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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

State of practice and emerging application of analytical techniques of nuclear forensic analysis: highlights from the 4th Collaborative Materials Exercise of the Nuclear Forensics International Technical Working Group (ITWG)

Founded in 1996 upon the initiative of the “Group of 8” governments (G8), the Nuclear Forensics International Technical Working Group (ITWG) is an ad hoc organization of official nuclear forensics practitioners (scientists, law enforcement, and regulators) that can be called upon to provide technical assistance to the global community in the event of a seizure of nuclear or radiological materials. The ITWG is supported by and is affiliated with roughly 40 countries and international partner organizations including the International Atomic Energy Agency (IAEA), EURATOM, INTERPOL, EUROPOL, and the United Nations Interregional Crime and Justice Research Institute (UNICRI). Besides providing a network of nuclear forensics laboratories that are able to assist law enforcement during a nuclear smuggling event, the ITWG is also committed to the advancement of the science of nuclear forensic analysis, largely through participation in periodic table top and Collaborative Materials Exercises (CMXs). Exercise scenarios use “real world” samples with realistic forensics investigation time constraints and reporting requirements. These exercises are designed to promote best practices in the field and test, evaluate, and improve new technical capabilities, methods and techniques in order to advance the science of nuclear forensics. The ITWG recently completed its fourth CMX in the 20 year history of the organization. This was also the largest materials exercise to date, with participating laboratories from 16 countries or organizations. Three samples of low enriched uranium were shipped to these laboratories as part of an illicit trafficking scenario, for which each laboratory was asked to conduct nuclear forensic analyses in support of a fictitious criminal investigation. An objective review of the State Of Practice and Art of international nuclear forensic analysis based upon the outcome of this most recent exercise is provided.

ITWG CMX-4↗
DOE OSTI2014

Power System Transient Stability Analysis through a Homotopy Analysis Method

As an important function of energy management systems (EMSs), online contingency analysis plays an important role in providing power system security warnings of instability. At present, N-1 contingency analysis still relies on time-consuming numerical integration. To save computational cost, the paper proposes a quasi-analytical method to evaluate transient stability through time domain periodic solutions’ frequency sensitivities against initial values. First, dynamic systems described in classical models are modified into damping free systems whose solutions are either periodic or expanded (non-convergent). Second, because the sensitivities experience sharp changes when periodic solutions vanish and turn into expanded solutions, transient stability is assessed using the sensitivity. Third, homotopy analysis is introduced to extract frequency information and evaluate the sensitivities only from initial values so that time consuming numerical integration is avoided. Finally, a simple case is presented to demonstrate application of the proposed method, and simulation results show that the proposed method is promising.

Wang, Shaobu↗
DOE OSTI2019

The SCALE/AMPX multigroup cross section processing for fast reactor analysis

The SCALE/AMPX multigroup (MG) cross section processing procedure has been updated to minimize reactivity differences for fast reactor designs and boiling water reactors (BWRs) with very high void fractions to provide excellent agreement with continuous-energy reference calculations. SCALE MG calculations are widely applied to thermal spectrum light-water reactor (LWR) systems as well as fast spectrum metallic systems of interest to National Nuclear Security Administration. With growing interest from industry and regulators in applying SCALE for the design of fast spectrum reactors, both sodium and molten salt, and in the licensing of power up rates for BWRs, it is desirable to review the SCALE/AMPX procedure for unresolved resonance self-shielded data and high energy neutron spectra. The data were improved by generating MG unresolved resonance data based on the analytic probability table method with the narrow resonance approximation as well as the use of a very fine group structure typically used in fast system analysis. This study focused on verifying the probability table and the SCALE/AMPX MG cross section processing procedure by performing reaction rate analysis and benchmark calculations for various fast reactor and high void BWR systems. Here, results indicate that the improved SCALE/AMPX MG cross section processing provides excellent results for the fast reactor analysis.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

Self-consistent clustering analysis: an efficient multiscale scheme for inelastic heterogeneous materials

A predictive computational theory is shown for modeling complex, hierarchical materials ranging from metal alloys to polymer nanocomposites. The theory can capture complex mechanisms such as plasticity and failure that span across multiple length scales. This general multiscale material modeling theory relies on sound principles of mathematics and mechanics, and a cutting-edge reduced order modeling method named self-consistent clustering analysis (SCA) [Zeliang Liu, M.A. Bessa, Wing Kam Liu, “Self-consistent clustering analysis: An efficient multi-scale scheme for inelastic heterogeneous materials,” Comput. Methods Appl. Mech. Engrg. 306 (2016) 319–341]. SCA reduces by several orders of magnitude the computational cost of micromechanical and concurrent multiscale simulations, while retaining the microstructure information. This remarkable increase in efficiency is achieved with a data-driven clustering method. Computationally expensive operations are performed in the so-called offline stage, where degrees of freedom (DOFs) are agglomerated into clusters. The interaction tensor of these clusters is computed. In the online or predictive stage, the Lippmann-Schwinger integral equation is solved cluster-wise using a self-consistent scheme to ensure solution accuracy and avoid path dependence. To construct a concurrent multiscale model, this scheme is applied at each material point in a macroscale structure, replacing a conventional constitutive model with the average response computed from the microscale model using just the SCA online stage. A regularized damage theory is incorporated in the microscale that avoids the mesh and RVE size dependence that commonly plagues microscale damage calculations. The SCA method is illustrated with two cases: a carbon fiber reinforced polymer (CFRP) structure with the concurrent multiscale model and an application to fatigue prediction for additively manufactured metals. For the CFRP problem, a speed up estimated to be about 43,000 is achieved by using the SCA method, as opposed to FE2, enabling the solution of an otherwise computationally intractable problem. The second example uses a crystal plasticity constitutive law and computes the fatigue potency of extrinsic microscale features such as voids. This shows that local stress and strain are capture sufficiently well by SCA. This model has been incorporated in a process-structure-properties prediction framework for process design in additive manufacturing.

Liu, Z.↗
DOE OSTI2014

Structural Analysis of N- and O-glycans Using ZIC-HILIC/Dialysis Coupled to NMR Detection

Protein glycosylation, an important and complex post-translational modification (PTM), is involved in various biological processes including the receptor-ligand and cell-cell interaction, and plays a crucial role in many biological functions. However, little is known about the glycan structures of important biological complex samples, and the conventional glycan enrichment strategy (i.e., size-exclusion column [SEC] separation,) prior to nuclear magnetic resonance (NMR) detection is time-consuming and tedious. In this study, we employed SEC, Zwitterionic hydrophilic interaction liquid chromatography (ZIC-HILIC), and ZIC-HILIC coupled with dialysis strategies to enrich the glycopeptides from the pronase E digests of RNase B, followed by NMR analysis of the glycoconjugate. Our results suggest that the ZIC-HILIC enrichment coupled with dialysis is the most efficient, which was thus applied to the analysis of biological complex sample, the pronase E digest of the secreted proteins from the fungi Aspergillus niger. The NMR spectra revealed that the secreted proteins from A. niger contain both N-linked glycans with a high-mannose core and O-linked glycans bearing mannose and glucose with 1->3 and 1->6 linkages. In all, our study provides compelling evidence that ZIC-HILIC separation coupled to dialysis is superior to the commonly used SEC separation to prepare glycopeptides for the downstream NMR analysis, which could greatly facilitate the future NMR-based glycoproteomics research.

A.niger↗
DOE OSTI2023

Exploratory analysis of machine learning techniques in the Nevada geothermal play fairway analysis

Play fairway analysis (PFA) is commonly used to generate geothermal potential maps and guide exploration studies, with a particular focus on locating and characterizing blind geothermal systems. This study evaluates the application of machine learning techniques to PFA in the Great Basin region of Nevada. Following the evaluation of various techniques, we identified two approaches to PFA that produced promising results, 1) supervised Bayesian probabilistic neural networks to generate geothermal potential maps with confidence intervals, and 2) unsupervised principal component analysis paired with k-means clustering to generate both cluster maps to help identify spatial patterns, as well as new combined feature inputs. We applied these techniques to perform a comparative analysis between two principal sets of geological and geophysical features related to permeability and heat and a set of positive (known geothermal resources) and negative training sites (known drill sites with unsuitable geothermal conditions). We found that these methods constrain previously unrecognized feature controls on geothermal favorability, many of which are spatially organized within the extent of cluster groups and the major structural-hydrologic domains of the study area. Furthermore, we utilized exploratory unsupervised modeling to highlight spatial relationships between input data and predictive output results of our supervised modeling. As a result, we demonstrate how our models compare to the previous Nevada PFA and how the rapid insights these machine learning techniques offer may support future assessments of both known and undiscovered blind geothermal systems in the Great Basin region of Nevada and beyond.

15 GEOTHERMAL ENERGY↗
DOE OSTI2018

Subnanogram proteomics: Impact of LC column selection, MS instrumentation and data analysis strategy on proteome coverage for trace samples

One of the greatest challenges for mass spectrometry (MS)-based proteomics is the limited ability to analyze small samples. Here we investigate the relative contributions of liquid chromatography (LC), MS instrumentation and data analysis methods with the aim of improving proteome coverage for sample sizes ranging from 0.5 ng to 50 ng. We show that the LC separations utilizing 30-µm-i.d. columns increase signal intensity by >3-fold relative to those using 75-µm-i.d. columns, leading to 32% increase in peptide identifications. The Orbitrap Fusion Lumos mass spectrometer significantly boosted both sensitivity and sequencing speed relative to earlier generation Orbitraps (e.g., LTQ-Orbitrap), leading to a ~3× increase in peptide identifications and 1.7× increase in identified protein groups for 2 ng tryptic digests of bacterial lysate. The Match Between Runs algorithm of open-source MaxQuant software further increased proteome coverage by ~ 95% for 0.5 ng samples and by ~42% for 2 ng samples. The present platform is capable of identifying >3000 protein groups from tryptic digestion of cell lysates equivalent to 50 HeLa cells and 100 THP-1 cells (~10 ng total proteins), respectively, and >950 proteins from subnanogram bacterial and archaeal cell lysates. The present ultrasensitive LC-MS platform is expected to enable deep proteome coverage for subnanogram samples, including single mammalian cells.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2018

Microstructural analysis of undoped and moderately Sc-doped TiO2 anatase nanoparticles using Scherrer equation and Debye function analysis

Highlights: • UV light sensitive undoped and moderate Sc-doped anatase nanocrystallites were prepared without post-synthesis annealing. • Elongated nanocrystallites were found by Scherrer equation and Debye Function Analysis applied to XRD data and also HRTEM. • 4 at.% Sc doping reduced the amount of Ti vacancies by half. • Doping showed ~0.3% growth of lattice parameters. - Abstract: UV light sensitive undoped and moderate (4 at.%) Sc-doped anatase nanocrystallites were prepared by an efficient and environmentally benign method based on homogeneous hydrolysis of TiOSO{sub 4} and Sc{sub 2}(C{sub 2}O{sub 4}){sub 3.5}H{sub 2}O aqueous solutions using urea as a precipitation agent, without post-synthesis calcination or annealing. X-ray diffraction study of the obtained powders revealed single phase anatase in both samples. Two different methods were applied to estimate the anatase crystallite size and shape from the X-ray diffraction data. The first one is based on the more conventional Scherrer equation (as implanted in GSAS-II program) while the second one is based on Debye function analysis (as implanted in DUBUSSY suite version 2.2), which is considered to be more adequate for nanocrystallites. Although each program has its own shape models, both methods indicated similar results of elongated nanocrystallite geometry for Sc-doped TiO{sub 2}: (i) GSAS-II confirmed ellipsoid shape with equatorial size of 5.1(0) nm and axial size of 6.8(0), (ii) DEBUSSY suite 2.2 showed cylinder shape with diameter of equivalent circle in the ab-plane, D{sub ab} = 4.9(1.0) nm and crystallite length along the c-axis, L{sub c} = 5.4(3.2) nm. For the undoped TiO{sub 2} sample, equatorial size of 5.5(0) nm and axial size of 7.3(0) nm for the ellipsoid shape was determined according to GSAS-II, while D{sub ab} = 5.5(1.3) nm and L{sub c} = 6.0(2.2) nm for the cylinder shape was determined by DEBUSSY suite 2.2. These outcomes were found to corroborate with HRTEM analysis. Doping with 4 at.% Sc caused ~0.3% growth of lattice parameters from a = 3.7979 [4] Å, c = 9.4995 [9] Å for the undoped sample to a = 3.8110 [7] Å, c = 9.5274 [16] Å for the moderately Sc doped sample, while reduction in the Ti vacancies by half was confirmed by both methods. The introducing of Sc as electronically active secondary species into the crystal lattice of TiO{sub 2} can greatly alter its optical absorption. The incorporation of Sc into the crystal lattice of TiO{sub 2} favors the substitution of Ti, as both have approximately the same ionic size, and generates surface oxygen vacancies which can act as trapping center for the photogenerated electrons and reduce the recombination of electron–hole pairs. We can expect Sc doped TiO{sub 2} nanomaterials to have applications as effective photocatalysts for selective photocatalytic oxidation of various environmental organic pollutants.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2018

Analysis of the Frequency and Diversity of 1,3-Dialkylimidazolium Ionic Liquids Appearing in the Literature

The hypothetical assertion that there are potentially millions of ionic liquids (ILs) can be validated using basic knowledge of IL precursors and simple calculations. While it is an interesting thought exercise to ponder the possibilities of ILs, it is important to investigate how many discrete ILs (i.e., unique cation and anion pairings) have actually been synthesized and reported in the literature. A complete analysis of all ILs is a daunting task, especially if the definition of what constitutes an IL is broad. Nonetheless, insight can be gained into the use of ILs over the past ~20 years from a focused analysis of systematically varied 1,3-dialkylimidazolium-based ILs (i.e., [R 1 R 2 im][X], where R 1 and R 2 are n-alkyl chains and X is either a halide or molecular anion). This family of ILs includes many of the most widely used and most thoroughly studied IL substances, including 1-butyl-3-methylimidazolium hexafluorophosphate ([C 4 mim][PF 6 ]) and 1-ethyl-3-methylimidazolium bistriflimide ([C 2 mim][Tf 2 N]). Using data retrieved from SciFinder searches, we analyzed the variety and frequency of 1,3-dialkylimidazolium-based ILs appearing in the literature. Our analysis reveals that there is a relatively large number of simple 1,3-dialkylimidazolium cations which have not yet been synthesized. Our findings indicate that despite the broad possibilities of IL structures available, there are but a handful of ILs that are commonly used and studied. Within the 1248 [R 1 R 2 im][X] ILs studied, there were only 12 cations extensively used, which included [R 1 R 2 im] + (R 1 = C 1 and R 2 = C 1 –C 12 ). Of the 16 anions studied, only 5, including [BF 4 ] – , [Cl] – , [PF 6 ] – , [Tf 2 N] – , and [Br] – , were used significantly. Thus, it appears that although ILs can be used as designer solvents with task-specific properties, there is a small default subset of ILs, which are “go-to” or “one-size-fits-all.” Here, we rationalize the current state of the IL landscape in terms of the historical perceptions (and misconceptions) around ILs, familiarity, availability and cost of starting materials, commercial availability of ILs, and the motivations from which researchers choose to synthesize and characterize new ILs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗