Search NASA⌕ Search

SEARCH · Search NASA

Results for “Class generation”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Review of the U.S. Department of Energy's "Deep Dive" Effort to Understand Voltage Fade in Li- and Mn-rich Cathodes

With roughly two-thirds of daily oil consumption in the United States allotted for transportation, the possibility of efficient and affordable electric vehicles suggests a way to substantially alleviate the Country’s dependence on oil and mitigate the rise of greenhouse gases. Although commercialized Li-ion batteries do not currently meet the stringent demands of a would-be, economically competitive, electrified vehicle fleet, significant efforts are being focused on promising new materials for the next generation of Li-ion batteries. The leading class of materials most suitable for the challenge is the Li- and manganese-rich class of oxides. Denoted as LMR-NMC (Li-manganese-rich, nickel, manganese, cobalt), these materials could significantly improve energy densities, cost, and safety, relative to state-of-the-art Ni- and Co-rich Li-ion cells, if successfully developed.1 The success or failure of such a development relies heavily on understanding two defining characteristics of LMR-NMC cathodes. The first is a mechanism whereby the average voltage of cells continuously decreases with each successive charge and discharge cycle. This phenomenon, known as voltage fade, decreases the energy output of cells to unacceptable levels too early in cycling. The second characteristic is a pronounced hysteresis, or voltage difference, between charge and discharge cycles. The hysteresis represents not only an energy inefficiency (i.e., energy in vs energy out) but may also complicate the state of charge/depth of discharge management of larger systems, especially when accompanied by voltage fade. n 2012, the United States Department of Energy’s Office of Vehicle Technologies, well aware of the inherent potential of LMR-NMC materials for improving the energy density of automotive energy storage systems, tasked a team of scientists across the National Laboratory Complex to investigate the phenomenon of voltage fade. Unique studies using synchrotron X-ray absorption (XAS) and high-resolution diffraction (HR-XRD) were coupled with nuclear magnetic resonance spectroscopy (NMR), neutron diffraction, high-resolution transmission electron microscopy (HR-TEM), first-principles calculations, molecular dynamics simulations, and detailed electrochemical analyses. These studies demonstrated for the first time the atomic-scale, structure–property relationships that exist between nanoscale inhomogeneities and defects, and the macroscale, electrochemical performance of these layered oxides. These inhomogeneities and defects have been directly correlated with voltage fade and hysteresis, and a model describing these mechanisms has been proposed. This Account gives a brief summary of the findings of this recently concluded, approximately three-year investigation. Lastly, the interested reader is directed to the extensive body of work cited in the given references for a more comprehensive review of the subject.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Increasing the Scale of the Mass Spectrometry Query Language Compendium with Explainable AI

A significant bottleneck in metabolomics data interpretation is the effective use of domain knowledge to assign structural information based on fragmentation patterns. The mass spectrometry query language (MassQL) aims to make this process accessible and applicable across multiple analysis platforms. While advanced computational methods are capable of predicting compound structures from fragmentation data, AI/ML approaches often rely on complex, opaque criteria that are difficult to interpret or modify. As a result, their predictive patterns cannot be readily translated into human-readable rules, such as those used in MassQL. Here, in this study, we introduce ChemEcho, a machine learning embedding method that converts tandem mass spectrometry data into sparse feature vectors containing peak and neutral mass subformulae to enhance explainable AI/ML-based methods. An advantage of this approach is that decision trees trained using these feature vectors can be directly translated to MassQL. Using a battery of decision trees trained using ChemEcho embeddings to predict molecular attributes, we generated over 1500 MassQL queries for 765 molecular features and evaluated their precision and recall. From these queries, the 50 highest-performing queries were integrated into the MassQL compendium. This set of generated MassQL queries included environmentally and biologically relevant classes such as PFAS and molecules containing phosphate or sulfate substructures. To illustrate the impact these queries would have on a typical metabolomics experiment, these MassQL queries were applied to a public metabolomics data set─resulting in a marked increase in the structural information derived from tandem mass spectra. Access and reuse of these queries is expected to enhance structural annotation in untargeted experiments, leading to more specific claims and advancing many applications in metabolomics.

Harwood, Thomas V. [USDOE Joint Genome Institute (↗
DOE OSTI2017

Controlling Pu behavior on Titania: Implications for LEU Fission-Based Mo-99 Production

Molybdenum-99 is the parent isotope of the most widely used isotope, technetium-99m, in all diagnostic nuclear medicine procedures. Due to proliferation concerns associated with the use of highly enriched uranium (HEU), the preferred method of fission-based Mo-99 production uses low enriched uranium (LEU) targets. Using LEU versus HEU for Mo-99 production produces similar to 30 times more Pu-239, due to neutron capture on U-238 to produce Np-239, which ultimately decays to Pu-239 (t(1/2) = 24,110 yr). Argonne National Laboratory is supporting a potential US Mo-99 producer in their efforts to produce Mo-99 from an LEU solution. In order to mitigate the generation of large volumes of greater-than-class-C (GTCC) low level waste (Pu-239 concentrations greater than 1 nCi/g), we have focused our efforts on the separation chemistry of Pu and Mo with a titania sorbent in sulfate media. Results from batch and column experiments show that temperature and acid wash concentration can be used to control Pu behavior on titania.

low enriched uranium↗
DOE OSTI2025

Monitoring Fracture Hydromechanical Evolution in the Lab and Field Using Unsupervised Metric Learning

Fractures evolve in time through thermal‐hydraulic‐mechanical‐chemical (THMC) processes that alter their long‐range hydraulic transport properties and modify subsurface behavior and activities. The location of subsurface fractures makes it necessary to use remote sensing techniques such as passive or active seismic monitoring for fracture characterization. In this paper, we develop a machine learning approach to monitor the evolution of fracture properties using passive seismic sources in a laboratory setting and using active seismic monitoring from the Sanford Underground Research Facility in Lead, South Dakota, at a depth of 1.25 km in amphibolite rock during stimulation of natural fractures as well as during induced fracturing. The unsupervised metric learning technique applies tandem neural networks (twin (Siamese) or triplet) with contrastive loss and adaptive margins to track slowly varying systems for which class or similarity labels are not available. The approach adopts locality‐sensitive hashing to divide time‐ordered contiguous data into an arbitrary number of pseudo‐classes. Contrastive‐loss training with many hash bins generates an evolving latent‐space trajectory. This approach enables unsupervised metric learning for seismic data stacks under the condition of contiguous state sampling and slowly varying fracture properties. The displacement discontinuity theory provides a mechanistic foundation for the fracture‐dependent trajectories that are related to relaxation of fractures with time‐dependent specific stiffness responding to changes in stress or fluid saturation.

02 PETROLEUM↗
DOE OSTI2017

Note: Infrared laser diagnostics for deuterium gas puff Z pinches

Deuterium gas puff Z pinches have been used for generation of strong neutron fluxes on the MA class pulse power machines. Due to the low electron density of deuterium Z-pinch plasma, regular laser diagnostics in the visible range cannot be used for observation and study of the pinch. Laser probing at the wavelength of 1064 nm was used for visualization of deuterium plasma. Finally, infrared schlieren and interferometry diagnostics showed the deuterium gas puff plasma dynamics, instabilities, and allowed for the reconstruction of the profile of the plasma density.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

CORONAL RESPONSE TO AN EUV WAVE FROM DEM ANALYSIS

Extreme-Ultraviolet (EUV) waves are globally propagating disturbances that have been observed since the era of the Solar and Heliospheric Observatory/Exteme-ultraviolet Imaging Telescope instrument. Although the kinematics of the wave front and secondary wave components have been widely studied, there is not much known about the generation and plasma properties of the wave. In this paper we discuss the effect of an EUV wave on the local plasma as it passes through the corona. We studied the EUV wave, generated during the 2011 February 15 X-class flare/coronal mass ejection event, using Differential Emission Measure diagnostics. We analyzed regions on the path of the EUV wave and investigated the local density and temperature changes. From our study we have quantitatively confirmed previous results that during wave passage the plasma visible in the Atmospheric Imaging Assembly (AIA) 171 Å channel is getting heated to higher temperatures corresponding to AIA 193 and 211 Å channels. We have calculated an increase of 6%–9% in density and 5%–6% in temperature during the passage of the EUV wave. We have compared the variation in temperature with the adiabatic relationship and have quantitatively demonstrated the phenomenon of heating due to adiabatic compression at the wave front. However, the cooling phase does not follow adiabatic relaxation but shows slow decay indicating slow energy release being triggered by the wave passage. We have also identified that heating is taking place at the front of the wave pulse rather than at the rear. Our results provide support for the case that the event under study here is a compressive fast-mode wave or a shock.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Proton beam emittance growth in multipicosecond laser-solid interactions

High intensity laser-solid interactions can accelerate high energy, low emittance proton beams via the target normal sheath acceleration (TNSA) mechanism. Such beams are useful for a number of applications, including time-resolved proton radiography for basic plasma and high energy density physics studies. In experiments using the OMEGA EP laser system, we perform the first measurements of TNSA proton beams generated by up to 100 ps, kilojoule-class laser pulses with relativistic intensities. By systematically varying the laser pulse duration, we measure degradation of the accelerated proton beam quality as the pulse length increases. Two dimensional particle-in-cell simulations and simple scaling arguments suggest that ion motion during the rise time of the longer pulses leads to extended preformed plasma expansion from the rear target surface and strong filamentary field structures which can deflect ions away from uniform trajectories and therefore lead to large emittance growth.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Large covariance matrices: accurate models without mocks

Abstract Covariance matrix estimation is a persistent challenge for cosmology. We focus on a class of model covariance matrices that can be generated with high accuracy and precision, using a tiny fraction of the computational resources that would be required to achieve comparably precise covariance matrices using mock catalogues. In previous work, the free parameters in these models were determined using sample covariance matrices computed using a large number of mocks, but we demonstrate that those parameters can be estimated consistently and with good precision by applying jackknife methods to a single survey volume. This enables model covariance matrices that are calibrated from data alone, with no reference to mocks.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Investigation of the photoluminescent properties, scintillation behaviour and toxicological profile of various magnesium tungstate nanoscale motifs

We have synthesized several morphologies and crystal structures of MgWO 4 using a one-pot hydrothermal method, producing not only monoclinic stars and large nanoparticles but also triclinic wool balls and sub-10 nm nanoparticles. Herein we describe the importance of reaction parameters in demonstrating morphology control of as-prepared MgWO 4 . Moreover, we correlate structure and composition with the resulting photoluminescence and radioluminescence properties. Specifically, triclinic-phase samples yielded a photoluminescence emission of 421 nm, whereas monoclinic-phase materials gave rise to an emission maximum of 515 nm. The corresponding radioluminescence data were characterized by a broad emission peak, located at 500 nm for all samples. Annealing the wool balls and sub-10 nm particles to transform the crystal structure from a triclinic to a monoclinic phase yielded a radioluminescence (RL) emission signal that was two orders of magnitude greater than that of their unannealed counterparts. Finally, to confirm the practical utility of these materials for biomedical applications, a series of sub-10 nm particles, including as-prepared and annealed samples, were functionalized with biocompatible PEG molecules, and subsequently were found to be readily taken up by various cell lines as well as primary cultured hippocampal neurons with low levels of toxicity, thereby highlighting for the first time the potential of this particular class of metal oxides as viable and readily generated platforms for a range of biomedical applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

A metric framework for evaluating the resilience contribution of hydropower to the grid

This paper will describe a proposed framework for expressing the resilience of hydropower generation and provide initial case studies for three classes of hydropower, run-of-river hydropower, hydropower with reservoirs, and pumped storage hydropower. Hydropower has great flexibility to provide support during and after natural and man-made events that can disrupt critical infrastructure functionality. The concept of the framework provides for consideration of policy and rules, constraints of the water shed and other allocations of water, storage and plant capabilities to produce real and reactive power, and the strength of the delivery network. The paper details a resilience response metric that has inputs of state of storage and plant level constraints on real and reactive power production. Using the definition of resilience, based on maintaining a minimally normal operations, we provide a qualitative assessment of hydropower’s ability to address the various time scales comprising the “R”s of resilience.

13 HYDRO ENERGY↗
DOE OSTI2024

Investigation of Proton Beam-Driven Fusion Reactions Generated by an Ultra-Short Petawatt-Scale Laser Pulse

We present results from a pitcher-catcher experiment utilizing a proton beam generated with nanostructured targets at a petawatt-class, short-pulse laser facility to induce proton-boron fusion reactions in a secondary target. A 45-fs laser pulse with either 400 nm wavelength and 7 J energy, or 800 nm and 14 J, and an intensity of up to 5 × 10 21 W/cm 2 was used to irradiate either thin foil targets or near-solid density, nanostructured targets made of boron nitride (BN) nanotubes. In particular, for 800 nm wavelength irradiation, a BN nanotube target created a proton beam with about five times higher maximum energy and about ten times more protons than a foil target. This proton beam was used to irradiate a thick plate made of boron nitride placed in close proximity to trigger 11 B (p, α) 2α fusion reactions. A suite of diagnostics consisting of Thomson parabola ion spectrometers, postshot nuclear activation measurements, neutron time-of-flight detectors, and differentially filtered solid-state nuclear track detectors were used to measure both the primary proton spectrum and the fusion products. From the primary proton spectrum, we calculated (p, n) and (α,n) reactions in the catcher and compare with our measurements. The nuclear activation results agree quantitatively and neutron signals agree qualitatively with the calculations, giving confidence that primary particle distributions can be obtained from such measurements. These results provide new insights for measuring the ion distributions inside of proton-boron fusion targets.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Classification of River Catchments in the Contiguous United States: Code, Dataset, Similarity Patterns, and Resulting Classes

This dataset serves as supplementary information for the paper by Ciulla F. and Varadharajan C. A Network Approach for Multiscale Catchment Classification using Traits (see reference 1). It contains environmental and physical catchment traits, such as temperatures, precipitation, land use and human interference, from 9067 sites across the contiguous United States (CONUS). The purpose of this dataset is to provide information for a better trait-based categorization of river catchments in the CONUS using networks as an analytical tool. The traits variables match the ones present in the GAGES-II dataset and the preprocessing steps are described in the Methods section (processed_dataset.csv). Additionally we include the topologies (nodes, edges and clusters, also referred as classes) of the catchment network and traits network generated by said dataset (csv and json files). A series of tables support the information carried by the network providing more detailed descriptions of cluster components (SI1.pdf). A summary of all the plots of clusters of catchments with at least 50 nodes is provided (SI2.pdf). The characteristic traits for each cluster of catchments is presented as z-score (traits_categories_zscores_per_catchment_class.csv). The link to the hydrological behavior of clusters of catchments is displayed by boxplots, each describing a particular river discharge index (SI3.pdf). Both csv and json files can be read by common text editors but the data contained into them can be better handled using programming languages like python and database oriented libraries like pandas. Pdf files can be read by any pdf reader software.[02-23-2024] Update: The code and datasets necessary to reproduce the results of the study are available as a zipped repository (code_datasets_catchments_similarity.zip).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Identification of a Class of WNK Isoform-Specific Inhibitors Through High-Throughput Screening

Introduction: WNK [with no lysine (K)] kinases are serine/threonine kinases associated with familial hyperkalemic hypertension (FHHt). WNKs are therapeutic targets for blood pressure regulation, stroke and several cancers including triple negative breast cancer and glioblastoma. Here, we searched for and characterized novel WNK kinase inhibitors. Methods: We used a ~210,000-compound library in a high-throughput screen, re-acquisition and assay, commercial specificity screens and crystallography to identify WNK-isoform-selective inhibitors. Results: We identified five classes of compounds that inhibit the kinase activity of WNK1: quinoline compounds, halo-sulfones, cyclopropane-containing thiazoles, piperazine-containing compounds, and nitrophenol-derived compounds. The compounds are strongly pan-WNK selective, inhibiting all four WNK isoforms. A class of quinoline compounds was identified that further shows selectivity among the WNK isoforms, being more potent toward WNK3 than WNK1. The crystal structure of the quinoline-derived SW120619 bound to the kinase domain of WNK3 reveals active site binding, and comparison to the WNK1 structure reveals the potential origin of isoform specificity. Discussion: The newly discovered classes of compounds may be starting points for generating pharmacological tools and potential drugs treating hypertension and cancer.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

New Design Methods And Algorithms For High Energy-Efficient And Low-cost Distillation Processes

This project sought and successfully answered two big challenges facing the creation of low-energy, cost-effective, zeotropic multi-component distillation processes: first, identification of an efficient search space that includes all the useful distillation configurations and no undesired configurations; second, development of an algorithm to search the space efficiently and generate an array of low-energy options for industrial multi-component mixtures. Such mixtures are found in large-scale chemical and petroleum plants. Commercialization of our results was addressed by building a user interface allowing practical application of our methods for industrial problems by anyone with basic knowledge of distillation for a given problem. We also provided our algorithm to a major U.S. Chemical Company for use by the practitioners. The successful execution of this program has provided methods and algorithms at the disposal of process engineers to readily generate low-energy solutions for a large class of multicomponent distillation problems in a typical chemical and petrochemical plant. In a petrochemical complex, the distillation trains within crude oil processing, hydrotreating units containing alkylation, isomerization, reformer, LPG (liquefied petroleum gas) and NGL (natural gas liquids) processing units can benefit from our results. Effluents from naphtha crackers and ethane-propane crackers typically contain mixtures of methane, ethylene, ethane, propylene, propane, butane and heavier hydrocarbons. We have shown that our systematic search method with a more complete search space, along with the optimization algorithm, has a potential to yield low-energy distillation configurations for all such applications with energy savings up to 50%.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

New Design Methods and Algorithms for Energy Efficient Multicomponent Distillation Column Trains (Final Report)

The major objectives of this project are to; first develop new methods and tools, and then incorporate them in a user-friendly software that will readily generate low-energy solutions for a large class of multicomponent distillation applications found in typical chemical and petrochemical plants. Having such methods and corresponding software at the disposal of the process engineers will allow chemical manufacturers of all sizes to reduce energy consumption of their grassroots as well as existing separation plants.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

High Pressure Synthesis of New Magnets, Featuring Diamagnetic Sources of Anisotropy

Permanent magnets are the functional component of electric motors and generators found in numerous renewable energy applications spanning from regenerative brakes to wind turbines. Magnets that generate higher magnetic flux per volume are central to improved energy generation in these applications. To develop a new class of permanent magnets while retaining the properties conferred by rare-earth elements, a fundamentally different approach is required. We hypothesize that by engendering a covalent interaction between two elements, it will be possible to interact the two components of a magnetic moment—spin and orbital angular momentum—from two separate atoms to form a complete magnetic moment. This seed project focuses on the scale up of the compound FeBi 2 , which was initially synthesized in our laboratory. Scale up approaches include slow decompression, alternate synthetic routes, and using fabrication approaches to more intimately mix the precursor elements. We also pursued the synthesis of new phases in the Mn-Bi system targeted to create new magnetic materials. In our initial experiments we decompressed FeBi 2 down to 2.9 GPa, demonstrating a kinetic stability to the phase that enabled it to be recovered to an order of magnitude lower pressure than that needed to synthesize it (30 GPa). Our goal is to recover this exciting material to ambient pressures so that we can isolate samples for detailed physical properties measurements. We have undertaken three distinct approaches toward that goal, which we summarize below. Our two most notable results are the formation of a quenchable phase through antimony doping of FeBi 2 , and the development of a new approach to preparing samples for diamond anvil cell syntheses.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Variable Effects of Dispersed Nanoparticles on Triboelectric Nanogenerators

Technology has recently seen a drastic physical downsizing. Wearable and small devices with lower power demands have become the norm and continue to be more prominent in daily life. With modern devices growing smaller and requiring less electricity, a power source will always be needed. Contemporary batteries are the most common means to power small electronics. However, reliance on conventional batteries may prove insufficient due to the non renewable resources (Li, Ni, Co) required to power the growing number of individual devices each person may own. Additionally, the infrastructure required to harvest and recycle the sheer number of batteries produced presents a further logistic issue to be addressed. A promising alternative to batteries is the usage of triboelectric nanogenerators (TENGs). TENGs are a class of energy harvesting devices that utilize triboelectric generation to convert mechanical/kinetic energy into electrical energy and have exhibited efficiencies up to 85 % at low frequencies. TENGs exhibit a high voltage but low current. Even with the high voltage, the low current output proves to be a significant factor preventing undoped TENGs from being commercially viable. This review will investigate factors that increase the total current produced by TENGs when nanoparticles are utilized in TENGs. Factors such as increasing porosity, surface area, surface charge density, charge storage, deep trap formation, and dielectric constant can be altered to affect the total current by impregnating nanoparticles into the polymer material will be explored.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Variable Effects of Dispersed Nanoparticles on Triboelectric Nanogenerators

Technology has recently seen a drastic physical downsizing. Wearable and small devices with lower power demands have become the norm and continue to be more prominent in daily life. With modern devices growing smaller and requiring less electricity, a power source will always be needed. Contemporary batteries are the most common means to power small electronics. However, reliance on conventional batteries may prove insufficient due to the non renewable resources (Li, Ni, Co) required to power the growing number of individual devices each person may own. Additionally, the infrastructure required to harvest and recycle the sheer number of batteries produced presents a further logistic issue to be addressed. A promising alternative to batteries is the usage of triboelectric nanogenerators (TENGs). TENGs are a class of energy harvesting devices that utilize triboelectric generation to convert mechanical/kinetic energy into electrical energy and have exhibited efficiencies up to 85 % at low frequencies. TENGs exhibit a high voltage but low current. Even with the high voltage, the low current output proves to be a significant factor preventing undoped TENGs from being commercially viable. This review will investigate factors that increase the total current produced by TENGs when nanoparticles are utilized in TENGs. Factors such as increasing porosity, surface area, surface charge density, charge storage, deep trap formation, and dielectric constant can be altered to affect the total current by impregnating nanoparticles into the polymer material will be explored.

42 ENGINEERING↗