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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Preparation and analysis of multilayer composites based on polyelectrolyte complexes

A method for preparing multilayer film composites based on chitosan has been developed by the example of polymer pairs: chitosan–hyaluronic acid, chitosan–alginic acid, and chitosan–carrageenan. The structure of the composite films is characterized by X-ray diffractometry and scanning electron microscopy. It is shown that the deposition of a solution of hyaluronic acid, alginic acid, or carrageenan on a chitosan gel film leads to the formation of a polyelectrolyte complex layer at the interface, which is accompanied by the ordering of chitosan chains in the surface region; the microstructure of this layer depends on the nature of contacting polymer pairs.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

REopt: Energy Decision Analysis [Slides]

REopt transforms complex energy project decisions into actionable results for building owners, utilities, and industry. Based on decades of NREL decision-support expertise, REopt guides investment in economic, resilient energy technologies. This presentation provides an overview of how REopt can help building owners, utilities, developers, and industry optimize the economic and resilience benefits of distributed energy resources.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Jas4pp — A data-analysis framework for physics and detector studies

This paper describes the Jas4pp framework for exploring physics cases and for detector-performance studies of future particle collision experiments. Jas4pp is a multi-platform Java program for numeric calculations, scientific visualization in 2D and 3D, storing data in various file formats and displaying collision events and detector geometries. It also includes complex data-analysis algorithms for function minimization, regression analysis, event reconstruction (such as jet reconstruction), limit settings and other libraries widely used in particle physics. The framework can be used with several scripting languages, such as Python/Jython, Groovy and JShell. Several benchmark tests discussed in the paper illustrate significant improvements in the performance of the Groovy and JShell scripting languages compared to the standard Python implementation in C. Furthermore, the improvements for numeric computations in Java are attributed to recent enhancements in the Java Virtual Machine.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Plutonium Particles in Samples Extracted from Hanford Tank Waste TX-118 and SY-102 (Interim Report)

This is an interim report on the characterization of plutonium particles from Hanford wastes. Plutonium-bearing particles were located in Hanford Waste Tank solids, SY-102 and TX-118. The particles in SY-102 were small, typically < 5 to 10 µm in length, and were crystalline plutonium oxide with an association of other elements at minor levels, including bismuth, phosphate, and iron based on Sanning Electron Microscopy (SEM) observations. Plutonium particles from SY-102 were extracted from the surface mount using the SEM-Focused Ion Beam (FIB) and prepared for Scanning Transmission Electron Microscopy (STEM). This was the first time that this type of analysis of Hanford tank waste solids has been attempted. The STEM analysis indicated a complex co-precipitation of plutonium oxide with bismuth and phosphate. Diffraction and imaging only partially matched with a PuO 2 phase. Pockets of phosphate and bismuth reside within the plutonium oxide suggesting that these phases formed at the same time. The SEM analysis indicated that the plutonium particles from TX-118 were a mixed bismuth-phosphate phase and plutonium oxide. These particles will be examined with SEM-FIB at a later time and then will undergo more detailed examination in the STEM.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Working Group on Virtual Data Integration

This report is the outcome of a workshop commissioned by the U.S. Department of Energy’s (DOE) Climate and Environmental Sciences Division (CESD) to examine current and future data infrastructure requirements foundational for achieving CESD scientific mission goals in advancing a robust, predictive understanding of Earth’s climate and environmental systems. Over the past several years, data volumes in CESD disciplines have risen sharply to unprecedented levels (tens of petabytes). Moreover, the complexity and diversity of this research data— including simulations, observations, and reanalysis— have grown significantly, posing new challenges for data capture, storage, verification, analysis, and integration. With the trends of increased data volume (in the hundreds of petabytes), more complex analysis processes, and growing cross-disciplinary collaborations, it is timely to investigate whether the CESD community has the computational and data support needed to fully realize the scientific potential of its data collections. In recognition of the challenges, a partnership is forming across CESD and among national and international agencies to examine the viability of creating an integrated, collaborative data infrastructure: a Virtual Laboratory. The overarching goal of this report is to identify the community’s key data technology requirements and high-priority development needs for sustaining and growing its scientific discovery potential. The report also aims to map these requirements to existing solutions and to identify gaps in current services, tools, and infrastructure that will need to be addressed in the short, medium, and long term to advance scientific progress.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Specificity determinants revealed by the structure of glycosyltransferase Campylobacter concisus PglA

Abstract In selected Campylobacter species, the biosynthesis of N‐linked glycoconjugates via the pgl pathway is essential for pathogenicity and survival. However, most of the membrane‐associated GT‐B fold glycosyltransferases responsible for diversifying glycans in this pathway have not been structurally characterized which hinders the understanding of the structural factors that govern substrate specificity and prediction of resulting glycan composition. Herein, we report the 1.8 Å resolution structure of Campylobacter concisus PglA, the glycosyltransferase responsible for the transfer of N ‐acetylgalatosamine (GalNAc) from uridine 5′‐diphospho‐ N ‐acetylgalactosamine (UDP‐GalNAc) to undecaprenyl‐diphospho‐ N , N ′‐diacetylbacillosamine (UndPP‐diNAcBac) in complex with the sugar donor GalNAc. This study identifies distinguishing characteristics that set PglA apart within the GT4 enzyme family. Computational docking of the structure in the membrane in comparison to homologs points to differences in interactions with the membrane‐embedded acceptor and the structural analysis of the complex together with bioinformatics and site‐directed mutagenesis identifies donor sugar binding motifs. Notably, E113, conserved solely among PglA enzymes, forms a hydrogen bond with the GalNAc C6″‐OH. Mutagenesis of E113 reveals activity consistent with this role in substrate binding, rather than stabilization of the oxocarbenium ion transition state, a function sometimes ascribed to the corresponding residue in GT4 homologs. The bioinformatic analyses reveal a substrate‐specificity motif, showing that Pro281 in a substrate binding loop of PglA directs configurational preference for GalNAc over GlcNAc. This proline is replaced by a conformationally flexible glycine, even in distant homologs, which favor substrates with the same stereochemistry at C4, such as glucose. The signature loop is conserved across all Campylobacter PglA enzymes, emphasizing its importance in substrate specificity.

Vuksanovic, Nemanja↗
DOE OSTI2018

Conceptual Advances from Werner Complexes to Metal–Organic Frameworks

Alfred Werner's work on the geometric aspects of how ligands bind to metal ions at the end of the 19th century has given rise, in the molecular realm, to organometallic, bioinorganic, and cluster chemistries. By stitching together organic and inorganic units into crystalline porous metal-organic frameworks (MOFs), the connectivity, spatial arrangement, and geometry of those molecular complexes can now be fixed in space and become directly addressable. The fact that MOFs are porous provides additional space within which molecules can further be transformed and their chemistry controlled. Finally, an aspect not available in molecular chemistry but a direct consequence of Werner's analysis of coordination complexes is the ability to have multivariable functionality in MOFs to bring about a continuum of chemical environments, within the repeating order of the framework, from which a substrate can sample and be transformed in ways not possible in molecular complex chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Characterisation of two-stage ignition in diesel engine-relevant thermochemical conditions using direct numerical simulation

With the goal of providing a more detailed fundamental understanding of ignition processes in diesel engines, this study reports analysis of a direct numerical simulation (DNS) database. In the DNS, a pseudo turbulent mixing layer of dimethyl ether (DME) at 400 K and air at 900 K is simulated at a pressure of 40 atmospheres. At these conditions, DME exhibits a two-stage ignition and resides within the negative temperature coefficient (NTC) regime of ignition delay times, similar to diesel fuel. The analysis reveals a complex ignition process with several novel features. Autoignition occurs as a distributed, two-stage event. The high-temperature stage of ignition establishes edge flames that have a hybrid premixed/autoignition flame structure similar to that previously observed for lifted laminar flames at similar thermochemical conditions. In conclusion, a combustion mode analysis based on key radical species illustrates the multi-stage and multi-mode nature of the ignition process and highlights the substantial modelling challenge presented by diesel combustion.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

MOOSE ProbML: Parallelizable Probabilistic Machine Learning and Uncertainty Quantification Capabilities

The Multiphysics Object Oriented Simulation Environment (MOOSE) is a widely used open- source finite element software for performing multiphysics multiscale simulations in a massively parallel fashion. Recently, the computational team at Idaho National Laboratory (INL) has implemented Probabilistic Machine Learning (ProbML) capabilities in MOOSE—in a parallelized fashion—and enable active learning with large-scale computational models for tasks such as surrogate model development, scale bridging, forward/inverse uncertainty quantification (UQ), Bayesian optimization, etc. This presentation summarizes these developments in MOOSE along with demonstrations on several real applications relevant to nuclear energy. At the fundamental level, samplers like Monte Carlo/Latin Hypercube, variance reduction, parallelized Markov Chain Monte Carlo (MCMC) support uncertainty propagation in both forward and inverse settings. These samplers can be integrated with the Gaussian processes (GP) suite in MOOSE, which offer several variants like scalar GPs, multi-output GPs, and deep GPs, to enable active learning. These GPs can be tuned using gradient-based optimization methods like Adam and its variants or gradient-free methods like the elliptical slice sampler (a variant of MCMC adept under Gaussian settings) for more complex covariance kernels or likelihoods whose gradient computations can be cumbersome. A variety of batch acquisition functions permit parallelized evaluation of the computational model and support different learning objectives with high efficiency like Bayesian inference, global surrogate development, optimization, etc. Furthermore, libtorch integration supports training, evaluation, and re-training of neural networks and other complex machine learning models in active learning settings. The impacts of these developments are shown on several real applications: (1) nuclear fuel inverse UQ and model inadequacy assessment using the Kennedy O’Hagan framework; (2) uncertainty aware surrogate modeling for additive manufacturing to predict field quantities; (3) nuclear reactor rare events analysis; and (4) complex fluid flow prediction using a global surrogate with quantified prediction uncertainty. Finally, the outlook of MOOSE ProbML is discussed for both outer-loop and inner-loop computations in the broad view to accelerate fuels and materials qualification, address gaps in knowledge and data, and assess new reactor/fuel systems.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

XANES reflects coordination change and underlying surface disorder of zinc adsorbed to silica

In this work, zinc K -edge X-ray absorption near-edge structure (XANES) spectroscopy of Zn adsorbed to silica and Zn-bearing minerals, salts and solutions was conducted to explore how XANES spectra reflect coordination environment and disorder in the surface to which a metal ion is sorbed. Specifically, XANES spectra for five distinct Zn adsorption complexes (Zn ads ) on quartz and amorphous silica [SiO 2(am) ] are presented from the Zn–water–silica surface system: outer-sphere octahedral Zn ads on quartz, inner-sphere octahedral Zn ads on quartz, inner-sphere tetrahedral Zn ads on quartz, inner-sphere octahedral Zn ads on SiO 2(am) and inner-sphere tetrahedral Zn ads on SiO 2(am) . XANES spectral analysis of these complexes on quartz versus SiO 2(am) reveals that normalized peak absorbance and K -edge energy position generally decrease with increasing surface disorder and decreasing Zn–O coordination. On quartz, the absorption-edge energy of Zn ads ranges from 9663.0 to 9664.1 eV for samples dominated by tetrahedrally versus octahedrally coordinated species, respectively. On SiO 2(am) , the absorption-edge energy of Zn ads ranges from 9662.3 to 9663.4 eV for samples dominated by tetrahedrally versus octahedrally coordinated species, respectively. On both silica substrates, octahedral Zn ads presents a single K -edge peak feature, whereas tetrahedral Zn ads presents two absorbance features. The energy space between the two absorbance peak features of the XANES K -edge of tetrahedral Zn ads is 2.4 eV for Zn on quartz and 3.2 eV for Zn on SiO 2(am) . Linear combination fitting of samples with a mixture of Zn ads complex types demonstrates that the XANES spectra of octahedral and tetrahedral Zn ads on silica are distinct enough for quantitative identification. These results suggest caution when deciphering Zn speciation in natural samples via linear combination approaches using a single Zn ads standard to represent sorption on a particular mineral surface. Correlation between XANES spectral features and prior extended X-ray absorption fine structure (EXAFS) derived coordination environments for these Zn ads on silica samples provides insight into Zn speciation in natural systems with XANES compatible Zn concentrations too low for EXAFS analysis.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Automated Extraction of Energy Systems Information from Remotely Sensed Data: A Review and Analysis

We report high quality energy systems information is a crucial input to energy systems research, modeling, and decision-making. Unfortunately, actionable information about energy systems is often of limited availability, incomplete, or only accessible for a substantial fee or through a non-disclosure agreement. Recently, remotely sensed data (e.g., satellite imagery, aerial photography) have emerged as a potentially rich source of energy systems information. However, the use of these data is frequently challenged by its sheer volume and complexity, precluding manual analysis. Recent breakthroughs in machine learning have enabled automated and rapid extraction of useful information from remotely sensed data, facilitating large-scale acquisition of critical energy system variables. Here we present a systematic review of the literature on this emerging topic, providing an in-depth survey and review of papers published within the past two decades. We first taxonomize the existing literature into ten major areas, spanning the energy value chain. Within each research area, we distill and critically discuss major features that are relevant to energy researchers, including, for example, key challenges regarding the accessibility and reliability of the methods. We then synthesize our findings to identify limitations and trends in the literature as a whole, and discuss opportunities for innovation. These include the opportunity to extend the methods beyond electricity to broader energy systems and wider geographic areas; and the ability to expand the use of these methods in research and decision making as satellite data become cheaper and easier to access. We also find that there are persistent challenges: limited standardization and rigor of performance assessments; limited sharing of code, which would improve replicability; and a limited consideration of the ethics and privacy of data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Partitioning of Large-Scale Power Electronics-Based Power Systems for Small-Signal Stability Analysis

The nodal admittance matrix (NAM)-based approach is suitable for analyzing the small-signal stability of large-scale power electronics-based power systems (PEPSs) as it preserves the system structure by utilizing the admittance matrix. Previously, NAM-based area partition has been proposed, which divides the system into various subareas and interconnections for easier analysis of the low-dimension matrix compared to the entire system-based high-dimension matrix. However, no partition algorithm has been presented for the NAM-based area partition method. This paper focuses on implementing the spectral partitioning algorithm for partitioning large-scale PEPSs into a low-dimension matrix to reduce the computation complexity of the analysis. These spectral components facilitate data transformation into a new space, enabling the application of traditional clustering methods like k-means. To evaluate the performance of the partitioning method, the subareas and interconnections obtained from the spectral clustering algorithm are incorporated into the NAM-based area partition method for a large system with 140 buses. The computational times of the original method, where the NAM-based criterion is directly applied to the entire system, are compared with those of the NAM-based partition method in MATLAB. PSCAD simulations of the whole system and the obtained subareas are conducted to validate the effectiveness of the proposed algorithm.

Nupur, Nupur↗
DOE OSTI2016

Frequency domain analysis of errors in cross-correlations of ambient seismic noise

We analyse random errors (variances) in cross-correlations of ambient seismic noise in the frequency domain, which differ from previous time domain methods. Extending previous theoretical results on ensemble averaged cross-spectrum, we estimate confidence interval of stacked cross-spectrum of finite amount of data at each frequency using non-overlapping windows with fixed length. The extended theory also connects amplitude and phase variances with the variance of each complex spectrum value. Analysis of synthetic stationary ambient noise is used to estimate the confidence interval of stacked cross-spectrum obtained with different length of noise data corresponding to different number of evenly spaced windows of the same duration. This method allows estimating Signal/Noise Ratio (SNR) of noise cross-correlation in the frequency domain, without specifying filter bandwidth or signal/noise windows that are needed for time domain SNR estimations. Based on synthetic ambient noise data, we also compare the probability distributions, causal part amplitude and SNR of stacked cross-spectrum function using one-bit normalization or pre-whitening with those obtained without these pre-processing steps. Natural continuous noise records contain both ambient noise and small earthquakes that are inseparable from the noise with the existing pre-processing steps. Using probability distributions of random cross-spectrum values based on the theoretical results provides an effective way to exclude such small earthquakes, and additional data segments (outliers) contaminated by signals of different statistics (e.g. rain, cultural noise), from continuous noise waveforms. This technique is applied to constrain values and uncertainties of amplitude and phase velocity of stacked noise cross-spectrum at different frequencies, using data from southern California at both regional scale (~35 km) and dense linear array (~20 m) across the plate-boundary faults. A block bootstrap resampling method is used to account for temporal correlation of noise cross-spectrum at low frequencies (0.05–0.2 Hz) near the ocean microseismic peaks.

58 GEOSCIENCES↗
DOE OSTI2022

Natural switches in behaviour rapidly modulate hippocampal coding

Throughout their daily lives, animals and humans often switch between different behaviours. However, neuroscience research typically studies the brain while the animal is performing one behavioural task at a time, and little is known about how brain circuits represent switches between different behaviours. Here we tested this question using an ethological setting: two bats flew together in a long 135 m tunnel, and switched between navigation when flying alone (solo) and collision avoidance as they flew past each other (cross-over). Bats increased their echolocation click rate before each cross-over, indicating attention to the other bat. Hippocampal CA1 neurons represented the bat’s own position when flying alone (place coding). Notably, during cross-overs, neurons switched rapidly to jointly represent the interbat distance by self-position. This neuronal switch was very fast—as fast as 100 ms—which could be revealed owing to the very rapid natural behavioural switch. The neuronal switch correlated with the attention signal, as indexed by echolocation. Interestingly, the different place fields of the same neuron often exhibited very different tuning to interbat distance, creating a complex non-separable coding of position by distance. Theoretical analysis showed that this complex representation yields more efficient coding. Overall, our results suggest that during dynamic natural behaviour, hippocampal neurons can rapidly switch their core computation to represent the relevant behavioural variables, supporting behavioural flexibility.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

ROSE

Developed at Lawrence Livermore National Laboratory (LLNL), ROSE is an open source compiler infrastructure to build source-to-source program transformation and analysis tools for large-scale C (C89 to C23), C++ (C++98 to C++23), UPC, Fortran (Fortran4, 66, 77, 95, 2003), OpenMP, Java, Python, and Binary applications. ROSE users range from experienced compiler researchers to library and tool developers who may have minimal compiler experience. ROSE is particularly well suited for building custom tools for static analysis, program optimization, arbitrary program transformation, domain-specific optimizations, complex loop optimizations, performance analysis, and cyber-security. ROSE is: A library (and set of associated tools) to quickly and easily apply compiler techniques to one's code in order to improve application performance and developer productivity. A research and development compiler infrastructure for for writing custom source-to-source translators to perform source code transformations, analysis, and optimizations. Is

Pinnow, NathanT [Lawrence Livermore National Labor↗
DOE OSTI2021

Structural Polymorphism of Chitin and Chitosan in Fungal Cell Walls From Solid-State NMR and Principal Component Analysis

Chitin is a major carbohydrate component of the fungal cell wall and a promising target for novel antifungal agents. However, it is technically challenging to characterize the structure of this polymer in native cell walls. Here, we recorded and compared 13 C chemical shifts of chitin using isotopically enriched cells of six Aspergillus, Rhizopus, and Candida strains, with data interpretation assisted by principal component analysis (PCA) and linear discriminant analysis (LDA) methods. The structure of chitin is found to be intrinsically heterogeneous, with peak multiplicity detected in each sample and distinct fingerprints observed across fungal species. Fungal chitin exhibits partial similarity to the model structures of α- and γ-allomorphs; therefore, chitin structure is not significantly affected by interactions with other cell wall components. Addition of antifungal drugs and salts did not significantly perturb the chemical shifts, revealing the structural resistance of chitin to external stress. In addition, the structure of the deacetylated form, chitosan, was found to resemble a relaxed two-fold helix conformation. This study provides high-resolution information on the structure of chitin and chitosan in their cellular contexts. The method is applicable to the analysis of other complex carbohydrates and polymer composites.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

On the conformational stability of the smallest RNA kissing complexes maintained through two G·C base pairs

Two identical 5′GACG3′ tetra-loop motifs with different stem sequences (called H2 and H3) are found in the 5′ end region of Moloney Murine Leukemia Virus (MMLV) genomic RNA. They play important roles in RNA dimerization and encapsidation through two identical tetra-loops (5′GACG3′) forming a loop-to-loop kissing complex, the smallest RNA kissing complex ever found in nature. We examined the effects of a loop-closing base pair as well as a stem sequence on the conformational stability of the kissing complex. UV melting analysis and gel electrophoresis were performed on eight RNA sequences mimicking the H2 and H3 hairpin tetra-loops with variation in loop-closing base pairs. Our results show that changing the loop-closing base pair from the wildtype (5′A·U3′ for H3, 5′U·A3′ for H2) to 5′G·C3’/5′C·G3′ has significant effect on the stability of the kissing complexes: the substitution to 5′C·G3′ significantly decreases both thermal and mechanical stability, while switching to the 5′G·C3′ significantly increases the mechanical stability only. The kissing complexes with the wildtype loop-closing base pairs (5′A·U3′ for H3 and 5′U·A3′ for H2) show different stability when attached to a different stem sequence (H2 stem vs. H3 stem). This suggests that not only the loop-closing base pair itself, but also the stem sequence, affects the conformational stability of the RNA kissing complex. - Highlights: • Thermodynamic parameters of the smallest RNA kissing interactions were measured. • The effects of loop-closing base pairs on the RNA kissing complex was investigated. • Changing the base pair to 5′CG3′ decreases the stability of the kissing complex. • Changing it to 5′GC3′ increases the mechanical resilience of the kissing complex. • Difference in its stem sequence also affects the stability of the kissing complex.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Synthesis, structure, luminescence and photocatalytic properties of an uranyl-2,5-pyridinedicarboxylate coordination polymer

An uranium coordination polymer, namely [(UO{sub 2}(pydc)(H{sub 2}O)]·H{sub 2}O (1) (H{sub 2}pydc=2,5-pyridinedicarboxylic acid), has been obtained by hydrothermal method and characterized by X-ray single crystal structure determination. Structural analysis reveals that complex 1 exhibits 1D chain coordination polymer, in which UO{sub 2}{sup 2+} ions are bridged by 2,5-pyridinedicarboxylate ligands and the chains are connected into a 3D supramolecular network by O–H···O hydrogen bond interactions and π–π stacking interactions. The photocatalytic properties of 1 for degradation of methylene blue (MB), Rhodamine B (RhB) and methyl orange (MO) under Hg-lamp irradiation have been performed, and the amount of the catalyst as well as Hg-lamp irradiation with different power on the photodegradation efficiency of MB have been investigated. Elemental analyses, infrared spectroscopy, TG-DTA analyses and luminescence properties were also discussed. - Graphical abstract: Complex 1 exhibits 1D chain coordination polymer in which UO{sub 2}{sup 2+} ions are bridged by 2,5-pyridinedicarboxylate ligand. Photoluminescence studies reveal that complex 1 exhibits characteristic emissions of uranyl centers. The compound is selective to degraded dye and displays good photocatalytic activities for the degradation of MB under Hg-lamp. Display Omitted - Highlights: • Complex 1 exhibits 1D chain coordination polymer. • Complex 1 could degrade methylene blue and Rhodamine B under Hg-lamp irradiation. • Luminescent property of 1 has been studied.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗