River Basin, for assessing agriculture water uses impacts on water scarcity. Seventy‐eight intelligent agents are simulated, which can be grouped into three categories based on their parameter values: the “aggressive” (swift actions; low regrets), the “forward‐looking conservative” (mild actions; high regrets; fast learning), and the “myopic conservative” (mild actions; median regrets; slow learning). The ABM‐CRSS results showed that the major reservoirs in the Upper Colorado Basin might experience more frequent water shortages due to the increasing water uses compared to the original CRSS results. If the drought continues, the case study also demonstrates that agents can learn and adjust their demands.

Hung, Fengwei↗

Nonequilibrium dynamics of spontaneous symmetry breaking into a hidden state of charge-density wave

Abstract Nonequilibrium phase transitions play a pivotal role in broad physical contexts, from condensed matter to cosmology. Tracking the formation of nonequilibrium phases in condensed matter requires a resolution of the long-range cooperativity on ultra-short timescales. Here, we study the spontaneous transformation of a charge-density wave in CeTe 3 from a stripe order into a bi-directional state inaccessible thermodynamically but is induced by intense laser pulses. With ≈100 fs resolution coherent electron diffraction, we capture the entire course of this transformation and show self-organization that defines a nonthermal critical point, unveiling the nonequilibrium energy landscape. We discuss the generation of instabilities by a swift interaction quench that changes the system symmetry preference, and the phase ordering dynamics orchestrated over a nonadiabatic timescale to allow new order parameter fluctuations to gain long-range correlations. Remarkably, the subsequent thermalization locks the remnants of the transient order into longer-lived topological defects for more than 2 ns.

36 MATERIALS SCIENCE↗

Ubiquitous short-range order in multi-principal element alloys

Recent research in multi-principal element alloys (MPEAs) has increasingly focused on the role of short-range order (SRO) on material performance. However, the mechanisms of SRO formation and its precise control remain elusive, limiting the progress of SRO engineering. Here, leveraging advanced additive manufacturing techniques that produce samples with a wide range of cooling rates (up to 10 7 K s –1 ) and an enhanced semi-quantitative electron microscopy method, we characterize SRO in three CoCrNi-based face-centered-cubic (FCC) MPEAs. Surprisingly, irrespective of the processing and thermal treatment history, all samples exhibit similar levels of SRO. Atomistic simulations reveal that during solidification, prevalent local chemical order arises in the liquid-solid interface (solidification front) even under the extreme cooling rate of 10 11 K s –1 . This phenomenon stems from the swift atomic diffusion in the supercooled liquid, which matches or even surpasses the rate of solidification. Therefore, SRO is an inherent characteristic of most FCC MPEAs, insensitive to variations in cooling rates and even annealing treatments typically available in experiments.

36 MATERIALS SCIENCE↗

Improving the fast-charging capability of NbWO-based Li-ion batteries

The discovery of Nb-W-O materials years ago marks the milestone of charging a lithium-ion battery in minutes. Nevertheless, for many applications, charging lithium-ion battery within one minute is urgently demanded, the bottleneck of which largely lies in the lack of fundamental understanding of Li + storage mechanisms in these materials. Herein, by visualizing Li + intercalated into representative Nb 16 W 5 O 55 , we find that the fast-charging nature of such material originates from an interesting rate-dependent lattice relaxation process associated with the Jahn-Teller effect. Furthermore, in situ electron microscopy further reveals a directional, [010]-preferred Li + transport mechanism in Nb 16 W 5 O 55 crystals being the “bottleneck” toward fast charging that deprives the entry of any desolvated Li + through the prevailing non-(010) surfaces. Hence, we propose a machine learning-assisted interface engineering strategy to swiftly collect desolvated Li + and relocate them to (010) surfaces for their fast intercalation. As a result, a capacity of ≈ 116 mAh g −1 (68.5% of the theoretical capacity) at 80 C (45 s) is achieved when coupled with a Li negative electrode.

batteries↗

Automation and machine learning drive rapid optimization of isoprenol production in Pseudomonas putida

Advances in genome engineering have improved our ability to perturb microbial metabolic networks, yet bioproduction campaigns often struggle with parsing complex metabolic datasets to efficiently enhance product titers. We address this challenge by coupling laboratory automation with machine learning to systematically optimize the production of isoprenol, a sustainable aviation fuel precursor, in Pseudomonas putida. The simultaneous downregulation through CRISPR interference of combinations of up to four gene targets, guided by machine learning, permitted us to increase isoprenol titer 5-fold in six consecutive design-build-test-learn cycles. Moreover, machine learning enabled us to swiftly explore a vast experimental design space of 800,000 possible combinations by strategically recommending approximately 400 priority constructs. High-throughput proteomics allowed us to validate CRISPRi downregulation and identify biological mechanisms driving production increases. Our work demonstrates that ML-driven automated design-build-test-learn cycles, when combined with rigorous data validation, can rapidly enhance titers without specific biological knowledge, suggesting that it can be applied to any host, product, or pathway.

Carruthers, David N↗

Comparison of short-range order in irradiated dysprosium titanates

Abstract The structural response of Dy 2 TiO 5 oxide under swift heavy ion irradiation (2.2 GeV Au ions) was studied over a range of structural length scales utilizing neutron total scattering experiments. Refinement of diffraction data confirms that the long-range orthorhombic structure is susceptible to ion beam-induced amorphization with limited crystalline fraction remaining after irradiation to 8 × 10 12 ions/cm 2 . In contrast, the local atomic arrangement, examined through pair distribution function analysis, shows only subtle changes after irradiation and is still described best by the original orthorhombic structural model. A comparison to Dy 2 Ti 2 O 7 pyrochlore oxide under the same irradiation conditions reveals a different behavior: while the dysprosium titanate pyrochlore is more radiation resistant over the long-range with smaller degree of amorphization as compared to Dy 2 TiO 5 , the former involves more local atomic rearrangements, best described by a pyrochlore-to-weberite-type transformation. These results highlight the importance of short-range and medium-range order analysis for a comprehensive description of radiation behavior.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Online energy consumption forecast for battery electric buses using a learning-free algebraic method

Accurately predicting the energy consumption plays a vital role in battery electric buses (BEBs) route planning and deployment. Based on the algebraic derivative estimation, we present a novel method to forecast the energy consumption in real time. In contrast to the mainstream machine-learning-based methods, the proposed method does not require access to the historical energy consumption data. It eliminates the time-consuming and computationally expensive offline training. Consequently, its prediction performance is not constrained by the quantity and quality of the training data. Moreover, the method can swiftly adapt to new situations not included in the previous driving cycles, which makes it especially suitable for emerging transport modes, e.g., on-demand transit services. In addition, its online execution only involves algebraic calculations, yielding superior calculation efficiency. Using real-world data, we comprehensively compare the performance of the proposed learning-free algebraic method with multiple representative machine-learning-based methods. Finally, the advantages and limitations of the proposed method are discussed in detail.

33 ADVANCED PROPULSION SYSTEMS↗

Simultaneous observations of the blazar PKS 2155-304 from ultra-violet to TeV energies

Here we report the results of the first ever contemporaneous multi-wavelength observation campaign on the BL Lac object PKS 2155−304 involving Swift , NuSTAR , Fermi -LAT, and H.E.S.S. The use of these instruments allows us to cover a broad energy range, which is important for disentangling the different radiative mechanisms. The source, observed from June 2013 to October 2013, was found in a low flux state with respect to previous observations but exhibited highly significant flux variability in the X-rays. The high-energy end of the synchrotron spectrum can be traced up to 40 keV without significant contamination by high-energy emission. A one-zone synchrotron self-Compton model was used to reproduce the broadband flux of the source for all the observations presented here but failed for previous observations made in April 2013. A lepto-hadronic solution was then explored to explain these earlier observational results.

79 ASTRONOMY AND ASTROPHYSICS↗

Investigation of the correlation patterns and the Compton dominance variability of Mrk 421 in 2017

We present a detailed characterisation and theoretical interpretation of the broadband emission of the paradigmatic TeV blazar Mrk 421, with a special focus on the multi-band flux correlations. The dataset has been collected through an extensive multi-wavelength campaign organised between 2016 December and 2017 June. The instruments involved are MAGIC, FACT, Fermi-LAT, Swift, GASP-WEBT, OVRO, Medicina, and Metsähovi. Additionally, four deep exposures (several hours long) with simultaneous MAGIC and NuSTAR observations allowed a precise measurement of the falling segments of the two spectral components. The very-high-energy (VHE; E> 100 GeV) gamma rays and X-rays are positively correlated at zero time lag, but the strength and characteristics of the correlation change substantially across the various energy bands probed. The VHE versus X-ray fluxes follow different patterns, partly due to substantial changes in the Compton dominance for a few days without a simultaneous increase in the X-ray flux (i.e., orphan gamma-ray activity). Studying the broadband spectral energy distribution (SED) during the days including NuSTAR observations, we show that these changes can be explained within a one-zone leptonic model with a blob that increases its size over time. The peak frequency of the synchrotron bump varies by two orders of magnitude throughout the campaign. Our multi-band correlation study also hints at an anti-correlation between UV-optical and X-ray at a significance higher than 3σ. A VHE flare observed on MJD 57788 (2017 February 4) shows gamma-ray variability on multi-hour timescales, with a factor ten increase in the TeV flux but only a moderate increase in the keV flux. The related broadband SED is better described by a two-zone leptonic scenario rather than by a one-zone scenario. We find that the flare can be produced by the appearance of a compact second blob populated by high energetic electrons spanning a narrow range of Lorentz factors, from γ' min =2x10 4 to γ' max =6x10 5 .

79 ASTRONOMY AND ASTROPHYSICS↗

Discovery of the luminous X-ray ignition eRASSt J234402.9-352640: I. Tidal disruption event or a rapid increase in accretion in an active galactic nucleus?

In November 2020, a new, bright object, eRASSt J234402.9-352640, was discovered in the second all-sky survey of SRG/eROSITA. The object brightened by a factor of at least 150 in 0.2–2.0 keV flux compared to an upper limit found six months previous, reaching an observed peak of 1.76 -0.24 +0.03 × 10 -11 erg cm -2 s -1 . The X-ray ignition is associated with a galaxy at z = 0.10, making the peak luminosity log 10 (L 0.2-2 keV /[erg s -1 ]) = 44.7 ± 0.1. Around the time of the rise in X-ray flux, the nucleus of the galaxy brightened by approximately 3 mag. in optical photometry, after correcting for the host contribution. We present X-ray follow-up data from Swift, XMM-Newton, and NICER, which reveal a very soft spectrum as well as strong 0.2–2.0 keV flux variability on multiple timescales. Optical spectra taken in the weeks after the ignition event show a blue continuum with broad, asymmetric Balmer emission lines, and high-ionisation ([OIII]λλ4959,5007) and low-ionisation ([NII]λ6585, [SII]λλ6716,6731) narrow emission lines. Following the peak in the optical light curve, the X-ray, UV, and optical photometry all show a rapid decline. The X-ray light curve shows a decrease in luminosity of ~0.45 over 33 days and the UV shows a drop of ~0.35 over the same period. eRASSt J234402.9-352640 also shows a brightening in the mid-infrared, likely powered by a dust echo of the luminous ignition. We find no evidence in Fermi-LAT γ-ray data for jet-like emission. The event displays characteristics of a tidal disruption event (TDE) as well as of an active galactic nucleus (AGN), complicating the classification of this transient. Based on the softness of the X-ray spectrum, the presence of high-ionisation optical emission lines, and the likely infrared echo, we find that a TDE within a turned-off AGN best matches our observations.

79 ASTRONOMY AND ASTROPHYSICS↗