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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 1,387 records · Page 77
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

A preconditioned dual–primal finite element tearing and interconnecting method for solving three-dimensional time-harmonic Maxwell's equations

A new preconditioned dual–primal nonoverlapping domain decomposition method is proposed for the finite element solution of three-dimensional large-scale electromagnetic problems. With the aid of two Lagrange multipliers, the new method converts the original volumetric problem to a surface problem by using a higher-order transmission condition at the subdomain interfaces to significantly improve the convergence of the iterative solution of the global interface equation. Similar to the previous version, a global coarse problem related to the degrees of freedom at the subdomain corner edges is formulated to propagate the residual error to the whole computational domain at each iteration, which further increases the rate of convergence. In addition, a fully algebraic preconditioner based on matrix splitting is constructed to make the proposed domain decomposition method even more robust and scalable. Perfectly matched layers (PMLs) are considered for the boundary truncation when solving open-region problems. The influence of the PML truncation on the convergence performance is investigated by examining the convergence of the transmission condition for an interface inside the PML. Numerical examples including wave propagation and antenna radiation problems truncated with PMLs are presented to demonstrate the validity and the capability of this method.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Delayed gamma-ray spectroscopy with lanthanum bromide detector for non-destructive assay of nuclear material

High-energy delayed γ-ray spectroscopy is a potential technique for directly assaying spent fuel assemblies and achieving the safeguards goal of quantifying nuclear material inventories for spent fuel handling, interim storage, reprocessing facilities, repository sites, and final disposal. Requirements for the γ-ray detection system, up to ~6 MeV, can be summarized as follows: high efficiency at high γ-ray energies, high energy resolution, good linearity between γ-ray energy and output signal amplitude, ability to operate at very high count rates, and ease of use in industrial environments such as nuclear facilities. High Purity Germanium Detectors (HPGe) are the state of the art and provide excellent energy resolution but are limited in their count rate capability. Lanthanum Bromide (LaBr 3 ) scintillation detectors offer significantly higher count rate capabilities at lower energy resolution. Thus, LaBr 3 detectors may be an effective alternative for nuclear spent-fuel applications, where count-rate capability is a requirement. This paper documents the measured performance of a 2” (length) × 2” (diameter) of LaBr3 scintillation detector system, coupled to a negatively biased PMT and a tapered active high voltage divider, with count-rates up to ~3 Mcps. An experimental methodology was developed that uses the average current from the PMT’s anode and a dual source method to characterize the detector system at specific very high count rate values. Delayed γ-ray spectra were acquired with the LaBr 3 detector system at the Idaho Accelerator Center, Idaho State University, where samples of ~3g of 235 U were irradiated with moderated neutrons from a photo-neutron source. Results of the spectroscopy characterization and analysis of the delayed γ-ray spectra acquired indicate the possible use of LaBr3 scintillation detectors when high count rate capability may outweigh the lower energy resolution.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Modified Energy Span Analysis of Catalytic Parallel Pathways and Selectivity

Mechanistic modeling provides vital insights into catalytic reactions. To analyze complex reaction networks with parallel pathways, we leverage the graph theory approach of the Energy Span Model (ESM) to develop a modified energy span analysis (MESA). A new method of cycle plots is proposed to perform reaction pathways analysis visually. We demonstrate this method on two published models: one describing carbon monoxide oxidation and the other simulating ethylene conversion to propanal via hydroformylation or ethane via hydrogenation. Fundamental insights explain kinetic observables, such as a reactant’s negative reaction order. General principles are revealed, such as rate-determining surface species being outside the primary reaction flux cycle and pathway selectivity being a purely kinetic property when reaction conditions are not near equilibrium. Lastly, we demonstrate MESA’s consistency with published microkinetic modeling results, highlighting this technique’s extension of the ESM to heterogeneous catalysts using collision theory to describe adsorption steps and concentration effects.

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

Atomic Layer Deposition of Cu Electrocatalysts on Gas Diffusion Electrodes for CO 2 Reduction

Electrochemical reduction of CO 2 using Cu catalysts enables the synthesis of C 2+ products including C 2 H 4 and C 2 H 5 OH. Here, in this study, Cu catalysts were fabricated using plasma-enhanced atomic layer deposition (PEALD), achieving conformal deposition of catalysts throughout 3-D gas diffusion electrode (GDE) substrates while maintaining tunable control of Cu nanoparticle size and areal loading. The electrochemical CO 2 reduction at the Cu surface yielded a total Faradaic efficiency (FE) > 75% for C 2+ products. Parasitic hydrogen evolution was minimized to a FE of ~10%, and a selectivity of 42.2% FE for C 2 H 4 was demonstrated. Compared to a line-of-sight physical vapor deposition method, PEALD Cu catalysts show significant suppression of C 1 products compared to C 2+ , which is associated with improved control of catalyst morphology and conformality within the porous GDE substrate. Finally, PEALD Cu catalysts demonstrated a stable performance for 15 h with minimal reduction in the C 2 H 4 production rate.

42 ENGINEERING↗
DOE OSTI2015

Identification and quantification analysis of nonlinear dynamics properties of combustion instability in a diesel engine

The cycling combustion instabilities in a diesel engine have been analyzed based on chaos theory. The objective was to investigate the dynamical characteristics of combustion in diesel engine. In this study, experiments were performed under the entire operating range of a diesel engine (the engine speed was changed from 600 to 1400 rpm and the engine load rate was from 0% to 100%), and acquired real-time series of in-cylinder combustion pressure using a piezoelectric transducer installed on the cylinder head. Several methods were applied to identify and quantitatively analyze the combustion process complexity in the diesel engine including delay-coordinate embedding, recurrence plot (RP), Recurrence Quantification Analysis, correlation dimension (CD), and the largest Lyapunov exponent (LLE) estimation. The results show that the combustion process exhibits some determinism. If LLE is positive, then the combustion system has a fractal dimension and CD is no more than 1.6 and within the diesel engine operating range. We have concluded that the combustion system of diesel engine is a low-dimensional chaotic system and the maximum values of CD and LLE occur at the lowest engine speed and load. This means that combustion system is more complex and sensitive to initial conditions and that poor combustion quality leads to the decrease of fuel economy and the increase of exhaust emissions.

42 ENGINEERING↗
DOE OSTI2020

Data-driven Cyberattack Detection for Photovoltaic (PV) Systems through Analyzing Micro-PMU Data

With increasing exposure to software-based sensing and control, Photovoltaic (PV) systems are facing higher risks of cyber attacks. Here, to ensure the system stability and minimize potential economic losses, it is imperative to monitor operating states and detect attacks at the early stage. To meet this demand, Micro-Phasor Measurement Units (μPMU) are increasingly popular in monitoring distribution networks. However, due to the relatively low sampling rate, μPMU has not yet been used to detect and classify cyber-attacks in power electronics enabled smart grid. To our knowledge, this is one of the first attempts to use μPMU to detect cyber attacks that degrade the performance of power electronics systems. We propose to apply data-driven methods on micro-PMU data to implement attack detection. We have evaluated data-driven methods, including decision tree (DT), K-nearest neighbor (KNN), support vector machine (SVM), artificial neural network (ANN), long short-term memory (LSTM) and convolutional neural network (CNN). The proposed CNN model achieves the required performances with the highest 99.23% accuracy and 0.9963 F 1 score.

14 SOLAR ENERGY↗
DOE OSTI2014

The Octavius1500 2D ion chamber array and its associated phantoms: Dosimetric characterization of a new prototype

Purpose: The purpose of the study is to characterize the prototype of the new Octavius1500 (PTW, Freiburg, Germany) 2D ion chamber array, covering its use in different phantom setups, from the most basic solid water sandwich setup to the more complex cylindrical Octavius{sup ®} 4D (Oct4D) (PTW) phantom/detector combination. The new detector houses nearly twice the amount of ion chambers as its predecessors (Seven29 and Octavius729), thereby tackling one of the most important limitations of ion chamber (or diode) arrays, namely the limited detector density. The 0.06 cm{sup 3} cubic ion chambers are now arranged in a checkerboard pattern, leaving no lines (neither longitudinally nor laterally) without detectors. Methods: All measurements were performed on a dual energy (6 MV and 18 MV) iX Clinac (Varian Medical Systems, Palo Alto, CA) and all calculations were done in the Eclipse treatment planning system (Varian) with the Anisotropic Analytical Algorithm. First, the basic characteristics of the 2D array, such as measurement stability, dose rate dependence and dose linearity were investigated in the solid water sandwich setup. Second, the directional dependence was assessed to allow the evaluation of the new Octavius2D phantom (Oct2D{sup 1500}) for planar verification measurements of composite plans. Third, measurements were performed in the Oct4D phantom to evaluate the impact of the increased detector density on the accuracy of the volumetric dose reconstruction. Results: While showing equally good dose linearity and dose rate independence, the Octavius1500 outperforms the previous models because of its instantaneous measurement stability and its twofold active area coverage. Orthogonal field-by-field measurements immediately benefit from the increased detector density. The 3.9 cm wide compensation cavity in the new Oct2D{sup 1500} phantom prototype adequately corrects for directional dependence from the rear, resulting in good agreement within the target dose. Discrepancies may arise towards the sides of the array because of uncompensated lateral beam incidence. The beneficial impact of the detector density is most prominent in the Oct4D system, for which the average pass rate (PR) is now nearly 100% (99.31 ± 0.37) when using gamma criteria of 2%G,2 mm (10% dose threshold). In search of gamma analysis criteria that are not too lenient to detect possibly relevant deviations, the authors conclude that for our radiotherapy environment, the authors choose to adopt 3%L,3 mm PR97% (threshold 10%) criteria for the Oct2D{sup 1500}/Octavius1500 system and 2%L,3 mm PR97% (threshold 10%) for the Oct4D/Octavius1500 system. These are first line pass/check criteria and plans that fail are not necessarily rejected, but submitted to a more detailed investigation. Conclusions: When irradiated from the front, the Octavius1500 array has two main advantages over its 729 predecessors: its instantaneous measurement stability and-–most importantly—its twofold detector density. In the Oct2D1500 phantom, these advantages are counterbalanced by the more pronounced directional dependence. The measurement-based 3D dose reconstruction in the Oct4D system, however, benefits considerably from the higher detector density in the checkerboard panel design.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2019

Challenges in Clinical Trial Implementation: Results from a Survey of the National Accreditation Program of Breast Centers (NAPBC)

Background: Although the results of clinical trials often guide best practices, changing clinical practice based on clinical trial results can be challenging. The objective of this study was to examine provider-reported barriers to adopting best clinical practices according to clinical trial data. Methods: A cross-sectional survey was conducted of providers from the National Accreditation Program for Breast Centers about barriers that prevent the incorporation of trial findings. Descriptive analyses and multivariable analyses were performed to determine provider characteristics that were significantly associated with reported barriers. Results: Overall, 383 institutions participated (63.5% response rate), with a total of 1226 physicians responding to the survey (80% response rate). Providers identified national guidelines and meetings as the most compelling way to receive practice-changing information. They reported the following internal barriers to trial implementation: patient preference (45%), strongly held beliefs by partners/colleagues (37%), and insufficient time to discuss new practices (30%). External barriers preventing trial implementation included a lack of agreement from multidisciplinary tumor boards (32%), fear of reimbursement loss (23%), and resistance from clinical staff (20%). Reported barriers differed by provider specialty, with plastic surgeons and radiation oncologists reporting that strongly held beliefs by partners/colleagues and disagreement from multidisciplinary tumor boards were the most significant factors preventing clinical trial implementation. Conclusions: Physician beliefs and patient preferences are the most frequently reported barriers to clinical trial implementation. Tactics to better educate providers about how to explain new clinical trial data to their patients and colleagues are needed.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2017

Magnetic Partitioning Nanofluid for Rare Earth Extraction from Geothermal Fluids

Rare earth metals are critical materials in a wide variety of applications in generating and storing renewable energy and in designing more energy efficient devices. Extracting rare earth metals from geothermal brines is a very challenging problem due to the low concentrations of these elements and engineering challenges with traditional chemical separations methods involving packed sorbent beds or membranes that would impede large volumetric flow rates of geothermal fluids transitioning through the plant. We are demonstrating a simple and highly cost-effective nanofluid-based method for extracting rare earth metals from geothermal brines. Core-shell composite nanoparticles are produced that contain a magnetic iron oxide core surrounded by a shell made of silica or metal-organic framework (MOF) sorbent functionalized with chelating ligands selective for the rare earth elements. By introducing the nanoparticles at low concentration (≈0.05 wt%) into the geothermal brine after it passes through the plant heat exchanger, the brine is exposed to a very high concentration of chelating sites on the nanoparticles without need to pass through a large and costly traditional packed bed or membrane system where pressure drop and parasitic pumping power losses are significant issues. Instead, after a short residence time flowing with the brine, the particles are effectively separated out with an electromagnet and standard extraction methods are then applied to strip the rare earth metals from the nanoparticles, which are then recycled back to the geothermal plant. Recovery efficiency for the rare earths at ppm level has now been measured for both silica and MOF sorbents functionalized with a variety of chelating ligands. A detailed preliminary techno-economic performance analysis of extraction systems using both sorbents showed potential to generate a promising internal rate of return (IRR) up to 20%.

58 GEOSCIENCES↗
DOE OSTI2024

Evaluation of In-Situ AM Process Monitoring Techniques and Potential for Detecting Process Anomalies and Undesirable Microstructures

The US Department of Energy’s Advanced Materials and Manufacturing Technologies (AMMT) program is pursuing rapid qualification of new materials for fabrication of nuclear relevant components using advanced manufacturing techniques. Particular interest is placed on code-qualifying stainless steel (SS) 316H processed by laser powder bed fusion (LPBF) additive manufacturing. A paradigm that incorporates data from in-situ sensing during the printing, ex-situ characterization, and advanced artificial intelligence–based models was established under the Transformation Challenge Reactor (TCR) program to develop a pedigree for each fabricated component that could be tracked from the feedstock to the component’s release for application. Under the TCR program, the Peregrine software was developed as a tool for incorporating the vast amounts of in-situ and ex-situ characterization data collected; all data stored on a rapidly growing digital platform. The digital platform allows for users to link site-specific process anomalies to the macro- and microstructure. The platform will eventually be able to predict component performance, which will be crucial to qualifying materials and components in risk-averse industries such as those supporting and building nuclear reactors. Current in-situ process monitoring techniques that are already integrated with software like Peregrine are advantageous for identifying process anomalies including powder spatter, component edge swelling, recoating-build interactions, and so on. However, additional data are required to fully predict the resulting microstructures needed for identifying relationships to component performance. The rapid cooling rates observed in LPBF are some of the highest of any bulk manufacturing process, resulting in heterogenous microstructures and typically causing anisotropy in mechanical properties. Moreover, evolved residual thermal stresses are high, which can cause severe defects such as delamination or cracking. Therefore, other in-situ monitoring methods are warranted for exploration to measure and map the thermal history, and potentially the stress state, of each build. This report summarizes different in-situ monitoring strategies proposed for LPBF with a focus on the more developed sensor systems. Novel capabilities for measuring melt pool temperatures are also addressed to better inform modeling efforts.

36 MATERIALS SCIENCE↗
DOE OSTI2021

PlasmidMaker: a Versatile, Automated, and High Throughput End-to-End Platform for Plasmid Construction

Plasmids are used extensively in basic and applied biology. However, design and construction of plasmids, specifically the ones carrying complex genetic information, remains one of the most time-consuming, labor-intensive, and rate-limiting steps in performing sophisticated biological experiments. Here, we report the development of a versatile, robust, automated end-to-end platform named PlasmidMaker that allows error-free construction of plasmids with virtually any sequences in a high-throughput manner. This platform consists of a most versatile DNA assembly method using Pyrococcus furiosus Argonaute ( Pf Ago)-based artificial restriction enzymes, a user-friendly frontend for plasmid design, and a backend that streamlines the workflow and integration with a robotic system. As a proof of concept, we used this platform to generate ~100 plasmids from six different species ranging from 5 to 18 kb in size from up to 11 DNA fragments within 3 days. PlasmidMaker should greatly expand the potential of synthetic biology.

Enghiad, Behnam↗
DOE OSTI2017

Experimental Evaluation of an Oxidizing Hazard in the Presence of Sorbents

Oxidizing chemicals are commonly found in waste generated from actinide separations and other chemical processes. Because they can create and/or increase the combustion of combustible materials, they need to be experimentally evaluated, in order to provide a highly reliable assessment of their potential hazards. Two sets of experiments were performed using a modified approach to the Environmental Protection Agency (EPA) SW-846 Method 1040. In the first set of experiments (scoping studies), the purpose was to determine the relative strength of some selected oxidizers. In the second set of experiments, the potential of the strongest tested oxidizer to increase the burning rate or burning intensity of some selected sorbents was investigated. The overall goal of this work was to conservatively identify oxidizer/sorbent mixtures producing non-oxidizer results. A few results from this experimental study are presented herein. More exhaustive information on this work can be found in supporting documentation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2012

Sexual Functioning Among Endometrial Cancer Patients Treated With Adjuvant High-Dose-Rate Intra-Vaginal Radiation Therapy

Purpose: We used the Female Sexual Function Index (FSFI) to investigate the prevalence of sexual dysfunction (SD) and factors associated with diminished sexual functioning in early stage endometrial cancer (EC) patients treated with simple hysterectomy and adjuvant brachytherapy. Methods and Materials: A cohort of 104 patients followed in a radiation oncology clinic completed questionnaires to quantify current levels of sexual functioning. The time interval between hysterectomy and questionnaire completion ranged from <6 months to >5 years. Multivariate regression was performed using the FSFI as a continuous variable (score range, 1.2-35.4). SD was defined as an FSFI score of <26, based on the published validation study. Results: SD was reported by 81% of respondents. The mean ({+-} standard deviation) domain scores in order of highest-to-lowest functioning were: satisfaction, 2.9 ({+-}2.0); orgasm, 2.5 ({+-}2.4); desire, 2.4 ({+-}1.3); arousal, 2.2 ({+-}2.0); dryness, 2.1 ({+-}2.1); and pain, 1.9 ({+-}2.3). Compared to the index population in which the FSFI cut-score was validated (healthy women ages 18-74), all scores were low. Compared to published scores of a postmenopausal population, scores were not statistically different. Multivariate analysis isolated factors associated with lower FSFI scores, including having laparotomy as opposed to minimally invasive surgery (effect size, -7.1 points; 95% CI, -11.2 to -3.1; P<.001), lack of vaginal lubricant use (effect size, -4.4 points; 95% CI, -8.7 to -0.2, P=.040), and short time interval (<6 months) from hysterectomy to questionnaire completion (effect size, -4.6 points; 95% CI, -9.3-0.2; P=.059). Conclusions: The rate of SD, as defined by an FSFI score <26, was prevalent. The postmenopausal status of EC patients alone is a known risk factor for SD. Additional factors associated with poor sexual functioning following treatment for EC included receipt of laparotomy and lack of vaginal lubricant use.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Identification of Leakage Spectra from Neutron Activation in Glass/Cherenkov Detectors - Paper 96

Oak Ridge National Laboratory has developed a new detector system concept that can be deployed in major US cities to identify the leakage spectrum of a nuclear weapon detonation. The detector is based on a small piece of glass that has been doped with an element that has a high activation cross section and creates a radioactive activation product with a reasonable length half-life. The decay of the activation product(s) after exposure creates Cherenkov light which can propagate to a photomultiplier and can be turned into a count-rate signal. The signal from each glass in each detector in a city can be individually analyzed to determine the amount of activation products produced in the initial exposure. Several activation products can be determined in a single glass if the half-lives are not the same. With a known source location and a detailed 3D model of a city, neutron transport simulations can be made by using a library of known sources to predict the activation amounts each source would have made in the glass detectors. A simple comparison of the measured activation amounts and the predicted activation amounts can identify the source spectrum contained in the library that is the best match. Choosing dopants with a large range in the threshold energy for the activation reactions can help to differentiate the spectra in the library. The method of matching the measured activation amounts to the predicted activation amounts to identify the source spectrum is similar to the analysis used for the passive Activation Foil Integrated Detector System (AFIDS), also developed at Oak Ridge National Laboratory. In AFIDS, wires or foils of known mass and isotopic composition are deployed before and then collected after exposure. Counting gammas in a nearby laboratory determines the activation amounts. The glass/Cherenkov system is active - it uses a battery-powered detector to count flashes of Cherenkov light and to communicate its count rates to a remote location for further analysis. Work has been performed in several areas, including glass making, automated detection and communication systems and software tools for analysis of the signal and source spectrum identification. Bell and Boatner have developed phosphate glasses that incorporate elements with high capture cross sections, and Hayward has simulated the response with Geant4 and measured the response with isotopic gamma sources. This paper will focus on the software tools for determining the activation amounts from the Cherenkov count-rate signal and finding the best matching source spectrum. A test problem in an urban environment is used to demonstrate the potential of a spectrum identification system using neutron activation. The analysis methods developed to identify the neutron leakage spectra from Cherenkov light given off by neutron activation in doped glasses work well. The calculation used to unfold the count-rate information into the number of actual activation products uses robust algorithms that can also compute associated uncertainties. These uncertainties and the known uncertainties of the glass tube material compositions are incorporated into the matching analysis to determine which of the source spectra in the library best matches the measured activation data. Any measurement method used to identify a neutron source spectrum relies at some point on a comparison against known sources; no identification method is definitive. Detection systems measure some physical aspect of the source, not its serial number. Many systems measure the physical aspect to determine that the source has some property, and then leave it to experts to determine which potential sources share that property. The analysis system presented here incorporates the comparison into the analysis itself. The statistical tests show which of the known library sources match the measured data the best and whether that match is a good match. If the best match still does not fit the measured data well (a very high χ{sup 2} value), that indicates the true source is not one of the sources in the library. This is still valuable information for decision makers. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Comparing EGF Methods for Estimating Corner Frequency and Stress Drop from P-wave Spectra

Empirical Green's functions (EGF) are widely applied to correct earthquake spectra for attenuation and other path effects in order to estimate corner frequencies and stress drops, but these source parameter estimates often exhibit poor agreement between different studies. We investigate this issue by analyzing a compact cluster of over 3000 aftershocks of the 1992 Landers earthquake. We apply and compare two different analysis and modeling methods: (1) the spectral decomposition and global EGF fitting approach, and (2) a more traditional EGF method of modeling spectral ratios. We find that spectral decomposition yields event terms that are consistent with stacks of spectral ratios for individual events, but source-parameter estimates nonetheless vary between the methods. The main source of differences comes from the modeling approach used to estimate the EGF. The global EGF-fitting approach suffers from parameter tradeoffs among the absolute stress drop, the stress-drop scaling with moment, and the high-frequency falloff rate, but has the advantage that the relative spectral shapes and stress drops among the different events in the cluster are well-resolved even if their absolute levels are not. The spectral-ratio approach solves for a different EGF for each target event without imposing any constraint on the corner frequency, f c , of the smaller events, and so can produce biased results for target-event f c . Placing constraints on the small-event f c improves the performance of the spectral-ratio method and allows the two methods to yield very similar results.

58 GEOSCIENCES↗
DOE OSTI2014

Preparation and characterization of magnetic CsH{sub 2}PW{sub 12}O{sub 40}/Fe–SiO{sub 2} nanocatalysts for biodiesel production

Graphical abstract: In this study, a series of magnetic CsH{sub 2}PW{sub 12}O{sub 40}/Fe–SiO{sub 2} nanocatalysts were prepared and tested for biodiesel production. The best operational conditions were CH3OH/oil = 12/1 at 60 °C with mechanical stirring, the biodiesel yield reaches to 81% in 4 h. Also notably, recovery of the catalyst can be achieved easily with the help of an external magnet with no need for expensive ultracentrifugation. - Highlights: • Effects of preparation conditions for biodiesel production were studied. • The CsH{sub 2}PW{sub 12}O{sub 40}/Fe–SiO{sub 2} catalyst is efficient catalyst for biodiesel production. • The reaction conditions were found methanol/oil = 12/1, T = 60 °C. - Abstract: The magnetic CsH{sub 2}PW{sub 12}O{sub 40}/Fe–SiO{sub 2} nanocatalysts were prepared via combination of sol–gel and impregnation methods. The effects of different H{sub 3}PW{sub 12}O{sub 40}/(Fe–SiO{sub 2}) weight percentage, loading of Cs as a promotor and calcination conditions on the catalytic performance has been studied. It was found that the catalyst with H{sub 3}PW{sub 12}O{sub 40}/Fe–SiO{sub 2} = 4 wt.% and Cs = 2 wt.% is an optimal catalyst for biodiesel production. The activity of optimal catalyst was studied in different operational conditions. The best operational conditions were CH{sub 3}OH/oil = 12/1 at 60 °C with mechanical stirring rate of 500 rpm and the biodiesel yield reaches to 81% in 4 h. Characterization of catalysts was carried out by using scanning electron microscopy (SEM), X-ray diffraction (XRD), Fourier transform-infrared spectroscopy (FT-IR), vibrating sample magnetometry (VSM), N{sub 2} adsorption–desorption measurements methods, Thermal gravimetric analysis (TGA) and differential scanning calorimetry (DSC)

36 MATERIALS SCIENCE↗
DOE OSTI2016

Machine- z : Rapid machine-learned redshift indicator for Swift gamma-ray bursts

Studies of high-redshift gamma-ray bursts (GRBs) provide important information about the early Universe such as the rates of stellar collapsars and mergers, the metallicity content, constraints on the re-ionization period, and probes of the Hubble expansion. Rapid selection of high-z candidates from GRB samples reported in real time by dedicated space missions such as Swift is the key to identifying the most distant bursts before the optical afterglow becomes too dim to warrant a good spectrum. Here, we introduce ‘machine-z’, a redshift prediction algorithm and a ‘high-z’ classifier for Swift GRBs based on machine learning. Our method relies exclusively on canonical data commonly available within the first few hours after the GRB trigger. Using a sample of 284 bursts with measured redshifts, we trained a randomized ensemble of decision trees (random forest) to perform both regression and classification. Cross-validated performance studies show that the correlation coefficient between machine-z predictions and the true redshift is nearly 0.6. At the same time, our high-z classifier can achieve 80 per cent recall of true high-redshift bursts, while incurring a false positive rate of 20 per cent. With 40 per cent false positive rate the classifier can achieve ~100 per cent recall. As a result, the most reliable selection of high-redshift GRBs is obtained by combining predictions from both the high-z classifier and the machine-z regressor.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Improving Detection of Disease Re-emergence Using a Web-Based Tool (RED Alert): Design and Case Analysis Study

Background: Currently, the identification of infectious disease re-emergence is performed without describing specific quantitative criteria that can be used to identify re-emergence events consistently. This practice may lead to ineffective mitigation. In addition, identification of factors contributing to local disease re-emergence and assessment of global disease re-emergence require access to data about disease incidence and a large number of factors at the local level for the entire world. This paper presents Re-emerging Disease Alert (RED Alert), a web-based tool designed to help public health officials detect and understand infectious disease re-emergence. Objective: Our objective is to bring together a variety of disease-related data and analytics needed to help public health analysts answer the following 3 primary questions for detecting and understanding disease re-emergence: Is there a potential disease re-emergence at the local (country) level? What are the potential contributing factors for this re-emergence? Is there a potential for global re-emergence? Methods: We collected and cleaned disease-related data (eg, case counts, vaccination rates, and indicators related to disease transmission) from several data sources including the World Health Organization (WHO), Pan American Health Organization (PAHO), World Bank, and Gideon. We combined these data with machine learning and visual analytics into a tool called RED Alert to detect re-emergence for the following 4 diseases: measles, cholera, dengue, and yellow fever. We evaluated the performance of the machine learning models for re-emergence detection and reviewed the output of the tool through a number of case studies. Results: Our supervised learning models were able to identify 82%-90% of the local re-emergence events, although with 18%-31% (except 46% for dengue) false positives. This is consistent with our goal of identifying all possible re-emergences while allowing some false positives. The review of the web-based tool through case studies showed that local re-emergence detection was possible and that the tool provided actionable information about potential factors contributing to the local disease re-emergence and trends in global disease re-emergence. Conclusions: To the best of our knowledge, this is the first tool that focuses specifically on disease re-emergence and addresses the important challenges mentioned above.

60 APPLIED LIFE SCIENCES↗