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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A knock-on deuteron imager for measurements of fuel and hotspot asymmetry in direct-drive inertial confinement fusion implosions (invited)

A knock-on deuteron imager (KoDI) has been implemented to measure the fuel and hotspot asymmetry of cryogenic inertial confinement fusion implosions on OMEGA. Energetic neutrons produced by D–T fusion elastically scatter (“knock on”) deuterons from the fuel layer with a probability that depends on ρR. Deuterons above 10 MeV are produced by near-forward scattering, and imaging them is equivalent to time-integrated neutron imaging of the hotspot. Deuterons below 6 MeV are produced by a combination of side scattering and ranging in the fuel, and encode information about the spatial distribution of the dense fuel. Here, the KoDI instrument consists of a multi-penumbral aperture positioned 10–20 cm from the implosion using a ten-inch manipulator and a detector pack at 350 cm from the implosion to record penumbral images with magnification of up to 35×. Range filters and the intrinsic properties of CR-39 are used to distinguish different charged-particle images by energy along the same line of sight. Image plates fielded behind the CR-39 record a 10 keV x-ray image using the same aperture. A maximum-likelihood reconstruction algorithm has been implemented to infer the source from the projected penumbral images. The effects of scattering and aperture charging on the instrument point-spread function are assessed. Synthetic data are used to validate the reconstruction algorithm and assess an appropriate termination criterion. Significant aperture charging has been observed in the initial experimental dataset, and increases with aperture distance from the implosion, consistent with a simple model of charging by laser-driven EMP.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Non-Electricity Based Renewable Fuels: Theory and Computation for Solar Thermochemical Hydrogen

Dominated by photovoltaics and wind, current renewable energy sources generate mostly electricity, but 80% of the global final energy consumption occurs in form of fuels. Therefore, direct solar fuel generation would be a major breakthrough for the energy transition. Solar thermochemical hydrogen (STCH) is one of the very few potential routes towards scalable renewable fuels, but currently suffers from lack of an oxide working material that could optimally perform energy conversion within the thermodynamic boundary conditions. Theory and computation can contribute in two distinct ways, through materials search and discovery, but also by providing detailed mechanistic models for specific systems so to advance our understanding of possible design strategies. To enable high-throughput materials screening, we developed a defect graph neural network (dGNN) machine learning approach,[1] which accelerates the prediction of defect formation energies by replacing the tedious density functional theory (DFT) supercell calculations for all possible defect sites. This approach enables high-throughput database screening of oxides, which was integrated with thermodynamic modeling to extract the reduction entropies as additional selection criterion for STCH. Once potential candidate materials are identified, detailed models can guide materials design by predicting performance characteristics. One challenge is to quantitatively predict thermochemical equilibria at high concentrations when the redox active defects start to interact with each other, thereby impeding the formation of additional defects. Introducing a model for the free energy of defect interaction, parametrized on the basis of DFT data, we simulated the complete STCH redox cycle for (Sr,Ce)MnO3 alloys, achieving near-quantitative agreement with experimental data.[2] The analysis of these simulations reveals how defect interactions diminish the reduction entropy and H2 yield, suggesting to include these interactions in design considerations. Finally, we revisit the popular van't Hoff method for analyzing reduction enthalpies and entropies. This method is not ideal, as it involves a temperature-dependent convolution of gas-phase and solid-state entropies, causing uncertainties in the same order of magnitude as the physical quantities of interest. To avoid this problem, we suggest a simple alternative approach which can be applied to experimental and simulated data alike.

first-principles calculations↗
DOE OSTI2026

Elucidating the Structural and Electronic Effects of Ni and Mn Cationic Incorporation on CoOOH for Efficient Benzyl Alcohol Electrooxidation

Transition-metal oxyhydroxides such as CoOOH are promising low-cost electrocatalysts for the selective electrooxidation of organic molecules, yet the influence of ubiquitous transition-metal impurities on their performance and durability remains poorly understood. Here, we experimentally probed the individual and synergistic electrochemical and structural effects of Ni and Mn incorporations into model CoOOH electrocatalysts toward an efficient benzyl alcohol oxidation reaction (BAOR). Comprehensive electrochemical, microscopic, and spectroscopic analyses reveal that Ni incorporation enhances charge-transfer kinetics and overall activity through the formation of catalytically active Ni 3+ sites, whereas Mn exhibited a more complex but interesting role. At the early stages of operation, Mn 4+ acts as a stabilizing surface layer that mitigates catalyst degradation but partially blocks Co sites before they undergo gradual leaching. The concurrent incorporation of both Ni and Mn yields a trimetallic 2NMC@NF electrocatalyst that integrates the activity benefits of Ni with the stability conferred by Mn, achieving 92.9% benzyl alcohol conversion and 91.4% Faradaic efficiency after 24 h at 1.5 V vs RHE. These findings elucidate how trace Ni and Mn impurities, often introduced from electrolytes or external sources, can modulate the lattice and electronic structure of CoOOH, offering a design strategy for enhancing both activity and long-term stability in electrocatalytic organic oxidation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Proposed Analytical Methods for Determining Filter Media Properties

High Efficiency Particulate Air (HEPA) filters, commonly used in nuclear filtration applications, are an integral part of the waste management processes in nuclear plants. HEPA filters are 99.97% efficient filtration devices characterized by their high resistance to air flow, or pressure drop. From theoretical models, the initial pressure drop across a clean filter is proven to be a function of the filter media fiber diameters and porosity of the media. These filter properties are relatively difficult to obtain with traditional manual methods; therefore, there is a need to develop analytical methods to find the fiber diameter and porosity to determine the pressure drop. Typically, these values can be found by substituting a calculated representative value based upon measured values, such as equivalent fiber diameter based upon a clean pressure drop. However, these values may also be directly recorded and measured by incorporating Scanning Electron Microscope (SEM) image analysis and other measurement methods to analyze the filter media and determine its physical properties without the need for media testing. DiameterJ, an open source Java plug-in, used with ImageJ, can process images of filter media taken by an SEM to find statistical data such as mean fiber diameter and porosity. To produce the raw data, SEM images of two filter media type samples are taken and segmented in DiameterJ using the traditional and statistical region merging segmentation algorithms. Manual segmentation is necessary after the initial segmentation by the algorithms as the images tend to be too complex for the algorithms to output with the necessary accuracy. However, complications exist in the manual segmentation process as these methods can be time intensive and prone to the individual bias of the user. This in turn can skew the final mean fiber diameter result, and lead to either an over or under prediction of the pressure drop. It was also discovered that the porosity data produced by DiameterJ is inaccurate, as the SEM analyzes the three-dimensional filter media by projecting its geometry onto a plane and analyzing it as a two-dimensional binary image. Thus, the porosity is artificially inflated through the segmentation process, rendering this result incorrect. Alternatively, density determination, gravimetric analysis, and thickness testing of the filter media is collectively used to determine the filter fiber porosity. Together, the SEM image analysis and analytical lab methods produce results through direct measurements which allow for the prediction of the initial pressure drop from clean filter media without the need for prior media testing to collect pressure data. By improving upon this proposed analytical method in the future, there is potential to streamline the process of finding these filter properties into a more direct methodology for determining the pressure drop across HEPA filters.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

In vitro characterization of the antivirulence target of Gram-positive pathogens, peptidoglycan O-acetyltransferase A (OatA)

The O-acetylation of the essential cell wall polymer peptidoglycan occurs in most Gram-positive bacterial pathogens, including species of Staphylococcus, Streptococcus and Enterococcus. This modification to peptidoglycan protects these pathogens from the lytic action of the lysozymes of innate immunity systems and, as such, is recognized as a virulence factor. The key enzyme involved, peptidoglycan O-acetyltransferase A (OatA) represents a particular challenge to biochemical study since it is a membrane associated protein whose substrate is the insoluble peptidoglycan cell wall polymer. OatA is predicted to be bimodular, being comprised of an N-terminal integral membrane domain linked to a C-terminal extracytoplasmic domain. We present herein the first biochemical and kinetic characterization of the C-terminal catalytic domain of OatA from two important human pathogens, Staphylococcus aureus and Streptococcus pneumoniae. Using both pseudosubstrates and novel biosynthetically-prepared peptidoglycan polymers, we characterized distinct substrate specificities for the two enzymes. In addition, the high resolution crystal structure of the C-terminal domain reveals an SGNH/GDSL-like hydrolase fold with a catalytic triad of amino acids but with a non-canonical oxyanion hole structure. Site-specific replacements confirmed the identity of the catalytic and oxyanion hole residues. A model is presented for the O-acetylation of peptidoglycan whereby the translocation of acetyl groups from a cytoplasmic source across the cytoplasmic membrane is catalyzed by the N-terminal domain of OatA for their transfer to peptidoglycan by its C-terminal domain. This study on the structure-function relationship of OatA provides a molecular and mechanistic understanding of this bacterial resistance mechanism opening the prospect for novel chemotherapeutic exploration to enhance innate immunity protection against Gram-positive pathogens.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Optimization of the moderators in the STS preliminary design

This report details the results for an optimization of the dimensions of the moderators in the preliminary design of the Spallation Neutron Source Second Target Station (STS). This study uses the optimization algorithms of Dakota and an unstructured mesh model for the moderators in MCNP. More details on the unstructured mesh model and the automated mesh generation can be found in [3]. Parallel to this effort, the same moderator geometries have been optimized using a constructive solid geometry (CSG) MCNP model. More details on this model and its results can be found in [4]. Three optimal designs are selected for each moderator: one that is optimized for maximum peak brightness, one for maximum time-integrated brightness, and one for a combination of peak and time-integrated brightness. The backbone of the optimization work flow is provided by Dakota. For each set of design parameters requested by Dakota, a new solid geometry is automatically built in Creo and SpaceClaim, and subsequently exported to Attila4MC to generate an unstructured mesh geometry for MCNP. After the MCNP calculation is finished, the objective function (e.g., brightness metric) is returned to Dakota. After the new design has been evaluated, a result-file is written, and Dakota proposes the next set of design parameters to be evaluated. The loop continues until a specified convergence criterion has been met. The design parameters of the cylindrical (upper) moderator include the hydrogen radius, the premoderator thickness (top, bottom, radial), the beryllium radius and the horizontal position of the moderator. The crucial design choice is the hydrogen radius. A radius of 62 mm is shown to provide the maximum time-integrated brightness. The maximum peak brightness occurs with a radius of 40 mm. A combined (middle) design, which balances peak and time-integrated brightnesses, is obtained with a hydrogen radius of 50 mm. The premoderator thicknesses and the beryllium radius are slightly larger in the design optimized for time-integrated brightness than in the design optimized for peak brightness. The sensitivity to these two parameters is relatively small close to the optimal configurations. The hydrogen vessel and vacuum vessel wall thicknesses are dependent on the radius of the liquid hydrogen due to structural integrity requirements. The increased wall thicknesses for larger vessels significantly penalize the time-integrated brightness, with the maximum obtainable value reduced by more than 10% relative to earlier studies which used fixed vessel wall thicknesses. The impact of the variable wall thicknesses is much less for the peak brightness and combined brightness designs. The design parameters of the tube (lower) moderator selected for the optimization are the tube length, the annular premoderator thickness, the beryllium radius and the horizontal position of the moderator. The tube length is the crucial parameter and is chosen large (210 mm) and small (125 mm) in the designs optimized for time-integrated and peak brightness respectively. A combined optimal design has a tube length of 170 mm. The premoderator thickness and the beryllium radius are chosen larger in the design optimized for time-integrated brightness.

42 ENGINEERING↗
DOE OSTI2020

Capabilities of multivariate Bayesian inference toward seismic hazard assessment

Multivariate Bayesian analysis can bring significant benefits to seismic hazard analysis: Its multivariate feature enables computing scalar and vector hazard without making any approximations; Correlations between intensity measures are implicitly modeled, permitting direct simulation of ground motion selection tools such as the conditional mean spectrum and the generalized conditioning intensity measure; and Its updating feature enables a seamless integration of new ground motion data into the hazard results. Here, we first develop a multivariate Bayesian ground motion model through the NGA-West2 database. The model functional form considers fault-type, magnitude, and distance dependencies, and also the linear and the rock intensity dependent site response. We use a hybrid Markov Chain Monte Carlo sampling to perform Bayesian inference consisting of Gibbs step and a multilevel Metropolis-Hastings step. We then perform several checks on the model and note that its performance is satisfactory. Finally, we illustrate the merits of this multivariate Bayesian analysis, which include: ground motion model updating with ground motion data recorded in the last four years not part of the NGA-West2 database; computation of scalar and vector seismic hazard using the un-updated and updated ground motion models for Los Angeles, CA; and simulation of the conditional mean spectrum under scalar and vector IM conditioning while accounting for different sources of aleatoric and epistemic uncertainties.

58 GEOSCIENCES↗
DOE OSTI2020

The Economic Accessibility of CO2 Sequestration through Bioenergy with Carbon Capture and Storage (BECCS) in the US

Bioenergy with carbon capture and storage (BECCS) is one strategy to remove CO2 from the atmosphere. To assess the potential scale and cost of CO2 sequestration from BECCS in the US, this analysis models carbon sequestration net of supply chain emissions and costs of biomass production, delivery, power generation, and CO2 capture and sequestration in saline formations. The analysis includes two biomass supply scenarios (near-term and long-term), two biomass logistics scenarios (conventional and pelletized), and two generation technologies (pulverized combustion and integrated gasification combined cycle). Results show marginal cost per tonne CO2 (accounting for costs of electricity and CO2 emissions of reference power generation scenarios) as a function of CO2 sequestered (simulating capture of up to 90% of total CO2 sequestration potential) and associated spatial distribution of resources and generation locations for the array of scenario options. Under a near-term scenario using up to 206 million tonnes per year of biomass, up to 181 million tonnes CO2 can be sequestered annually at scenario-average costs ranging from $62 to $137 per tonne CO2; under a long-term scenario using up to 740 million tonnes per year of biomass, up to 737 million tonnes CO2 can be sequestered annually at scenario-average costs ranging from $42 to $92 per tonne CO2. These estimates of CO2 sequestration potential may be reduced if future competing demand reduces resource availability or may be increased if displaced emissions from conventional power sources are included. Results suggest there are large-scale opportunities to implement BECCS at moderate cost in the US, particularly in the Midwest, Plains States, and Texas.

09 BIOMASS FUELS↗
DOE OSTI2016

PROVIDING STRINGENT STAR FORMATION RATE LIMITS OF z ∼ 2 QSO HOST GALAXIES AT HIGH ANGULAR RESOLUTION

We present integral field spectrograph (IFS) with laser guide star adaptive optics (LGS-AO) observations of z ∼ 2 quasi-stellar objects (QSOs) designed to resolve extended nebular line emission from the host galaxy. Our data was obtained with W. M. Keck and Gemini North Observatories, using OSIRIS and NIFS coupled with the LGS-AO systems, respectively. We have conducted a pilot survey of five QSOs, three observed with NIFS+AO and two observed with OSIRIS+AO at an average redshift of z = 2.2. We demonstrate that the combination of AO and IFSs provides the necessary spatial and spectral resolutions required to separate QSO emission from its host. We present our technique for generating a point-spread function (PSF) from the broad-line region of the QSO and performing PSF subtraction of the QSO emission to detect the host galaxy emission at a separation of ∼0.″2 (∼1.4 kpc). We detect Hα narrow-line emission for two sources, SDSS J1029+6510 (z{sub Hα} = 2.182) and SDSS J0925+0655 (z{sub Hα} = 2.197), that have evidence for both star formation and extended narrow-line emission. Assuming that the majority of narrow-line Hα emission is from star formation, we infer a star formation rate (SFR) for SDSS J1029+6510 of 78.4 M{sub ⊙} yr{sup −1} originating from a compact region that is kinematically offset by 290–350 km s{sup −1}. For SDSS J0925+0655 we infer a SFR of 29 M{sub ⊙} yr{sup −1} distributed over three clumps that are spatially offset by ∼7 kpc. The null detections on three of the QSOs are used to infer surface brightness limits and we find that at 1.4 kpc from the QSO the un-reddened star formation limit is ≲0.3 M{sub ⊙} yr{sup −1} kpc{sup −2}. If we assume typical extinction values for z = 2 type-1 QSOs, the dereddened SFR for our null detections would be ≲0.6 M{sub ⊙} yr{sup −1} kpc{sup −2}. These IFS observations indicate that while the central black hole is accreting mass at 10%–40% of the Eddington rate, if star formation is present in the host (1.4–20 kpc) it would have to occur diffusely with significant extinction and not in compact, clumpy regions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Efficient Electrochemical Reduction of CO 2 to Formate in Methanol Solutions by Mn‐Functionalized Electrodes in the Presence of Amines**

Carbon cloth electrode modified by covalently attaching a manganese organometallic catalyst is used as cathode for the electrochemical reduction of CO 2 in methanol solutions. Six different industrial amines are employed as co-catalyst in millimolar concentrations to deliver a series of new reactive system. While such absorbents were so far believed to provide a CO 2 reservoir and act as sacrificial proton source, we herein demonstrate that this role can be played by methanol, and that the adduct formed between CO 2 and the amine can act as an effector or inhibitor toward the catalyst, thereby enhancing or reducing the production of formate. Pentamethyldiethylentriamine (PMDETA), identified as the best effector in our series, converts CO 2 in wet methanolic solution into bisammonium bicarbonate. Computational studies revealed that this adduct is responsible for a barrierless transformation of CO 2 to formate by the reduced form of the Mn catalyst covalently bonded to the electrode surface. As a consequence, selectivity can be switched on demand from CO to formate anion, and in the case of (PMDETA) an impressive TON HCOO- of 2.8×10 4 can be reached. This new valuable knowledge on an integrated capture and utilization system paves the way toward more efficient transformation of CO 2 into liquid fuel.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

OPEN leaf : an open‐source cloud‐based phenotyping system for tracking dynamic changes at leaf‐specific resolution in Arabidopsis

SUMMARY The first draft of the Arabidopsis genome was released more than 20 years ago and despite intensive molecular research, more than 30% of Arabidopsis genes remained uncharacterized or without an assigned function. This is in part due to gene redundancy within gene families or the essential nature of genes, where their deletion results in lethality (i.e., thedark genome). High‐throughput plant phenotyping (HTPP) offers an automated and unbiased approach to characterize subtle or transient phenotypes resulting from gene redundancy or inducible gene silencing; however, access to commercial HTPP platforms remains limited. Here we describe the design and implementation ofOPEN leaf, an open‐source phenotyping system with cloud connectivity and remote bilateral communication to facilitate data collection, sharing and processing.OPEN leaf, coupled with our SMART imaging processing pipeline was able to consistently document and quantify dynamic changes at the whole rosette level and leaf‐specific resolution when plants experienced changes in nutrient availability. Our data also demonstrate that VIS sensors remain underutilized and can be used in high‐throughput screens to identify and characterize previously unidentified phenotypes in a leaf‐specific time‐dependent manner. Moreover, the modular and open‐source design ofOPEN leafallows seamless integration of additional sensors based on users and experimental needs.

Plant Sciences↗
DOE OSTI2024

On the Impact of High-Order Harmonic Generation in Electrical Distribution Systems

The modern power grid has seen a rise in the integration of non-linear loads, presenting a significant concern for operators. These loads introduce unwanted harmonics, leading to potential issues such as overheating and improper functioning of circuit breakers. In pursuing a more sustainable grid, the adoption of electric vehicles (EVs) and photovoltaic (PV) systems in residential networks has increased. Understanding and examining the effects of high-order harmonic frequencies beyond $1.5$ kHz is crucial to understanding their impact on the operation and planning of electrical distribution systems under varying nonlinear loading conditions. This study investigates a diverse set of critical power electronic loads within a household modeled using PSCAD/EMTdc, analyzing their unique harmonic spectra. This information is utilized to run the time-series harmonic analysis program in OpenDSS on a modified IEEE 34 bus test system model. The impact of high-order harmonics is quantified using metrics that evaluate total harmonic distortion (THD), transformer harmonic-driven eddy current loss component, and propagation of harmonics from the source to the substation transformer.

Peerzada, Aaqib A. [BATTELLE (PACIFIC NW LAB)]↗
DOE OSTI2018

Assessment of CO 2 Storage Resources in Depleted Oil and Gas Fields in the Ship Shoal Area, Gulf of Mexico

The Gulf of Mexico is one of the most important regions in the United States for energy resources and infrastructure. Gulf of Mexico federal offshore oil and gas production accounts for 17% of total U.S. crude oil production and 5% of total U.S. gas production (EIA Gulf of Mexico Fact Sheet). This region presents an excellent combination of high need and significant opportunity for large scale geologic storage of CO 2 . The Ship Shoal Area is located about 20 miles offshore Louisiana within the Gulf Coast federal waters. Miocene and Pliocene sediments in the Ship Shoal Area are proven to provide excellent and secure traps for oil and gas. The Ship Shoal Area contains a large number of depleted oil and gas fields either currently abandoned, or planned for abandonment by 2025, which may provide very significant potential CO 2 storage capacity. GeoMechanics Technologies conducted a comprehensive research project to better characterize Neogene sediments in the Ship Shoal Area for high volume CO 2 storage. The data generated from literature, well data, well log, and formation evaluation were input into Rockwork 16 geologic software to create a detailed geologic model for the Ship Shoal study area. The geologic grids were then fed into TOUGH2, the gas migration model software and FLAC 3D, the geomechanical model software. The fluid flow modeling for both the Miocene and Pliocene simulation from both Block 107 and Block 84 indicated that Pliocene and Miocene are a good reservoir for the CO 2 sequestration. Thirty years of CO 2 injection (at a rate of 1 million metric tons CO 2 per year) and 30 years of observation simulations were run with the fluid flow modeling. The 3D geomechanical modeling for Ship Shoal Block 107 and Block 84 were developed to evaluate induced surface deformation and potential fault reactivation after 30 years CO 2 injection at base of Pliocene and at upper Miocene injection locations. Evaluation results indicate low to no risks for fault slips or fault reactivation. Twelve well bores and 76 well bores for Ship Shoal Blocks 84 and 107 respectively were reviewed for their cement history. Most wells (57 out of 76 and 7 out of 12 wells in Ship Shoal Block 107 and 84 respectively) have good integrity. Nineteen and 5 wells (in Ship Shoal Block 107 and 84 respectively) with no top plug, incomplete cement or Plug and Abandonment information are given yellow cautionary indicators. These cautionary wells may provide leakage paths of CO 2 through the well bores to the USDWs. Using our Quantitative Risk & Decision Analysis Tool (QRDAT) for caprock integrity evaluation, we compared Ship Shoal’s risk to that of In Salah, Sleipner, Kevin Dome, Loudon, Illinois Industrial CCS and Wilmington Graben. We found the risk at the Ship Shoal Blocks 84 and 107 fields are similar to the known CO 2 active sequestration sites, but lower than the Wilmington Graben turbidities offshore California studied site. The risk of natural seismicity in the Gulf of Mexico is relatively low. Geomechanics Technologies has documented the top 25 CO 2 emission sources within the close proximity of the Ship Shoal Block 84 and 107 fields. All the offshore and onshore pipelines have been digitized and can be viewed in an interactive website (http://www.geomechanicstech.com/shipshoal.html). We also performed a feasibility study on the potential for converting existing oil or gas pipelines for CO 2 transport. There are abandoned, idled and retired onshore and offshore pipelines. However, there is no standard specification for maximum pipeline pressures needed for CO 2 transport. It is a function of design, materials, and testing provided; thus it will be the responsibility of the pipeline operator to correctly determine, maintain and operate within the limits of the pipelines. There are a few transit corridors extending from onshore Louisiana (Cailou Bay) to offshore trunk-lines. The cost for constructing a pipeline has increased about 46% from 2015 to an average cost of $5,064,046 per mile in 2016. We use the NETL CO 2 storage resource mass estimate to calculate the potential resources for Ship Shoal Block 84 and 107 fields using the depleted oil and gas reservoir volume and sand volume generated from our geologic modeling. The estimated storage resource results are greater when using the sand volumes derived through geologic modeling than the oil and gas reservoir data. The difference is due to the depleted oil and gas reservoir information not accounting for the water-flooded sand located below the oil/gas-water contact or unproductive sand units. Resource calculation using the sand volume obtained through geologic modeling overestimate the storage capacity as the model accounts for all sand within the formation, not just the interconnected sand.

02 PETROLEUM↗
DOE OSTI2020

The AMUSING++ Nearby Galaxy Compilation. I. Full Sample Characterization and Galactic-scale Outflow Selection

We present here AMUSING++: the largest compilation of nearby galaxies observed with the MUSE integral-field spectrograph so far. This collection consists of 635 galaxies from different MUSE projects covering the redshift interval 0.0002 < z < 0.1. The sample and its main properties are characterized and described here. It includes galaxies of almost all morphological types, with a good coverage in its color–magnitude diagram, within the stellar mass range between 10{sup 8} and 10{sup 12} M {sub ⊙}, and with properties resembling those of a diameter-selected sample. The AMUSING++ sample is, therefore, suitable for studying, with unprecendented detail, the properties of nearby galaxies at global and local scales, providing us with more than 50 million individual spectra. We use this compilation to investigate the presence of galactic outflows. We exploit the use of combined emission-line images to explore the shape of the different ionized components and the distribution along classical diagnostic diagrams to disentangle the different ionizing sources across the optical extension of each galaxy. We use the cross-correlation function to estimate the level of symmetry of the emission lines as an indication of the presence of shocks and/or active galactic nuclei. We uncovered a total of 54 outflows, comprising ∼8% of the sample. A large number of the discovered outflows correspond to those driven by active galactic nuclei (∼60%), suggesting some bias in the selection of our sample. No clear evidence was found that outflow host galaxies are highly star-forming, and outflows appear to be found within all galaxies around the star-formation sequence.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Understanding latent timescales in neural ordinary differential equation models of advection-dominated dynamical systems

The neural ordinary differential equation (ODE) framework has shown considerable promise in recent years in developing highly accelerated surrogate models for complex physical systems characterized by partial differential equations (PDEs). For PDE-based systems, state-of-the-art neural ODE strategies leverage a two-step procedure to achieve this acceleration: a nonlinear dimensionality reduction step provided by an autoencoder, and a time integration step provided by a neural-network based model for the resultant latent space dynamics (the neural ODE). This work explores the applicability of such autoencoder-based neural ODE strategies for PDEs in which advection terms play a critical role. More specifically, alongside predictive demonstrations, physical insight into the sources of model acceleration (i.e., how the neural ODE achieves its acceleration) is the scope of the current study. Such investigations are performed by quantifying the effects of both autoencoder and neural ODE components on latent system time-scales using eigenvalue analysis of dynamical system Jacobians. To this end, the sensitivity of various critical training parameters – de-coupled versus end-to-end training, latent space dimensionality, and the role of training trajectory length, for example – to both model accuracy and the discovered latent system timescales is quantified. Furthermore, this work specifically uncovers the key role played by the training trajectory length (the number of rollout steps in the loss function during training) on the latent system timescales: larger trajectory lengths correlate with an increase in limiting neural ODE time-scales, and optimal neural ODEs are found to recover the largest time-scales of the full-order (ground-truth) system. Demonstrations are performed across fundamentally different unsteady fluid dynamics configurations influenced by advection: (1) the Kuramoto–Sivashinsky equations (2) Hydrogen-Air channel detonations (the compressible reacting Navier–Stokes equations with detailed chemistry), and (3) 2D Atmospheric flow.

Advection-dominated dynamical systems↗
DOE OSTI2016

X-ray Characterization of a Multichannel Smart-Pixel Array Detector

The Voxtel VX-798 is a prototype X-ray pixel array detector (PAD) featuring a silicon sensor photodiode array of 48 x 48 pixels, each 130 mu m x 130 mu m x 520 mu m thick, coupled to a CMOS readout application specific integrated circuit (ASIC). The first synchrotron X-ray characterization of this detector is presented, and its ability to selectively count individual X-rays within two independent arrival time windows, a programmable energy range, and localized to a single pixel is demonstrated. During our first trial run at Argonne National Laboratory's Advance Photon Source, the detector achieved a 60 ns gating time and 700 eV full width at half-maximum energy resolution in agreement with design parameters. Each pixel of the PAD holds two independent digital counters, and the discriminator for X-ray energy features both an upper and lower threshold to window the energy of interest discarding unwanted background. This smart-pixel technology allows energy and time resolution to be set and optimized in software. It is found that the detector linearity follows an isolated dead-time model, implying that megahertz count rates should be possible in each pixel. Measurement of the line and point spread functions showed negligible spatial blurring. When combined with the timing structure of the synchrotron storage ring, it is demonstrated that the area detector can perform both picosecond time-resolved X-ray diffraction and fluorescence spectroscopy measurements.

CMOS ASIC↗
DOE OSTI2024

Spin-Controllable Dynamics in Defect-Engineered Carbon Nanotubes as Single Photon Emitters: Data-Driven Modeling and Computations

Quantum technologies, such as quantum computing and sensing, require efficient single-photon emission (SPE) sources that operate at room temperature in telecom wavelengths. While several materials can serve as SPE sources, no single platform meets all the criteria for efficiency, ambient operation, and scalability. Single-walled carbon nanotubes (SWCNTs) with covalently attached molecules offer a promising solution. Their SPE can be easily tuned via modifications of the SWCNT's diameter, chirality, and bonded molecules, enabling emission across near-IR to telecom wavelengths at ambient conditions. However, to fully realize the potential of SWCNTs and unlock their quantum capabilities, a deeper understanding of how structural defects from molecular adducts affect their emission and competing photoexcited processes is essential. To address this gap in our knowledge, this project combined quantum chemistry calculations with data-driven methods of cheminformatics (QSAR) and machine learning (ML). The developed computational approaches have provided several design strategies for covalent functionalization of SWCNTs to improve their optical response. The collaboration with Los Alamos National Lab (LANL) enabled direct comparison of computational and experimental data, facilitating method validation. This partnership was enhanced through access to LANL's Center for Integrated Nanotechnologies (CINT) utilizing User Facility Program and summer internships, which provided three NDSU graduate students with hands-on experience at LANL. The outcomes of this project included (1) Advancing the current stage of computational methods in accurate modeling of non-adiabatic spin-dependent photoexcited dynamics and its applicability to nanosystems consisting of thousands of atoms, realized as open-access codes linked to existing DFT-based software; (2) Establishing the relationship between the structure of adducts and SWCNTs and intrinsic excitonic and spin properties of defect states for guiding novel synthetic strategies and experimental probes of chemically functionalized SWCNTs as near-IR emitting materials; (3) Generating virtual libraries of hypothetical functionalized SWCNTs for virtual screening of their chemical structures and optical properties, leveraging new functionalities of SWCNTs; (4) Offering a unique experience for NDSU graduate students that prepared them for future scientific careers related to materials modeling and big data processing. These results were summarized in 12 published journal papers and 3 recently submitted papers. One of a key finding is that the position of defect sites on the SWCNT surface primarily drives the emission redshift (up to 100 meV), while the polarity of the defect-inducing molecules has a much smaller effect (~10 meV). However, the electron-donating or withdrawing properties of a molecule influence selecting reactivity of defect sites. These insights important for optimizing synthetic protocols for desired emissions in SWCNTs. We also revealed that the interaction between two defects at various positions on the SWCNT enhances the redshift and optical activity of states, favoring strong near-IR emission. This suggests that manipulations in defect concentrations is a promising strategy for controlling efficient emission. Mostly important, the defect position was found controllable by the spin states of photoexcited intermediates: Excited aromatic molecules form ortho defects with SWCNTs at their singlet states in the presence of oxygen, while oxygen-free conditions favor para defects via the triplet-state mechanism. Additionally, a heat-activated [2+2] cycloaddition reaction facilitates divalent defect formation with fewer bonding positions that narrows emission bands. These groundbreaking findings have been experimentally validated and significantly advance our understanding of defect chemistry in SWCNTs. Using a novel encoding technique and 3D-MoRSE descriptors, we developed highly accurate ML/QSAR models to predict both the 3D structure and optical properties of SWCNTs with chemical defects. This model enabled the creation of a virtual library of 125,556 structures, providing new insights into the relationship between SWCNT-defect structure and emission.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

Design and Optimization of Structured Multi-Functional Trapping Catalysts for Conversion of Hydrocarbons and NOx from Diesel and Advanced Combustion Engines

Oxides of nitrogen in the form of nitric oxide (NO) and nitrogen dioxide (NO 2 ) commonly referred to as NOx, is one of the two chemical precursors that lead to ground-level ozone, a ubiquitous air pollutant in urban areas. A major source of NOx is generated by equipment and vehicles powered by diesel engines, which have a combustion exhaust that contains NOx in the presence of excess O 2 . Vehicular emission control catalysts are ineffective in eliminating CO, hydrocarbons, and NOx during engine cold-start when exhaust temperatures are below 200°C. The objective of the project was to develop and demonstrate a multi-functional, catalyzed trap that enables vehicles with advanced combustion strategies to meet Tier 3 emissions standards while achieving the 150 °C challenge for sustained co-oxidation of HCs and CO and ≥90% NO trapping and release during warmup. Specifically, the multi-functional Lean HC+NOx (LHCNT) was developed for application in the exhaust aftertreatment of conventional diesel engines and engines having low temperature combustion (LTC) regimes. Activities included the design and synthesis of adsorbents and catalysts, screening and evaluation. Passive NOx absorbers (PNA), hydrocarbon (HC) traps, and oxidation catalysts (OC) were evaluated for use in series or as integrated devices. Predictive tools were developed utilizing the characterization and analysis of these materials, and an emission system was designed and optimized utilizing the catalyst systems. Microkinetic models were developed for the PNA for the simple NO-only feed and complex feed containing CO, H 2 , and model hydrocarbons (ethylene and dodecane). A first-principles, mechanistic-based model of the PNA was developed which utilized molecular-scale estimates (density functional theory) of energy barriers, mechanistic-based kinetics and realistic treatments of the flow and transport processes. Two new oxidation catalysts were developed (PdCu alloy, mixed copper-ceria-cobalt oxide), both of which significantly lessened the detrimental inhibition by CO on hydrocarbon and NO oxidation. A method for lessening the detrimental impact of CO on PNA activity was developed that involves use of an oxidation catalyst upstream of the PNA. The SwRI Ectolab TM burner system was applied to evaluate the baseline PNA material and confirmed performance comparable to the benchflow PNA studies using simulated exhaust. Spatially-resolved mass spectrometry (SpaciMS) was used to measure the transient spatial profiles of reacting species spanning the length of a three-function LHCNT containing PNA, HCT, and OC. The findings from this study provide diesel vehicle and catalyst companies valuable information to develop more cost effective emission control catalysts which helps to expand the use of more fuel efficient diesel power. The fundamental modeling and experimental tools and findings from this project can be applied to catalyst technologies used in the energy and chemical industries. The project led to 14 publications in the peer-reviewed literature with 2 additional currently under review. Finally, the project also led to training of several doctoral students who were placed in research jobs in industry and academia. Specifically, Mugdha Ambast (UH) has joined Cummins, Kevin Gu (UVa) has joined GM, and Abhay Gupta (UH) is to join Caterpillar.

02 PETROLEUM↗