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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Geometric Interpretation of the Cluster Location Problem Part I: Theory

We present a new framing of the seismic location problem using principles drawn from differential geometry. Our interpretation relies upon the common assumption that travel times observed across a network are continuous, differentiable functions of source location. In consequence, travel‐time functions constitute a differentiable map between the source region and a Riemannian manifold. The manifold is said to be the image of the source region embedded in a generally high‐dimension travel‐time vector space. A cluster of events in the source region has an image of discrete points on the manifold, that, except in the simplest cases, cannot be viewed directly. However, it is possible to project the image of a cluster into a tangent space of the manifold for direct visualization. The projection operator can be computed directly from the data without a velocity model, but produces a distorted rendering of the cluster geometry. With a model we can predict the distortions and correct them to estimate cluster geometry. We develop these points with the simplest possible example, one for which direct visualization of the manifold is possible, using the example as an introduction to the relevant concepts from differential geometry in a familiar setting. The tangent space, a local linearization of the manifold, plays a key role. We develop a metric to estimate the limits of linearization, that is, to determine when the curvature of the manifold invalidates the linear assumption. We also examine the interplay of model error, inadequate network geometry, and pick error. We then generalize our results from the simple case to the general case of 3D source regions observed by general networks. Although we do suggest a new “project and correct” method for location, we do not develop it into a practical algorithm. In conclusion, our intention rather is to highlight new analytical methods grounded in differential geometry.

East Pacific Ocean Islands↗
DOE OSTI2016

High-performance oxygen reduction and evolution carbon catalysis: From mechanistic studies to device integration

The development of high-performance and low-cost oxygen reduction and evolution catalysts that can be easily integrated into existing devices is crucial for the wide deployment of energy storage systems that utilize O 2 -H 2 O chemistries, such as regenerative fuel cells and metal-air batteries. Herein, we report an NH 3 -activated N-doped hierarchical carbon (NHC) catalyst synthesized via a scalable route, and demonstrate its device integration. The NHC catalyst exhibited good performance for both the oxygen reduction reaction (ORR) and the oxygen evolution reaction (OER), as demonstrated by means of electrochemical studies and evaluation when integrated into the oxygen electrode of a regenerative fuel cell. The activities observed for both the ORR and the OER were comparable to those achieved by state-of-the-art Pt and Ir catalysts in alkaline environments. We have further identified the critical role of carbon defects as active sites for electrochemical activity through density functional theory calculations and high-resolution TEM visualization. As a result, this work highlights the potential of NHC to replace commercial precious metals in regenerative fuel cells and possibly metal-air batteries for cost-effective storage of intermittent renewable energy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Classification of Malaysia aromatic rice using multivariate statistical analysis

Aromatic rice (Oryza sativa L.) is considered as the best quality premium rice. The varieties are preferred by consumers because of its preference criteria such as shape, colour, distinctive aroma and flavour. The price of aromatic rice is higher than ordinary rice due to its special needed growth condition for instance specific climate and soil. Presently, the aromatic rice quality is identified by using its key elements and isotopic variables. The rice can also be classified via Gas Chromatography Mass Spectrometry (GC-MS) or human sensory panels. However, the uses of human sensory panels have significant drawbacks such as lengthy training time, and prone to fatigue as the number of sample increased and inconsistent. The GC–MS analysis techniques on the other hand, require detailed procedures, lengthy analysis and quite costly. This paper presents the application of in-house developed Electronic Nose (e-nose) to classify new aromatic rice varieties. The e-nose is used to classify the variety of aromatic rice based on the samples odour. The samples were taken from the variety of rice. The instrument utilizes multivariate statistical data analysis, including Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA) and K-Nearest Neighbours (KNN) to classify the unknown rice samples. The Leave-One-Out (LOO) validation approach is applied to evaluate the ability of KNN to perform recognition and classification of the unspecified samples. The visual observation of the PCA and LDA plots of the rice proves that the instrument was able to separate the samples into different clusters accordingly. The results of LDA and KNN with low misclassification error support the above findings and we may conclude that the e-nose is successfully applied to the classification of the aromatic rice varieties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Automated contouring error detection based on supervised geometric attribute distribution models for radiation therapy: A general strategy

Purpose: One of the most critical steps in radiation therapy treatment is accurate tumor and critical organ-at-risk (OAR) contouring. Both manual and automated contouring processes are prone to errors and to a large degree of inter- and intraobserver variability. These are often due to the limitations of imaging techniques in visualizing human anatomy as well as to inherent anatomical variability among individuals. Physicians/physicists have to reverify all the radiation therapy contours of every patient before using them for treatment planning, which is tedious, laborious, and still not an error-free process. In this study, the authors developed a general strategy based on novel geometric attribute distribution (GAD) models to automatically detect radiation therapy OAR contouring errors and facilitate the current clinical workflow. Methods: Considering the radiation therapy structures’ geometric attributes (centroid, volume, and shape), the spatial relationship of neighboring structures, as well as anatomical similarity of individual contours among patients, the authors established GAD models to characterize the interstructural centroid and volume variations, and the intrastructural shape variations of each individual structure. The GAD models are scalable and deformable, and constrained by their respective principal attribute variations calculated from training sets with verified OAR contours. A new iterative weighted GAD model-fitting algorithm was developed for contouring error detection. Receiver operating characteristic (ROC) analysis was employed in a unique way to optimize the model parameters to satisfy clinical requirements. A total of forty-four head-and-neck patient cases, each of which includes nine critical OAR contours, were utilized to demonstrate the proposed strategy. Twenty-nine out of these forty-four patient cases were utilized to train the inter- and intrastructural GAD models. These training data and the remaining fifteen testing data sets were separately employed to test the effectiveness of the proposed contouring error detection strategy. Results: An evaluation tool was implemented to illustrate how the proposed strategy automatically detects the radiation therapy contouring errors for a given patient and provides 3D graphical visualization of error detection results as well. The contouring error detection results were achieved with an average sensitivity of 0.954/0.906 and an average specificity of 0.901/0.909 on the centroid/volume related contouring errors of all the tested samples. As for the detection results on structural shape related contouring errors, an average sensitivity of 0.816 and an average specificity of 0.94 on all the tested samples were obtained. The promising results indicated the feasibility of the proposed strategy for the detection of contouring errors with low false detection rate. Conclusions: The proposed strategy can reliably identify contouring errors based upon inter- and intrastructural constraints derived from clinically approved contours. It holds great potential for improving the radiation therapy workflow. ROC and box plot analyses allow for analytically tuning of the system parameters to satisfy clinical requirements. Future work will focus on the improvement of strategy reliability by utilizing more training sets and additional geometric attribute constraints.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

In-situ Detection of Glovebox Glove Degradation Prior to Glove Failure; Effects on Safety, Waste, and Operational Costs - 20402

Glovebox glove pressure decay leak testing and analysis of the data can greatly improve glovebox safety, minimize Transuranic (TRU) glove waste, and minimize operational cost. It is well known, the weakest point of containment on a glovebox is the glove. Mitigating unplanned openings in gloves is critical to minimizing operational and safety costs in glovebox operations. Mitigating unplanned glove openings due to glove failures will be discussed in this paper. The lack of an engineered solution to determine a gloves operational life in nuclear operations, has lead to use of theoretical and manual subjective methods to determine the life and safety of a glovebox glove. Whether the glove is inspected visually prior to use, or gloves are changed regularly to theoretically avoid failure, both the operators PPE and the room are being exposed to contamination, or un-necessary amounts of TRU glove waste are being generated. Millions of dollars yearly in operational costs are spent on glove failures due to loss of production, incident analysis, regulatory audits, clean up, and paperwork. In a nuclear application, a glove failure could contaminate an operator and laboratory, shut down the operation for weeks, potentially create a regulatory audit, and potentially create a media frenzy; the damages to the organization can be astronomical. Elimination of glove failures is possible by tracking glove material degradation and setting limits to allow glove change when it becomes necessary, prior to glove failure. Analytical pressure decay leak testing allows the detection of material degradation, and in turn the ability to limit operational glove failures. A German based company called MK Versuchsanlagen, e.K., has developed an advanced Glove Integrity Testing System. The system, with its use of proprietary RFID and special software technology, is unique in its capabilities. The system is capable to perform highly accurate regular glove testing on any size glovebox line in minimal time. The system records and can analyze a tremendous amount of system data that in turn can determine, for example, a safe glove change time prior to a glove material failure. This paper will show how an advanced Glove Integrity Testing System can detect glove material degradation and help determine a safe change point prior to glove failure. Pressure decay curves of new gloves and recorded effects of accelerated aging on the glove over time will be shown. The use of this technology in nuclear facilities can greatly improve glovebox operational safety, minimize glovebox glove TRU waste, and save organizations tremendous costs in downtime, clean up, documentation, and potential regulatory review. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

A Glycan Array-Based Assay for the Identification and Characterization of Plant Glycosyltransferases

Growing plants with modified cell wall compositions is a promising strategy to improve resistance to pathogens, increase biomass digestibility, and tune other important properties. In order to alter biomass architecture, a detailed knowledge of cell wall structure and biosynthesis is a prerequisite. We report here a glycan array-based assay for the high-throughput identification and characterization of plant cell wall biosynthetic glycosyltransferases (GTs). We demonstrate that different heterologously expressed galactosyl-, fucosyl-, and xylosyltransferases can transfer azido-functionalized sugar nucleotide donors to selected synthetic plant cell wall oligosaccharides on the array and that the transferred monosaccharides can be visualized “on chip” by a 1,3-dipolar cycloaddition reaction with an alkynyl-modified dye. The opportunity to simultaneously screen thousands of combinations of putative GTs, nucleotide sugar donors, and oligosaccharide acceptors will dramatically accelerate plant cell wall biosynthesis research.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

LigninGraphs: lignin structure determination with multiscale graph modeling

Lignin is an aromatic biopolymer found in ubiquitous sources of woody biomass. Designing and optimizing lignin valorization processes requires a fundamental understanding of lignin structures. Experimental characterization techniques, such as 2D-heteronuclear single quantum coherence (HSQC) nuclear magnetic resonance (NMR) spectra, could elucidate the global properties of the polymer molecules. Computer models could extend the resolution of experiments by representing structures at the molecular and atomistic scales. We introduce a graph-based multiscale modeling framework for lignin structure generation and visualization. The framework employs accelerated rejection-free polymerization and hierarchical Metropolis Monte Carlo optimization algorithms. We obtain structure libraries for various lignin feedstocks based on literature and new experimental NMR data for poplar wood, pinewood, and herbaceous lignin. The framework could guide researchers towards feasible lignin structures, efficient space exploration, and future kinetics modeling. Its software implementation in Python, LigninGraphs, is open-source and available on GitHub.

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

Mannobiose Binding Induces Changes in Hydrogen Bonding and Protonation States of Acidic Residues in Concanavalin A As Revealed by Neutron Crystallography

Plant lectins are carbohydrate-binding proteins with various biomedical applications. Concanavalin A (Con A) holds promise in treating cancerous tumors. To better understand the Con A carbohydrate binding specificity, we obtained a room-temperature neutron structure of this legume lectin in complex with a disaccharide Manα1–2Man, mannobiose. The neutron structure afforded direct visualization of the hydrogen bonding between the protein and ligand, showing that the ligand is able to alter both protonation states and interactions for residues located close to and distant from the binding site. An unprecedented low-barrier hydrogen bond was observed forming between the carboxylic side chains of Asp28 and Glu8, with the D atom positioned equidistant from the oxygen atoms having an O···D···O angle of 101.5°.

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

Direct Visualization and Control of Atomic Mobility at {100} Surfaces of Ceria in the Environmental Transmission Electron Microscope

We report that ceria is one of the world’s most prominent material for applications in heterogeneous catalysis, as catalyst support or catalyst itself. Despite an exhaustive literature on the structure of reactive facets of CeO 2 in line with its catalytic mechanisms, the temporal evolution of the atomic surface structure exposed to realistic redox conditions remains elusive. Here, we provide a direct visualization of the atomic mobility of cerium atoms on {100} surfaces of CeO 2 nanocubes at room temperature in high vacuum, O 2 , and CO 2 atmospheres in an environmental transmission electron microscope. Lastly, through quantification of the cationic mobility, we demonstrate the control of the surface dynamics under exposure to O 2 and CO 2 atmospheres, providing opportunities for a better understanding of the intimate catalytic mechanisms.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Computational Study of the Malonic Acid Tautomerization Products in Highly Concentrated Particles

Knowing the tautomeric form of malonic acid (MA) in concentrated particles is critical to understanding its effect on the atmosphere. Energies and vibrational modes of hydrated MA particles were calculated using density functional theory (DFT) at the B3LYP/6-31G(d,p) level and the effective fragment potential (EFP) method. Visualization of the keto and enol isomer vibrational modes enabled the assignment of keto isomer peaks in the 1710–1750 cm –1 range, and previously unidentified experimental IR peaks in the 1690–1710 cm –1 can now be attributed to the enol isomer. Furthermore, a comparison of calculated spectra of pure hydrated enol or keto isomers confirm recent experimental evidence, of a shift in the keto–enol tautomer equilibrium when MA exists as concentrated particles.

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

The XtalOpt Evolutionary Algorithm for Crystal Structure Prediction

Significant progress has been made in the field of a priori crystal structure prediction, with a number of recent remarkable success stories. Herein, we briefly outline the methods that have been developed for finding the global minimum structure and interesting local minima without the need for experimental information. Focus is placed on describing the XTALOPT evolutionary algorithm (EA) developed in our group towards this end. XTALOPT is published under well-known open-source licenses, and the EA searches can be analyzed via the AVOGADRO chemical editor and visualizer. We describe new algorithmic developments that have made it possible to predict the structures of ever-more complex crystalline lattices. Benchmark tests, which clearly illustrate how the new developments improve the success rate and accelerate the discovery of the global minimum structure, are carried out. Lastly, we describe how XTALOPT has been employed to predict novel ternary hydrides that have the propensity for high-temperature superconductivity under pressure.

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

Tip-Enhanced Raman Chemical and Chemical Reaction Imaging in H 2 O with Sub-3-nm Spatial Resolution

Reproducible chemical and chemical reaction nano-imaging at solid-liquid interfaces remains challenging, particularly when resolutions on the order of a few nm are sought after. In this work, we demonstrate the latter through liquid tip-enhanced Raman (TER) measurements that target gold nanoplates functionalized with 4-mercaptobenzonitrile (MBN). In addition to chemical imaging and local optical field nano-visualization with high spatial resolution, we observe the signatures of 4-mercaptobenzoic acid, which forms as a result of plasmon-induced hydrolysis of MBN. Evidently, the solvent leads to distinct plasmon-induced/enhanced chemical reaction pathways that have not been documented. Here this work shows that such reactions that take place at solid-liquid interfaces can be tracked with a record sub-3 nm spatial resolution via TER spectral nano-imaging in liquids.

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

Rapid self-healing and anion selectivity in metallosupramolecular gels assisted by fluorine–fluorine interactions

Simple ML 2 [M = Fe(II), Co(II), Ni(II)] complexes taken from a perfluoroalkylamide derivative of 4-aminophenyl-2,2',6,2'-terpyridine spontaneously, yet anion selectively, self-assemble into gels, which manifest an unprecedented rapid gel strength recovery, viz . self-healing, and thermal rearrangement in aqueous dimethyl sulfoxide. The key factor for gelation and rheological properties emerges from the fluorine–fluorine interactions between the perfluorinated chains, as the corresponding hydrocarbon derivative did not form metallogels. The perfluoro-terpyridine ligand alone formed single crystals, while its Fe(II), Co(II) or Ni(II) complexes underwent rapid gelation leading to highly entangled fibrillar networks visualized by electron microscopy. The thermodynamic parameters of gelation based on variable temperature NMR 1 H and 19 F resonances showed that gelation was enthalpically favourable and entropically disfavourable. The step strain rheological experiments demonstrated that the gels undergo rapid self-healing and the morphological features, thermal stability and mechanical properties were found to depend on the nature of the metal ion.

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

Visualizing and Quantifying the Cationic Mobility at {100} Surfaces of Ceria: Application to CO 2 Adsorption/Desorption Phenomena in the Environmental Transmission Electron Microscope

Environmental transmission electron microscopy in a dedicated instrument allows ultimate spatial resolution with chemical analysis capabilities similar to high resolution transmission electron microscopes (HRTEMs), while retaining partial pressures up to 20 mbar around the specimen. Finally, such instruments provide an optimized approach to study the early stages of catalytic reactions, which can start from very low partial pressure, at the atomic-scale.

36 MATERIALS SCIENCE↗
DOE OSTI2021

NEXTorch: A Design and Bayesian Optimization Toolkit for Chemical Sciences and Engineering

Automation and optimization of chemical systems require well-informed decisions on what experiments to run to reduce time, materials, and/or computations. Data-driven active learning algorithms have emerged as valuable tools to solve such tasks. Bayesian optimization, a sequential global optimization approach, is a popular active-learning framework. Past studies have demonstrated its efficiency in solving chemistry and engineering problems. Here we introduce NEXTorch, a library in Python/PyTorch, to facilitate laboratory or computational design using Bayesian optimization. NEXTorch offers fast predictive modeling, flexible optimization loops, visualization capabilities, easy interfacing with legacy software, and multiple types of parameters and data type conversions. It provides GPU acceleration, parallelization, and state-of-the-art Bayesian optimization algorithms and supports both automated an d human-in-the-loop optimization. The comprehensive online documentation introduces Bayesian optimization theory and several examples from catalyst synthesis, reaction condition optimization, parameter estimation, and reactor geometry optimization. NEXTorch is open-source and available on GitHub

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Short-time dynamics of 2-thiouracil in the light absorbing S{sub 2}(ππ{sup ∗}) state

Ultrahigh quantum yields of intersystem crossing to the lowest triplet state T{sub 1} are observed for 2-thiouracils (2TU), which is in contrast to the natural uracils that predominantly exhibit ultrafast internal conversion to the ground state upon excitation to the singlet excited state. The intersystem crossing mechanism of 2TU has recently been investigated using second-order perturbation methods with a high-level complete-active space self-consistent field. Three competitive nonadiabatic pathways to the lowest triplet state T{sub 1} from the initially populated singlet excited state S{sub 2} were proposed. We investigate the initial decay dynamics of 2TU from the light absorbing excited states using resonance Raman spectroscopy, time-dependent wave-packet theory in the simple model, and complete-active space self-consistent field (CASSCF) and time dependent-Becke’s three-parameter exchange and correlation functional with the Lee-Yang-Parr correlation functional (TD-B3LYP) calculations. The obtained short-time structural dynamics in easy-to-visualize internal coordinates were compared with the CASSCF(16,11) predicted key nonadiabatic decay routes. Our results indicate that the predominant decay pathway initiated at the Franck-Condon region is toward the S{sub 2}/S{sub 1} conical intersection point and S{sub 2}T{sub 3} intersystem crossing point, but not toward the S{sub 2}T{sub 2} intersystem crossing point.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Demonstration of VOC Fenceline Sensors and Canister Grab Sampling near Chemical Facilities in Louisville, Kentucky

Experimental fenceline sensor pods (SPods) fitted with 30 s duration canister grab sampling (CGS) systems were deployed at a site near chemical facilities in Louisville, KY, from 4 June 2018 to 5 January 2020. The objective of the study was to better understand lower cost 10.6 eV photoionization detector (PID)-based volatile organic compound (VOC) sensors and investigate their utility for near-source emissions detection applications. Prototype SPods containing PID sensor elements from two different manufacturers yielded between 78% and 86% valid data over the study, producing a dataset of over 120,000 collocated pair fenceline measurements averaged into 5-min datapoints. Ten-second time-resolved SPod data from an elevated fenceline sensor signal day are presented, illustrating source emission detections from the direction of a facility 500 m west of the monitoring site. An SPod-triggered CGS acquired in the emission plume on this day contained elevated concentrations of 1,3-butadiene and cyclohexane (36 parts per billion by volume (ppbv) and 637 ppbv, respectively), compounds known to be emitted by this facility. Elevated concentrations of these compounds were observed in a subset of the 61 manual and triggered CGS grab samples acquired during the study, with winds from the west. Using novel wind-resolved visualization and normalization approaches described herein, the collocated pair SPod datasets exhibited similarity in emission source signature. With winds from the west, approximately 50% of SPod readings were above our defined theoretical detection limit indicating persistent measurable VOC signal at this site. Overall, this 19-month study demonstrated reasonable prototype SPod operational performance indicating that improved commercial forms of lower cost PID sensors could be useful for select VOC fenceline monitoring applications.

1,3-butadiene↗
DOE OSTI2018

Shadow of Schwarzschild–Tangherlini black holes

We study the shadow cast by the higher-dimensional Schwarzschild–Tangherlini black hole, and analytically calculate the influence of extra dimensions on the shadow of a black hole. A black hole casts a shadow as an optical appearance because of its strong gravitational field which is known to be a dark zone covered by a circle for a Schwarzschild black hole. We demonstrate that the null geodesic equation can be integrated by Hamilton–Jacobi approach, which enable us to investigate the shadow cast by the higher-dimensional Schwarzschild–Tangherlini black holes. Interestingly, it turns out that, for fixed values of the mass parameter, the shadow in higher-dimensional spacetimes are smaller when compared with four-dimensional Schwarzschild black hole. Further, the shadows of higher-dimensional Schwarzschild–Tangherlini black holes are concentric circles with radius of the circle decreases with increase in D. We visualize the photon regions and the shadows in various dimensions for different values of the parameters, and the energy emission rates are is also investigated. Our results, in the limit D=4, reduced exactly to vis-à-vis Schwarzschild black hole case.

79 ASTRONOMY AND ASTROPHYSICS↗