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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 1,189 records · Page 66
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Ultrafast X-ray Spectroscopy of Intersystem Crossing in Hexafluoroacetylacetone: Chromophore Photophysics and Spectral Changes in the Face of Electron-Withdrawing Groups

Intersystem crossings between singlet and triplet states represent a crucial relaxation pathway in photochemical processes. Herein, we probe the intersystem crossing in hexafluoro-acetylacetone with ultrafast X-ray transient absorption spectroscopy at the carbon K-edge. In this study, we observe the excited state dynamics following excitation with 266 nm UV light to the 1 ππ* (S 2 ) state with element and site-specificity using a broadband soft X-ray pulse produced by high harmonic generation. These results are compared to X-ray spectra computed from orbital optimized density functional theory methods. It is found that the electron-withdrawing fluorine atoms decongest the X-ray absorption spectrum by enhancing separation between features originating from different carbon atoms. This facilitates the elucidation of structural and electronic dynamics at the chromophore. The evolution of the core-to-valence resonances at the carbon K-edge reveals an ultrafast population transfer between the 1 nπ* (S 1 ) and 3 ππ* (T 1 ) states on a 1.6 ± 0.4 ps time scale, which is similar to the 1.5 ps time scale earlier observed for acetylacetone [ J. Am. Chem. Soc. 2017, 139, 16576—16583, DOI: 10.1021/jacs.7b07532]. It therefore appears that terminal fluorination has little influence on the intersystem crossing rate of the acetylacetone chromophore. In addition, the significant role of hydrogen-bond opened and twisted rotational isomers is elucidated in the excited state dynamics by comparison of the experimental transient X-ray spectra with theory.

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

Crystal Structure and C–H Bond-Cleaving Reactivity of a Mononuclear Co IV –Dinitrate Complex

High-valent Fe IV =O intermediates with a terminal metal–oxo moiety are key oxidants in many enzymatic and synthetic C–H bond oxidation reactions. While generating stable metal–oxo species for late transition metals remains synthetically challenging, notably, a number of high-valent non-oxo–metal species of late transition metals have been recently described as strong oxidants that activate C–H bonds. In this work, we obtained an unprecedented mononuclear Co IV –dinitrate complex (2) upon one-electron oxidation of its Co(III) precursor supported by a tridentate dianionic N3 ligand. 2 was structurally characterized by X-ray crystallography, showing a square pyramidal geometry with two coordinated nitrate anions. Furthermore, characterization of 2 using combined spectroscopic and computational methods revealed that 2 is a low-spin (S = 1/2) Co(IV) species with the unpaired electron located on the cobalt d z2 orbital, which is well positioned for substrate oxidations. Indeed, while having a high thermal stability, 2 is able to cleave sp 3 C–H bonds up to 87 kcal/mol to afford rate constants and kinetic isotope effects (KIEs) of 2–6 that are comparable to other high-valent metal oxidants. The ability to oxidize strong C–H bonds has yet to be observed for Co IV –O and Co III =O species previously reported. Therefore, 2 represents the first high-valent Co(IV) species that is both structurally characterized by X-ray crystallography and capable of activating strong C–H bonds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

A Markov State-based Quantitative Kinetic Model of Sodium Release from the Dopamine Transporter

Here, the dopamine transporter (DAT) belongs to the neurotransmitter:sodium symporter (NSS) family of membrane proteins that are responsible for reuptake of neurotransmitters from the synaptic cleft to terminate a neuronal signal and enable subsequent neurotransmitter release from the presynaptic neuron. The release of one sodium ion from the crystallographically determined sodium binding site Na2 had been identified as an initial step in the transport cycle which prepares the transporter for substrate translocation by stabilizing an inward-open conformation. We have constructed Markov State Models (MSMs) from extensive molecular dynamics simulations of human DAT (hDAT) to explore the mechanism of this sodium release. Our results quantify the release process triggered by hydration of the Na2 site that occurs concomitantly with a conformational transition from an outward-facing to an inward-facing state of the transporter. The kinetics of the release process are computed from the MSM, and transition path theory is used to identify the most probable sodium release pathways. An intermediate state is discovered on the sodium release pathway, and the results reveal the importance of various modes of interaction of the N-terminus of hDAT in controlling the pathways of release.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Identifying Critical Infrastructure in Imagery Data Using Explainable Convolutional Neural Networks

To date, no method utilizing satellite imagery exists for detailing the locations and functions of critical infrastructure across the United States, making response to natural disasters and other events challenging due to complex infrastructural interdependencies. This paper presents a repeatable, transferable, and explainable method for critical infrastructure analysis and implementation of a robust model for critical infrastructure detection in satellite imagery. This model consists of a DenseNet-161 convolutional neural network, pretrained with the ImageNet database. The model was provided additional training with a custom dataset, containing nine infrastructure classes. The resultant analysis achieved an overall accuracy of 90%, with the highest accuracy for airports (97%), hydroelectric dams (96%), solar farms (94%), substations (91%), potable water tanks (93%), and hospitals (93%). Critical infrastructure types with relatively low accuracy are likely influenced by data commonality between similar infrastructure components for petroleum terminals (86%), water treatment plants (78%), and natural gas generation (78%). Local interpretable model-agnostic explanations (LIME) was integrated into the overall modeling pipeline to establish trust for users in critical infrastructure applications. The results demonstrate the effectiveness of a convolutional neural network approach for critical infrastructure identification, with higher than 90% accuracy in identifying six of the critical infrastructure facility types.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1995

Gravity Sensors and the Role of 3-D Visualization and Simulation in Biomedical Research

Ross 3.0 software was developed in the Biocomputation Center for semi-automated reconstruction of objects from serial thin sections. Data are captured directly from a transmission electron microscope via a video camera to a graphics workstation where the sections are mosaicked and contours are traced, registered and displayed by semi-automated methods. For the first time, macular type II cells are described completely for their innervation patterns. The purposes are to learn more about the fundamental circuitry of the macula and to demonstrate whether the terminals are altered morphologically by space flight. Current examples, from the medial part of the macula, are from maculas collected in-flight on the Space Life Sciences-2 mission, 4.5 hrs post-flight, and from a ground control. Results show that the typical type 11 cell receives processes from up to six nearby calyces or afferents. Nearly all the processes are elongated; some have bouton-like swellings and numerous vesicles. Multiple (2 to 4) processes from a single calyx to a type II cell are common, and approx. 1/3 of the processes innervate 2 type II cells of a neighboring cluster of 3 cells. About 2% of type II cells resemble type I cells morphologically and are surrounded by demicalyces. Differences in size or shape of the terminals under flight conditions could not be determined because the sample size is still too small; but it is clear that reconstruction methods provide insights into macular circuitry not obtainable by other techniques. The results demonstrate a morphological basis for interactions between adjacent receptive fields, through feedback-feedforward connections, during preprocessing of linear acceleratory information by the maculas. While the methods are currently being tested using vestibular maculas as the model system, it is clear that the technology is applicable to any tissue that can be physically or optically sectioned. ROSS software has already been implemented for reconstructing objects from tissues studied by confocal and by transmitted light microscopy, and research into magnetic resonance imaging-computational tomography combined visualization are underway.

Ross, Muriel D.↗
DOE OSTI2021

From the Starship Enterprise to Los Alamos National Laboratory: Artificial Intelligence and Machine Learning in the NSRC

Artificial Intelligence (AI) conjures up different emotions in different people. Some view it with fear, imagining a malevolent AI similar to Skynet in the Terminator movies. Others see something benevolent, such as the character Data in Star Trek: The Next Generation. Still others see it as a means to advance the frontiers of science, engineering, and technology to new levels not possible through traditional means. At the National Security Research Center (NSRC or the Center), we see AI as a tool to help us go through the monumental tasks we have in digitizing, cataloging, and searching our collections.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Blockchain Empowered Provenance Framework for Sensor Identity Management and Data Flow Security in Fossil-based Power Plants

The overall goals of this project are divided into 3 important phases. First, a peer-to-peer SCADA network is to be established where identity profile of sensors from fossil-power plants will be stored in an immutable manner in order to verify data flow integrity in real time. Second, it is aimed to develop a Blockchain-based provenance platform to audit equipment operations along with data and process integrity violations. In this phase, various operational rules will be incorporated in the ledger on behalf of the operating sensor so its abnormal use can be easily detected. In addition, it is aimed to achieve provenance when the rate of transactions is exceedingly high, thus enabling to design a scalable provenance scheme that can work in real time when number of data collecting points or sensor units increase in fossil-based power plants. Finally, a working testbed will be developed to integrate the Blockchain platform with sensor-based fossil power plant comprising of Remote Terminal Units (RTU) and SCADA devices. Using multiple Raspberry-PIs mimicking the role of RTUs that are interfaced with multiple sensors devices will be deployed to serve as a critical component of fossil power plant and the performance metrics such as throughput, latency, bootstrapping time, etc., will be evaluated on the testbed.

20 FOSSIL-FUELED POWER PLANTS↗
NASA NTRS1997

Surface Development and Test Facility (SDTF) New R&D Simulator for Airport Operations

A new simulator, the Surface Development and Test Facility (SDTF) is under construction at the NASA Ames Research Center in Mountain View, California. Jointly funded by the FAA (Federal Aviation Administration) and NASA, the SDTF will be a testbed for airport surface automation technologies of the future. The SDTF will be operational in the third quarter of 1998. The SDTF will combine a virtual tower with simulated ground operations to allow evaluation of new technologies for safety, effectiveness, reliability, and cost benefit. The full-scale level V tower will provide a seamless 360 degree high resolution out-the-window view, and a full complement of ATC (air traffic control) controller positions. The imaging system will be generated by two fully-configured Silicon Graphics Onyx Infinite Reality computers, and will support surface movement of up to 200 aircraft and ground vehicles. The controller positions, displays and consoles can be completely reconfigured to match the unique layout of any individual airport tower. Dedicated areas will accommodate pseudo-airport ramp controllers, pseudo-airport operators, and pseudo-pilots. Up to 33 total personnel positions will be able to participate in simultaneous operational scenarios. A realistic voice communication infrastructure will emulate the intercom and telephone communications of a real airport tower. Multi-channel audio and video recording and a sophisticated data acquisition system will support a wide variety of research and development areas, such as evaluation of automation tools for surface operations, human factors studies, integration of terminal area and airport technologies, and studies of potential airport physical and procedural modifications.

Dorighi, Nancy S.↗
DOE OSTI2018

A Soft-Matter Biomolecular Memristor Synapse for Neuromorphic Systems

The goal of neuromorphic computing is to recreate the computational power and efficiency of the human brain with circuitry. The ability of the brain to solve complex real time tasks, while consuming 20 W of power on average, is made possible through its connection density, adaptability, and parallel processing. Recreating these features using traditional electronics circuit elements is incredibly difficult, and therefore, soft-matter memristors made of biomolecules similar to those found in biological synapses and capable of emulating various synaptic features can be used as neuromorphic hardware. In this work, we introduce and experimentally demonstrate an electronic neuron circuit capable of interacting with ionic, soft-matter memristors. These memristors are proven to exhibit short-term plasticity, especially paired-pulse facilitation and depression found in presynaptic terminals - features that are not found in state-of-the-art solid-state memristors. We make use of these features for applications in online learning by developing a synapse-neuron circuit which implements spike-rate-dependent plasticity (SRDP) as a learning function.

Weiss, Ryan↗
DOE OSTI2024

Exploring the fragmentation efficiency of proteins analyzed by MALDI-TOF-TOF tandem mass spectrometry using computational and statistical analyses

Matrix-assisted laser desorption/ionization time-of-flight-time-of-flight (MALDI-TOF-TOF) tandem mass spectrometry (MS/MS) is a rapid technique for identifying intact proteins from unfractionated mixtures by top-down proteomic analysis. MS/MS allows isolation of specific intact protein ions prior to fragmentation, allowing fragment ion attribution to a specific precursor ion. However, the fragmentation efficiency of mature, intact protein ions by MS/MS post-source decay (PSD) varies widely, and the biochemical and structural factors of the protein that contribute to it are poorly understood. With the advent of protein structure prediction algorithms such as Alphafold2, we have wider access to protein structures for which no crystal structure exists. In this work, we use a statistical approach to explore the properties of bacterial proteins that can affect their gas phase dissociation via PSD. We extract various protein properties from Alphafold2 predictions and analyze their effect on fragmentation efficiency. Our results show that the fragmentation efficiency from cleavage of the polypeptide backbone on the C-terminal side of glutamic acid (E) and asparagine (N) residues were nearly equal. In addition, we found that the rearrangement and cleavage on the C-terminal side of aspartic acid (D) residues that result from the aspartic acid effect (AAE) were higher than for E- and N-residues. From residue interaction network analysis, we identified several local centrality measures and discussed their implications regarding the AAE. We also confirmed the selective cleavage of the backbone at D-proline bonds in proteins and further extend it to N-proline bonds. Finally, we note an enhancement of the AAE mechanism when the residue on the C-terminal side of D-, E- and N-residues is glycine. To the best of our knowledge, this is the first report of this phenomenon. Our study demonstrates the value of using statistical analyses of protein sequences and their predicted structures to better understand the fragmentation of the intact protein ions in the gas phase.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Patchy Particle Model of the Hierarchical Self-Assembly of π-Conjugated Optoelectronic Peptides

Self-assembling peptides containing aromatic groups are an attractive target for bioelectronic materials design because of their ease of manufacture, biocompatibility, aqueous solubility, and chemical tunability. Microscopic understanding of the properties that control assembly is a prerequisite for rational design. In this work, we study the assembly of a family of DXXX-Π–XXXD oligopeptides possessing a π-conjugated core flanked by Asp-terminated tetrapeptide wings that display pH-triggered assembly into supramolecular aggregates. We develop a coarse-grained patchy particle model to conduct molecular dynamics simulations of the assembly of ten thousand oligopeptides over hundreds of nanometers and hundreds of microseconds. We study the effects of core and side chain interaction strength and side chain steric volume upon the morphology and kinetics of assembly. By characterizing the rate and fractal dimension of hierarchical nanoaggregate growth, we identify parameter regimes that favor rapid assembly of linear aggregates and map these regimes to sequence-defined candidate peptides for experimental synthesis and testing. Here, this work establishes new understanding of assembly on previously unexplored time and length scales and presents an efficient and extensible protocol for computational screening and prediction of promising peptide chemistries to assemble nanostructures with desirable optoelectronic properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Data-driven optimized control of the COVID-19 epidemics

Optimizing the impact on the economy of control strategies aiming at containing the spread of COVID-19 is a critical challenge. We use daily new case counts of COVID-19 patients reported by local health administrations from different Metropolitan Statistical Areas (MSAs) within the US to parametrize a model that well describes the propagation of the disease in each area. We then introduce a time-varying control input that represents the level of social distancing imposed on the population of a given area and solve an optimal control problem with the goal of minimizing the impact of social distancing on the economy in the presence of relevant constraints, such as a desired level of suppression for the epidemics at a terminal time. We find that with the exception of the initial time and of the final time, the optimal control input is well approximated by a constant, specific to each area, which contrasts with the implemented system of reopening ‘in phases’. For all the areas considered, this optimal level corresponds to stricter social distancing than the level estimated from data. Proper selection of the time period for application of the control action optimally is important: depending on the particular MSA this period should be either short or long or intermediate. We also consider the case that the transmissibility increases in time (due e.g. to increasingly colder weather), for which we find that the optimal control solution yields progressively stricter measures of social distancing. We finally compute the optimal control solution for a model modified to incorporate the effects of vaccinations on the population and we see that depending on a number of factors, social distancing measures could be optimally reduced during the period over which vaccines are administered to the population.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1974

Modification of an impulse-factoring orbital transfer technique to account for orbit determination and maneuver execution errors

A method has previously been developed to satisfy terminal rendezvous and intermediate timing constraints for planetary missions involving orbital operations. The method uses impulse factoring in which a two-impulse transfer is divided into three or four impulses which add one or two intermediate orbits. The periods of the intermediate orbits and the number of revolutions in each orbit are varied to satisfy timing constraints. Techniques are developed to retarget the orbital transfer in the presence of orbit-determination and maneuver-execution errors. Sample results indicate that the nominal transfer can be retargeted with little change in either the magnitude (Delta V) or location of the individual impulses. Additonally, the total Delta V required for the retargeted transfer is little different from that required for the nominal transfer. A digital computer program developed to implement the techniques is described.

Kibler, J. F.↗
DOE OSTI2024

A second-order-in-time, explicit approach addressing the redundancy in the low-Mach, variable-density Navier-Stokes equations

A novel algorithm for explicit temporal discretization of the variable-density, low-Mach Navier-Stokes equations is presented here in this study. Recognizing there is a redundancy between the mass conservation equation, the equation of state, and the transport equation(s) for the scalar(s) which characterize the thermochemical state, and that it destabilizes explicit methods, we demonstrate how to analytically eliminate the redundancy and propose an iterative scheme to solve the resulting transformed scalar equations. The method obtains second-order accuracy in time regardless of the number of iterations, so one can terminate this subproblem once stability is achieved. Hence, flows with larger density ratios can be simulated while still retaining the efficiency, low cost, and parallelizability of an explicit scheme. The temporal discretization algorithm is used within a pseudospectral direct numerical simulation which extends the method of Kim, Moin, and Moser for incompressible flow to the variable-density, low-Mach setting, where we demonstrate stability for density ratios up to ~25.7.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Selective Chemical Looping Combustion of Terminal Alkynes in Mixtures with Alkenes

The selective combustion of terminal alkynes in mixtures with alkenes is demonstrated during anaerobic reduction half-cycles on bulk bismuth oxide (Bi 2 O 3 ) as an approach to remove alkynes, which act as inhibitors in olefin polymerization. Bi 2 O 3 combusts phenylacetylene in styrene, 3-methylphenylacetylene in 3-methylstyrene, propyne in propylene, 1-hexyne in 1-hexene, and 1-octyne in 1-octene, with alkyne combustion selectivities exceeding 96%. Near unity reaction orders for hydrocarbon consumption during reduction half-cycles are consistent with combustion pathways initiated by rate-determining initial C–H activation, which drive selective alkyne combustion through intrinsic differences in the first-order rate constants for alkyne and alkene combustion rather than preferential adsorption of alkynes on Bi 2 O 3 surfaces. Computational assessments of initial C–H activation pathways for alkynes and alkenes on (010) α-Bi 2 O 3 surfaces using density functional theory illustrate that heterolytic transition states which form proton-carbanion pairs on Bi–O sites kinetically favor the activation of alkynes rather than alkenes due to differences in C–H bond acidity, and the barrier for heterolytic C–H activation is dictated in part by the sum of the molecular deprotonation energy and the energy to bind an R – carbanion to a Bi site in its transition-state geometry. Finally, these heterolytic reactivity channels during selective chemical looping combustion present novel routes for purifying olefin gas streams containing alkyne impurities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Molecular Zirconium Nitride Super Base from a Mononuclear Parent Imide

In this work, we prepared, isolated, and structurally characterized a zirconium complex having a terminally bound imide motif, (PN) 2 Zr≡NH (PN – = (N-(2- i Pr 2 P-4-methylphenyl)-2,4,6-trimethylanilide)), along with the zirconium nitride complex {(PN) 2 Zr≡N[μ 2 -Li(THF)]} 2 . (PN) 2 Zr≡NH was prepared by reduction of trans-(PN) 2 Zr(N 3 ) 2 with KC 8 . Isotopic labeling and spectroscopic studies were conducted using the respective 15 N enriched isotopologues, whereas solid-state structural studies confirmed some of the shortest Zr≡N distances known to date (Zr≡NH, 1.830(3) Å; Zr≡N – , 1.822(2) Å). It was found that the nitride in {(PN) 2 Zr≡N[μ 2 -Li(THF)]} 2 is super basic and in the range of –36 to –43 pK b units. Furthermore, computational studies have been applied to probe the bonding and structure for this new class of zirconium–nitrogen multiple bonds.

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

Hybrid Symbolic-Numerical Modeling and Parametric Stability Analysis of DC–AC Power Systems

Hybrid DC-AC power systems integrating diverse inverter-based resources (IBRs) and multi-terminal high-voltage direct current (MTDC) networks represent a promising architecture for future power grids, while introducing challenges for modeling, stability analysis, and control design. This paper develops a hybrid symbolic-numerical modeling framework and tool to characterize the parametric small-signal stability of DC-AC coupled power systems. The proposed approach constructs parametric state-space models to enable efficient representation of system dynamics under varying control parameters and network configurations, with target parameters retained as symbolic variables and the remainder treated numerically. The stability analysis framework covers eigenvalue, sensitivity, and stability boundary and region characterization. Enhanced linear matrix inequality (LMI) techniques are proposed to directly certify small-signal stability over regions of parameter space while also reducing the conservativeness and computational burden. The resulting tools and frameworks enable rapid parametric model construction across diverse grid conditions, thereby facilitating stability-informed control and operation in complex DC–AC power systems.

DC–AC power systems↗
DOE OSTI2025

An Instrumented Capsule Design to Measure Thermal Conductivity in Miniature UO2 Specimens

Numerous separate effects irradiations of miniature nuclear fuel specimens have been conducted in the High Flux Isotope Reactor (HFIR) under the experimental platform designated as MiniFuel. MiniFuel is a static irradiation capability in which microstructural evolution and fuel performance phenomena are observed during postirradiation examination thereby offering a snapshot of the terminal fuel characteristics. This approach inherently requires fielding an irradiation where the experimental conditions are determined using predictive models and the pertinent outcomes are measured at the end of the test. Static irradiations can provide useful insights to the relationships between fuel performance and the pivotal irradiation conditions, namely temperature and burnup, but the ability to monitor fuel performance in situ would further support fuel development and qualification. To this end, an instrumented experiment design is being developed at Oak Ridge National Laboratory to capture thermal conductivity degradation and fission gas release during HFIR irradiation. These phenomena will be monitored using unique capsule designs that each target a different phenomenon. This paper details the thermal conductivity capsule (TCC) design and its expected performance envelope as determined using computer models. Each TCC will contain a miniature UO2 disc specimen (~0.5 mm thick × 5 mm diameter) sandwiched between metallic slugs with embedded thermocouples. The coupling of in situ temperature measurements, known thermal conductivity of the metallic components, and heat generation rates computed using high-fidelity neutronics models make the thermal conductivity measurement possible. This paper describes the reactor physics and heat transfer models used to predict the capsule’s performance and the methodology for calculating the fuel specimen’s thermal conductivity from the thermocouple measurements.

Gorton, Jacob [ORNL] (ORCID:0000000269806083)↗