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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 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Synthesizing Highly Crystalline Graphite Powder from Bulk Polyethylene Waste for Lithium-Ion Battery Anodes

Upcycling plastic waste into graphite can potentially be used, in conjunction with other methods, to manage existing waste materials and diversify graphite supply chains. However, synthesizing large quantities of crystalline graphite powder from plastic waste, particularly polyethylene (PE), remains a challenge because PE decomposes into light gases during thermal processing and simple methods do not exist at any appreciable size scale to address this challenge. In this work, a method is developed for air processing bulk forms of PE waste to create stable carbon char that does not readily decompose during high-temperature processing. This method employs solid additives in the form of salts, which are combined with the PE melt during air processing to increase the effective surface area of the melt and improve the oxygen-driven chemistry that stabilizes PE for high-temperature processing. After removal of the solid salt additives from the PE-derived char, it is converted into a highly crystalline bulk graphite powder using an Fe-based catalytic process. The PE-derived graphite anode in a lithium-ion coin cell showed a specific capacity of 345 mAh/g at 0.05C with an initial Coulombic efficiency of 87% and reversible capacity retention of ~100% at different current rates. It also showed a specific capacity of up to 313 mAh/g at 0.5 discharge/charge cycles per hour (0.5C) and Coulombic efficiency of 99.9% after 250 cycles, indicating excellent electrochemical performance as an anode material for lithium-ion batteries. This method illustrates that there are opportunities for upcycling large quantities of PE waste to produce graphite powders suitable for use in LIBs.

25 ENERGY STORAGE↗
DOE OSTI2023

Improving E3SM Land Model Photosynthesis Parameterization via Satellite SIF, Machine Learning, and Surrogate Modeling

The parameterization of key photosynthesis parameters is one of the key uncertain sources in modeling ecosystem gross primary productivity (GPP). Solar-induced chlorophyll fluorescence (SIF) offers a good proxy for GPP since it marks the actual process of photosynthesis; while machine learning (ML) provides a robust approach to model the GPP-SIF relationship. Here, we trained the boosted regressing tree (BRT) and the Random Forest ML models with Greenhouse Gases Observing Satellite SIF data and in situ GPP observations from 49 eddy covariance towers. These trained ML GPP-SIF models were fed into the Energy Exascale Earth System Model (E3SM) Land Model (ELM) to generate ELM-simulated global SIF estimates, which were then benchmarked against satellite SIF observations with a surrogate modeling approach. Our results indicated good modeling performance of the ML-based GPP-SIF relationship. The ELM model when fed with the ML GPP-SIF models also can well predict the spatial-temporal variations in SIF. We also found high model accuracy for the surrogate modeling. Model parameter sensitivity analysis suggested that the fraction of leaf nitrogen in RuBisCO (flnr) is the most sensitive parameter to the SIF; other sensitive parameters include the Ball-Berry stomatal conductance slope (mbbopt) and the vcmax entropy (vcmaxse). The posterior uncertainty in simulated GPP was greatly reduced after benchmarking, and the model produced improved spatial patterns of mean GPP relative to FLUXCOM GPP. Our integrated approach provides a new avenue for improving land models and using remote-sensing SIF, which can be further improved in the future with more ground- and satellite-based observations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Sub-Diurnal Methane Variations on Mars Driven by Barometric Pumping and Planetary Boundary Layer Evolution

In recent years, the Tunable Laser Spectrometer within the Sample Analysis at Mars (TLS-SAM) instrument on board the Mars Science Laboratory (MSL) Curiosity rover has detected methane variations in the atmosphere at Gale crater. Methane concentrations appear to fluctuate seasonally as well as sub-diurnally, which is difficult to reconcile with an as-yet-unknown transport mechanism delivering the gas from underground to the atmosphere. To potentially explain the fluctuations, we consider barometrically induced transport of methane from an underground source to the surface, modulated by temperature-dependent adsorption. The subsurface fractured-rock seepage model is coupled to a simplified 1-D atmospheric mixing model to provide insights on the pattern of atmospheric methane concentrations in response to transient surface methane emissions, as well as to predict sub-diurnal variation in methane abundance for the northern summer period, which is a candidate time frame for a MSL Curiosity sampling campaign. Our analysis suggests that there is a lower limit to the subsurface fracture density that can produce the observed methane patterns, below which the atmospheric methane variations would be out of phase with the observations. The best-performing model scenarios indicate a significant, short-lived methane pulse just prior to sunrise, the detection of which by TLS-SAM would be a potential indicator of the contribution of barometric pumping to Mars' atmospheric methane variations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Dynamic behavior of molecular Pd-acetate trimers and dimers in heterogeneous vinyl acetate synthesis

Vinyl acetate monomer (VAM) is a crucial intermediate in the production of various polymers. While molecular Pd-acetate trimers and dimers, such as Pd 3 (OAc) 6 and K 2 Pd 2 (OAc) 6 , are known to form on potassium acetate (KOAc)-promoted PdAu catalysts during heterogeneous VAM synthesis, their mechanistic role remains unclear. Here, we study the dynamics of different Pd-acetate species by utilizing in situ and operando crystallographic and spectroscopic characterizations combined with computational modeling on monometallic Pd model catalysts. The promoter-free catalyst expectedly shows low catalytic activity and VAM selectivity, corresponding to the complete reduction of Pdn(OAc) 2n species to form Pd 0 and PdC x nanoparticles. Conversely, noticeable quantities of K n Pd 2 (OAc) n+4 species remain on the KOAc-promoted catalyst, leading to smaller nanoparticle formation with 10 times the activity and double the selectivity for VAM. This study reveals that molecular Pd-acetate trimers and dimers are significant indicators of catalytic performance and highlights their structurally dynamic nature in heterogeneous vinyl acetate chemistry.

Jacobs, Hunter P. [Rice Univ., Houston, TX (United↗
DOE OSTI2026

High yield production of 3-hydroxypropionic acid using Issatchenkia orientalis

Biomanufacturing provides a more sustainable alternative to fossil-based chemical manufacturing. 3-Hydroxypropionic acid (3HP) is a top Department of Energy value-added chemical and precursor to bioplastics, yet cost-effective microbial production remains elusive. Here, we establish the acid-tolerant yeast Issatchenkia orientalis as a robust host for low-pH 3HP biosynthesis. Genome-scale modeling identifies the β-alanine pathway as optimal, offering the highest theoretical yield and lowest oxygen requirement. Thermodynamic analysis confirms its favorability under acidic conditions. Using sequence similarity network analysis, we discover highly active aspartate 1-decarboxylase (PAND), β-alanine-pyruvate aminotransferase (BAPAT), and 3HP dehydrogenase (YDFG), which significantly improve the pathway efficiency. Next, to further elevate the production, pathway optimization through multi-copy PAND integration, byproduct elimination (knockouts of pyruvate decarboxylase and glycerol-3-phosphate dehydrogenase), and reinforcement of aspartate flux by overexpression of pyruvate carboxylase and aspartate amino transferase improves the titer to 29 g/L in shake flasks. Fed-batch fermentation at pH 4 with low-cost corn steep liquor medium further increases the production to 92 g/L with 0.7 g/g yield and 0.55 g/L/h productivity. Techno-economic analysis indicates that such performance could potentially enable a financially viable process for sustainable acrylic acid production. This work establishes I. orientalis as a next-generation platform for cost-effective 3HP production and paves the way toward industrial commercialization.

Biotechnology↗
DOE OSTI2023

Chapter 5: Non-Isocyanate Polyurethane from Vegetable and Microalgal Oil

In this chapter, vegetable oil, heterotrophic algal oil and phototrophic algal oil were used for NIPU development. NIPU properties were evaluated, and its promising performance was demonstrated, indicating that vegetable oils and algal oils with high functionalities are promising precursors for NIPU polymers.

BIOMASS FUELS↗
DOE OSTI2020

Assessing DER Network Cybersecurity Defences in a Power-Communication Co-Simulation Environment

Increasing penetrations of interoperable distributed energy resources (DER) in the electric power system are expanding the power system attack surface. Maloperation or malicious control of DER equipment can now cause substantial disturbances to grid operations. Fortunately, many options exist to defend and limit adversary impact on these newly-created DER communication networks, which typically traverse the public internet. However, implementing these security features will increase communication latency, thereby adversely impacting real-time DER grid support service effectiveness. In this work, a collection of software tools called SCEPTRE were used to create a co-simulation environment where SunSpec-compliant PV inverters were deployed as virtual machines and interconnected to simulated communication network equipment. Network segmentation, encryption, and moving target defence security features were deployed on the control network to evaluate their influence on cybersecurity metrics and power system performance. The results indicated that adding these security features did not impact DER-based grid control systems but improved the cybersecurity posture of the network when implemented appropriately.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Implementing time resolved electron temperature capability at the NIF using a streak camera

A new capability on NIF has been implemented to measure the temperature of x-ray emitting sources. Although it is designed primarily for Inertial Confinement Fusion (ICF), it can be used for any hot emitting source that is well modeled. The electron temperature (T e ) of the hot spot within the core of imploded inertial confinement fusion capsules is an effective indicator of implosion performance. Currently, there are spatially and temporally integrated T e inferences using image plates. A temporally resolved measurement of Te will help elucidate the mechanisms for hot spot heating and cooling such as conduction to fuel, alpha-heating, mix and radiative losses. To determine the temporally resolved T e of hot spots, specific filters are added to an existing x-ray streak camera “Streaked Polar Instrumentation for Diagnosing Energetic Radiation (SPIDER)” to probe the emission spectrum during the x-ray burn history of implosions on the National Ignition Facility (NIF). One of the difficulties in inferring the hot spot temperature is the attenuation of the emission due to opacity from the shell and fuel. Therefore, a series of increasingly thick titanium filters were implemented to isolate the emission in specific energy regions that are sensitive to temperatures above 3keV while not significantly influenced by the shell/fuel attenuation. Additionally, a relatively thin zinc filter was used to measure the contribution of colder emission sources. Since the signal levels of the emission through the thicker filters are relatively poor, a dual slit (aperture) was designed to increase detected signal at the higher end of the spectrum. Herein, the design of the filters and slit are described, an overview of the solving technique is provided, and initial electron temperature results are reported.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Electrical and structural properties of binary Ga–Sb phase change memory alloys

Material properties of Ga–Sb binary alloy thin films deposited under ultra-high vacuum conditions were studied for analog phase change memory (PCM) applications. Crystallization of this alloy was shown to occur in the temperature range of 180–264 °C, with activation energy >2.5 eV depending on the composition. X-ray diffraction (XRD) studies showed phase separation upon crystallization into two phases, Ga-doped A7 antimony and cubic zinc-blende GaSb. Synchrotron in situ XRD analysis revealed that crystallization into the A7 phase is accompanied by Ga out-diffusion from the grains. X-ray absorption fine structure studies of the local structure of these alloys demonstrated a bond length decrease with a stable coordination number of 4 upon amorphous-to-crystalline phase transformation. Mushroom cell structures built with Ga–Sb alloys on ø110 nm TiN heater show a phase change material resistance switching behavior with resistance ratio >100 under electrical pulse measurements. TEM and Energy Dispersive Spectroscopy (EDS) studies of the Ga–Sb cells after ∼100 switching cycles revealed that partial SET or intermediate resistance states are attained by the variation of the grain size of the material as well as the Ga content in the A7 phase. A mechanism for a reversible composition control is proposed for analog cell performance. These results indicate that Te-free Ga–Sb binary alloys are potential candidates for analog PCM applications.

Ume, Rubab (ORCID:0000000324766900)↗
DOE OSTI2024

Optimization of submicron Ni/Au/Ge contacts to an AlGaAs/GaAs two-dimensional electron gas

We report on fabrication and performance of sub-micrometer Ni/Au/Ge contacts to a two-dimensional electron gas in an AlGaAs/GaAs heterostructure. Utilizing scanning transmission electron microscopy, energy dispersive x-ray spectroscopy, and low temperature electrical measurements, we investigate the relationship between contact performance and the mechanical and chemical properties of the annealed metal stack. Contact geometry and crystallographic orientation significantly impact performance. Our results indicate that the spatial distribution of germanium in the annealed contact plays a central role in the creation of high transmission contacts. We characterize the transmission of our contacts at high magnetic fields in the quantum Hall regime. Our work establishes that contacts with an area of 0.5 μm2 and resistance less than 400 Ω can be fabricated with high yield.

Physics↗
DOE OSTI2025

Effect of annealing on the tribological behavior of Zr-based bulk metallic glass

Bulk Metallic Glasses (BMGs) are promising materials for several applications owing to their high elastic limit and resistance to permanent deformation. However, BMGs have lower wear resistance than their crystalline counterparts during dry sliding. The formation of a composite material with crystalline phases dispersed in the BMG matrix through devitrification and partial crystallization at elevated temperatures has recently been proposed as an effective way to improve the wear resistance. However, our understanding of the origin of the improved wear behavior of annealed BMGs is still elusive. Here, a systematic evaluation of the effect of annealing temperature (from temperatures lower than the BMG glass transition temperature to temperatures higher than the BMG recrystallization temperature) on the friction and wear response of a Zr-based BMG, namely Vit105 (Zr 52.5 Cu 17.9 Ni 14.6 Al 10 Ti 5 ), was performed. The results indicate that annealing Vit105 improves its wear resistance while also reducing the steady-state friction response when the annealing temperature is close to the glass transition temperature. Notably, the formation of a transfer film on the sapphire countersurface is highly dependent on the applied normal load and sliding time. Finally, the wear mechanism was found to be strongly dependent on the annealing temperature as a transition from a predominantly adhesive wear mechanism to an abrasive-dominated one was observed as the annealing temperature crossed the glass transition temperature. Altogether, the results of this work aid to our understanding of the tribological behavior of Zr-based BMGs in general, while also providing clues to strategies for the effective use of BMGs in tribological applications.

Lien, Hsu-Ming [Univ. of Texas, Austin, TX (United↗
DOE OSTI2024

Forecasting high-dimensional spatio-temporal systems from sparse measurements

This paper introduces a new neural network architecture designed to forecast high-dimensional spatio-temporal data using only sparse measurements. The architecture uses a two-stage end-to-end framework that combines neural ordinary differential equations (NODEs) with vision transformers. Initially, our approach models the underlying dynamics of complex systems within a low-dimensional space; and then it reconstructs the corresponding high-dimensional spatial fields. Many traditional methods involve decoding high-dimensional spatial fields before modeling the dynamics, while some other methods use an encoder to transition from high-dimensional observations to a latent space for dynamic modeling. In contrast, our approach directly uses sparse measurements to model the dynamics, bypassing the need for an encoder. This direct approach simplifies the modeling process, reduces computational complexity, and enhances the efficiency and scalability of the method for large datasets. We demonstrate the effectiveness of our framework through applications to various spatio-temporal systems, including fluid flows and global weather patterns. Although sparse measurements have limitations, our experiments reveal that they are sufficient to forecast system dynamics accurately over long time horizons. Our results also indicate that the performance of our proposed method remains robust across different sensor placement strategies, with further improvements as the number of sensors increases. This robustness underscores the flexibility of our architecture, particularly in real-world scenarios where sensor data is often sparse and unevenly distributed.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Scaling Arctic landscape and permafrost features improves active layer depth modeling

Tundra ecosystems in the Arctic store up to 40% of global below-ground organic carbon but are exposed to the fastest climate warming on Earth. However, accurately monitoring landscape changes in the Arctic is challenging due to the complex interactions among permafrost, micro-topography, climate, vegetation, and disturbance. This complexity results in high spatiotemporal variability in permafrost distribution and active layer depth (ALD). Moreover, these key tundra processes interact at different scales, and an observational mismatch can limit our understanding of intrinsic connections and dynamics between above and below-ground processes. Consequently, this could limit our ability to model and anticipate how ALD will respond to climate change and disturbances across tundra ecosystems. In this paper, we studied the fine-scale heterogeneity of ALD and its connections with land surface characteristics across spatial and spectral scales using a combination of ground, unoccupied aerial system, airborne, and satellite observations. We showed that airborne sensors such as AVIRIS-NG and medium-resolution satellite Earth observation systems like Sentinel-2 can capture the average ALD at the landscape scale. We found that the best observational scale for ALD modeling is heavily influenced by the vegetation and landform patterns occurring on the landscape. Landscapes characterized by small-scale permafrost features such as polygon tussock tundra require high-resolution observations to capture the intrinsic connections between permafrost and small-scale land surface and disturbance patterns. Conversely, in landscapes dominated by water tracks and shrubs, permafrost features manifest at a larger scale and our model results indicate the best performance at medium resolution (5 m), outperforming both higher (0.4 m) and lower resolution (10 m) models. This transcends our study to show that permafrost response to climate change may vary across dominant ecosystem types, driven by different above- and below-ground connections and the scales at which these connections are happening. We thus recommend tailoring observational scales based on landforms and characteristics for modeling permafrost distribution, thereby mitigating the influences of spatial-scale mismatches and improving the understanding of vegetation and permafrost changes for the Arctic region.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Recovering Rare Earth Elements from Coal Mine Drainage Using Industrial Byproducts: Environmental and Economic Consequences

Coal mine drainage (CMD) impairs tens of thousands of kilometers of U.S. waterways each year, in part with the leaching of low concentrations of rare earth elements (REEs). REEs are essential for modern technologies, yet economically viable natural deposits are geospatially limited, thus engendering geopolitical concerns, and their mining is energy intense and environmentally destructive. This work summarizes laboratory-scale experimentalresults of a trap-extract-precipitate (TEP) process and uses the mass and energy balances to estimate the economic costs and environmental impacts of the TEP. The TEP process uses the alkalinity and filtering capacity of stabilized flue gas desulfurization (sFGD) material or water treatment plant (WTP) sludge to remediate CMD waters and extract REEs. Passive treatment systems that use WTP sludge are cheaper than those that use sFGD material ($\$$89,300/year or $\$$86/gT-REE vs. $\$$89,800/year or $\$$278/gT-REE) and have improved environmental performance across all indicators from two different impact assessment methods. These differences are largely attributable to the larger neutralizing capacity of WTP sludge in the treatment application.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2020

GW190412: Observation of a binary-black-hole coalescence with asymmetric masses

We report the observation of gravitational waves from a binary-black-hole coalescence during the first two weeks of LIGO's and Virgo's third observing run. The signal was recorded on April 12, 2019 at 05:30:44 UTC with a network signal-to-noise ratio of 19. The binary is different from observations during the first two observing runs most notably due to its asymmetric masses: A ~30 M ⊙ black hole merged with a ~8 M ⊙ black hole companion. The more massive black hole rotated with a dimensionless spin magnitude between 0.22 and 0.60 (90% probability). Asymmetric systems are predicted to emit gravitational waves with stronger contributions from higher multipoles, and indeed we find strong evidence for gravitational radiation beyond the leading quadrupolar order in the observed signal. A suite of tests performed on GW190412 indicates consistency with Einstein's general theory of relativity. While the mass ratio of this system differs from all previous detections, we show that it is consistent with the population model of stellar binary black holes inferred from the first two observing runs.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Measurements of Chemical Potentials in Pb-Pb Collisions at $\sqrt{s_{NN}}$=5.02 TeV

This Letter presents the most precise measurement to date of the matter-antimatter imbalance at midrapidity in Pb-Pb collisions at a center-of-mass energy per nucleon pair $\sqrt{s_{NN}}$ = 5.02 TeV. Using the Statistical Hadronization framework, it is possible to obtain the value of the electric charge and baryon chemical potentials, μ Q = -0.18 ± 0.90 MeV and μ B = 0.71 ± 0.45 MeV, with unprecedented precision. A centrality-differential study of the antiparticle-to-particle yield ratios of charged pions, protons, Ω baryons, and light (hyper)nuclei is performed. These results indicate that the system created in Pb-Pb collisions at the LHC is on average baryon-free and electrically neutral at midrapidity.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Cryogenic Hydrogen Fuel for Controlled Inertial Confinement Fusion (Cryogenic Target Factory Concept Based on FST-Layering Method)

A central element of a power plant based on inertial confinement fusion (ICF) is a target with cryogenic hydrogen fuel that should be delivered to the center of a reactor chamber with a high accuracy and repetition rate. Therefore, a cryogenic target factory (CTF) is an integral part of any ICF reactor. A promising way to solve this problem consists in the FST layering method developed at the Lebedev Physical Institute (LPI). This method (rapid fuel layering inside moving free-standing targets) is unique, having no analogs in the world. The further development of FST-layering technologies is implemented in the scope of the LPI program for the creation of a modular CTF and commercialization of the obtained results. In this report, we discuss our concept of CTF (CTF-LPI) that exhibits the following distinctive features: using a FST-layering technology for the elaboration of an in-line production of cryogenic targets, using an effect of quantum levitation of high-temperature superconductors (HTSCs) in magnetic field for noncontacting manipulation, transport, and positioning of the free-standing cryogenic targets, as well as in using a Fourier holography technique for an on-line characterization and tracking of the targets flying into the reactor chamber. The results of original experimental and theoretical investigations performed at LPI indicate that the existing and developing target fabrication capabilities and technologies can be applied to ICF target production. The unique scientific, engineering, and technological base developed in Russia at LPI allows one to make a CTFLPI prototype for mass production of targets and delivery thereof at the required velocity into the ICF reactor chamber.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Streaming Data from Experimental Facilities to Supercomputers for Real-Time Data Processing

In this paper we demonstrate direct data streaming from instruments and detectors at a large-scale experimental facility to a supercomputer for real-time data processing and feedback. Streaming data to supercomputers introduces the potential for novel scientific applications and workflow models, including the ability to provide real-time feedback from very large datasets during an experiment and the integration of real-time ML training and inference at scale. We discuss a successful demonstration for real-time processing of data from the Advanced Photon Source (APS) on the Polaris supercomputer using an EPICS-based streaming framework. We describe the capabilities of the streaming framework itself, and outline the architecture that allows us to process experimentally derived data on a supercomputer without file-based data transfers. We present throughput measurements that are indicative of system performance capable of sustaining the expected data production rates of the facility, as well as discuss some outstanding challenges and our future directions.

real-time processing↗