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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Planck 2013 results. I. Overview of products and scientific results

The European Space Agency's Planck satellite, dedicated to studying the early Universe and its subsequent evolution, was launched 14 May 2009 and has been scanning the microwave and submillimetre sky continuously since 12 August 2009. In March 2013, ESA and the Planck Collaboration released the initial cosmology products based on the first 15.5 months of Planck data, along with a set of scientific and technical papers and a web-based explanatory supplement. This report gives an overview of the mission and its performance, the processing, analysis, and characteristics of the data, the scientific results, and the science data products and papers in the release. The science products include maps of the cosmic microwave background (CMB) and diffuse extragalactic foregrounds, a catalogue of compact Galactic and extragalactic sources, and a list of sources detected through the Sunyaev-Zeldovich effect. The likelihood code given to assess cosmological models against the Planck data and a lensing likelihood are described. Scientific results include robust support for the standard six-parameter ΛCDM model of cosmology and improved measurements of its parameters, including a highly significant deviation from scale invariance of the primordial power spectrum. The Planck values for these parameters and others derived from them are significantly different from those previously determined. Several large-scale anomalies in the temperature distribution of the CMB, first detected by WMAP, are confirmed with higher confidence. Planck sets new limits on the number and mass of neutrinos, and has measured gravitational lensing of CMB anisotropies at greater than 25σ. Planck finds no evidence for non-Gaussianity in the CMB. Planck's results agree well with results from the measurements of baryon acoustic oscillations. Planck finds a lower Hubble constant than found in some more local measures. Some tension is also present between the amplitude of matter fluctuations (σ8) derived from CMB data and that derived from Sunyaev-Zeldovich data. The Planck and WMAP power spectra are offset from each other by an average level of about 2% around the first acoustic peak. Analysis of Planck polarization data is not yet mature, therefore polarization results are not released, while the robust detection of E -mode polarization around CMB hot and cold spots is shown graphically.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Recording the synchrotron radiation by a picosecond streak camera for bunch diagnostics in cyclic accelerators

A PS-1/S1 picosecond streak camera with a linear sweep is used to measure temporal characteristics of synchrotron radiation pulses on a damping ring (DR) at the Budker Institute of Nuclear Physics (BINP) of the Siberian Branch of the Russian Academy of Sciences (Novosibirsk). The data obtained allow a conclusion as to the formation processes of electron bunches and their 'quality' in the DR after injection from the linear accelerator. The expediency of employing the streak camera as a part of an optical diagnostic accelerator complex for adjusting the injection from a linear accelerator is shown. Discussed is the issue of designing a new-generation dissector with a time resolution up to a few picoseconds, which would allow implementation of a continuous bunch monitoring in the DR during mutual work with the electron-positron colliders at the BINP. (acoustooptics)

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Addressing Limitations of the Endpoint Slippage Analysis

Some rate of oxidation and reduction side-reactions will inevitably coexist in most rechargeable batteries. While parasitic reduction traps electrons, parasitic oxidation donates electrons to the cell’s inventory and may cause temporary capacity gain. Consequently, capacity measurements can provide unreliable information about the total extent of side-reactions occurring in the cell. The most widely used method to determine the rate of both these parasitic processes involves analyzing the slippage of endpoints, which consists in tracking the termination of cell charge and discharge when data is represented along a cumulative capacity axis. Here, we argue that this approach could lead to inaccuracies when applied to certain systems, which includes Si electrodes in Li-ion batteries and hard carbon in Na-ion batteries. This inaccuracy originates from the smooth nature of the voltage profiles of these materials at low and high alkali-ion content, causing the termination of charge and discharge to be dictated by voltage changes at both the positive and negative electrodes. We analyze this issue in quantitative terms and propose equations that can provide true rates of parasitic processes from experimental endpoint slippage data. This work shows that, in battery science, well-established analytical approaches may not be directly transferrable to new electrode systems.

25 ENERGY STORAGE↗
DOE OSTI2026

The DECam MAGIC Survey $-$ Mapping the Ancient Galaxy in CaHK: Overview and Summary of Early Science

We present the DECam Mapping the Ancient Galaxy in CaHK (MAGIC) survey, a 54-night NOIRLab Survey Program to image $\gtrsim$5,000$\,$deg$^2$ of the southern hemisphere using a metallicity-sensitive narrow-band filter covering the Ca$\,$ii$\,$H&K lines centered at 3955$\,$A. This filter is installed on the Dark Energy Camera (DECam), mounted on the 4-m NSF Víctor M. Blanco Telescope. The survey reaches typical $10σ$ depths of $\text{mag}_{\text{CaHK}} \approx 22.5$, 3$-$4$\,$mag deeper than comparable surveys in the southern hemisphere. By combining photometry from this Ca$\,$ii$\,$H&K filter with existing DECam $g,r,i$ broadband photometry from the DECam Local Volume Exploration (DELVE) survey, MAGIC is deriving photometric metallicities for red giant branch stars down to the magnitude limit of usable proper motions from Gaia data release 3 (DR3). MAGIC has already imaged $\sim$3,000$\,$deg$^2$, supplemented by other affiliated observing programs that have used this filter to image star clusters, dwarf galaxies, and stellar streams. We overview MAGIC's survey strategy, describe data processing through the derivation of metallicities and photometric distances, and summarize early science results that have been published with this dataset. In addition, we present several new results, including the confirmation of a distant ($>5\,r_h$) member of the Reticulum II ultra-faint dwarf galaxy, on-sky density maps of low-metallicity stars into the distant Milky Way halo ($\sim150\,$kpc) recovering 13/14 ultra-faint dwarf galaxies in the current footprint, and a validation of our initial targeting of extremely metal-poor stars. Collectively, these results demonstrate that the MAGIC dataset enables cutting-edge studies of the faint, low-metallicity regime of the Milky Way and its substructures.

Chiti, A. [KIPAC, Menlo Park] (ORCID:0000000271556↗
DOE OSTI2015

Consumption study and identification of methyl salicylate in spicy cassava chips

Spicy cassava chips is a popular snack. However, some news in electronic media reported addition of balsam which is a banned food additives in that product to give extra spicy flavor. This study aimed to determine ITB students’ pattern of consumption, health problems caused by spicy chips consumption, and knowledge about illicit use of food additives in that product, and identify the main content of balsam namely methyl salicylate in 10 samples of spicy cassava chips taken from inside and outside about ITB campus. A total of 300 questionnaires distributed to ITB students then data processing was performed. Spicy cassava chips sample macerated in 50 mL of methanol for 24 hours at room temperature, filtered and analyzed using gas chromatography capillary column with OV-1, nitrogen carrier gas and flame ionization detector. Based on questionnaires, 292 (97%) of 300 respondents had consumed spicy chips. A total of 247 (85%) from 292 respondents spicy chips consumed less than 3 times a week. A total of 195 respondents (67%) had experienced health problems after eating spicy chips. There were 137 (47%) of the 292 respondents who knew about the illicit addition of food additives into spicy chips; only 35 respondents (12%) who knew about balsam’s addition. There were 126 respondents (43%) who did not pay attention to their health because they will keep eating spicy chips despite the addition of banned food additives. Through the verification of the standard addition method in gas chromatography system with a hydrogen pressure of 1.5 bar, injector temperature 200 °C, detector temperature 230 °C, oven temperature 60 °C for 2 minutes and then increased to 230 °C with rate 6 °C/menit; linearity, limit of detection, limit of quantitation, accuracy, precision, and specificity parameters met the acceptance limits. From 10 spicy cassava chips samples which were analyzed, they did not reveal any content of methyl salicylate. Methyl salicylate contained in the positive control was 1.273 mg/mL.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Salk Institute for Biological Studies Requirements (Analysis Report)

EPOC uses the Deep Dive process to discuss and analyze current and planned science, research, or education activities and the anticipated data output of a particular use case, site, or project to help inform the strategic planning of a campus or regional networking environment. This includes understanding future needs related to network operations, network capacity upgrades, and other technological service investments. A Deep Dive comprehensively surveys major research stakeholders’ plans and processes in order to investigate data management requirements over the next 5–10 years. Between February and March 2024, staff members from the Engagement and Performance Operations Center (EPOC) met with researchers and staff from the Salk Institute for Biological Studies (Salk) for the purpose of a Deep Dive into scientific and research drivers. The goal of this activity was to help characterize the requirements for a number of campus use cases, and to enable cyberinfrastructure support staff better to understand the needs of the researchers within the community. Material for this event included the written documentation from each of the profiled research areas, documentation about the current state of technology support, and a write-up of the discussion that took place via e-mail and video conferencing. The case studies highlighted the ongoing challenges and opportunities that Salk Institute for Biological Studies have in supporting a cross-section of established and emerging research use cases. Each case study mentioned unique challenges which were summarized into common needs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

New York-Presbyterian and Columbia University Irving Medical Center Requirements (Analysis Report)

EPOC uses the Deep Dive process to discuss and analyze current and planned science, research, or education activities and the anticipated data output of a particular use case, site, or project to help inform the strategic planning of a campus or regional networking environment. This includes understanding future needs related to network operations, network capacity upgrades, and other technological service investments. A Deep Dive comprehensively surveys major research stakeholders’ plans and processes in order to investigate data management requirements over the next 5–10 years. Between February and June 2024, staff members from the Engagement and Performance Operations Center (EPOC) met with researchers and staff from New York-Presbyterian (NYP), Columbia University Irving Medical Center (CUIMC), and NYSERNet for the purpose of a Deep Dive into scientific and research drivers. The goal of this activity was to help characterize the requirements for a number of campus use cases, and to enable cyberinfrastructure support staff to better understand the needs of the researchers within the community. Material for this event included the written documentation from each of the profiled research areas, documentation about the current state of technology support, and a write-up of the discussion that took place via e-mail and video conferencing. The case studies highlighted the ongoing challenges and opportunities that NYP and CUIMC have in supporting a cross-section of established and emerging research use cases. Each case study mentioned unique challenges which were summarized into common needs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Chemical thermodynamic data. 1. The concept of links to the chemical elements and the historical development of key thermodynamic data [plus Supplementary Electronic Annex 2]

Chemical thermodynamic data remain a keystone for geochemical modeling and reactive transport simulation as applied to an increasing number of applications in the earth sciences, as well as applications in other areas including metallurgy, material science, and industrial process design. The last century has seen the development of a large body of thermodynamic data and a number of major compilations. The past several decades have seen the development of thermodynamic databases in digital form designed to support computer calculations. However, problems with thermodynamic data appear to be persistent. One problem pertains to the use of inconsistent primary key reference data. Such data pertain to elemental reference forms and key, stoichiometrically simple chemical species including metal oxides, CO 2 , water, and aqueous species such as Na + and Cl - . A consistent set of primary key data (standard Gibbs energies, standard enthalpies, and standard entropies for key chemical species) for 298.15K and 1 bar pressure is essential. Thermochemical convention is to define the standard Gibbs energy and the standard enthalpy of an individual chemical species in terms of formation from reference forms of the constituent chemical elements. We propose a formal concept of “links” to the elemental reference forms. This concept involves a documented understanding of all reactions and calculations leading to values for a formation property (standard Gibbs energy or enthalpy). A valid link consists of two parts: (a) the path of reactions and corrections and (b) the associated data, which are key data. Such a link differs from a bare “key” or “reference” datum in that it requires additional information. Some or all of its associated data may also be key data. In evaluating a reported thermodynamic datum, one should identify the links to the chemical elements, a process which can be time-consuming and which may lead to a dead end (an incomplete link). The use of two or more inconsistent links to the same elemental reference form in a thermodynamic database will result in an inconsistency in the database. Thus, in constructing a database, it is important to establish a set of reliable links (generally resulting in a set of primary reference data) and then correct all data adopted subsequently for consistency with that set. Recommended values of key data have not been constant through history. We review some of this history through the lens of major compilations and other influential reports, and note a number of problem areas. Finally, we illustrate the concepts developed in this paper by applying them to some key species of geochemical interest, including liquid water; quartz and aqueous silica; and gibbsite, corundum, and the aqueous aluminum ion.

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

Prediction of chronic kidney disease progression using recurrent neural network and electronic health records

Chronic kidney disease (CKD) is a progressive loss in kidney function. Early detection of patients who will progress to late-stage CKD is of paramount importance for patient care. To address this, we develop a pipeline to process longitudinal electronic heath records (EHRs) and construct recurrent neural network (RNN) models to predict CKD progression from stages II/III to stages IV/V. The RNN model generates predictions based on time-series records of patients, including repeated lab tests and other clinical variables. Our investigation reveals that using a single variable, the recorded estimated glomerular filtration rate (eGFR) over time, the RNN model achieves an average area under the receiver operating characteristic curve (AUROC) of 0.957 for predicting future CKD progression. When additional clinical variables, such as demographics, vital information, lab test results, and health behaviors, are incorporated, the average AUROC increases to 0.967. In both scenarios, the standard deviation of the AUROC across cross-validation trials is less than 0.01, indicating a stable and high prediction accuracy. Our analysis results demonstrate the proposed RNN model outperforms existing standard approaches, including static and dynamic Cox proportional hazards models, random forest, and LightGBM. The utilization of the RNN model and the time-series data of previous eGFR measurements underscores its potential as a straightforward and effective tool for assessing the clinical risk of CKD patients concerning their disease progression.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Hybrid PSO-ASVR-based method for data fitting in the calibration of infrared radiometer

The present paper describes a hybrid particle swarm optimization-adaptive support vector regression (PSO-ASVR)-based method for data fitting in the calibration of infrared radiometer. The proposed hybrid PSO-ASVR-based method is based on PSO in combination with Adaptive Processing and Support Vector Regression (SVR). The optimization technique involves setting parameters in the ASVR fitting procedure, which significantly improves the fitting accuracy. However, its use in the calibration of infrared radiometer has not yet been widely explored. Bearing this in mind, the PSO-ASVR-based method, which is based on the statistical learning theory, is successfully used here to get the relationship between the radiation of a standard source and the response of an infrared radiometer. Main advantages of this method are the flexible adjustment mechanism in data processing and the optimization mechanism in a kernel parameter setting of SVR. Numerical examples and applications to the calibration of infrared radiometer are performed to verify the performance of PSO-ASVR-based method compared to conventional data fitting methods.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Digital Autoradiography as a novel complementary technique for the investigation of radioactive contamination in nuclear facilities under dismantlement

The detection (location and quantification) of nuclear facilities to be dismantled possible contamination with low-range particles emitters ({sup 3}H, other low-energy β emitters, a emitters) remains a tedious and expensive task. Indeed, usual remote counters show a too low sensitivity to these non-penetrating radiations, while conventional wipe tests are irrelevant for fixed radioactivity evaluation. The only method to accurately measure activity levels consists in sampling and running advanced laboratory analyses (spectroscopy, liquid scintillation counting, pyrolysis...). Such measurements generally induce sample preparation, waste production (destructive analyses, solvents), nuclear material transportation, long durations, and significant labor mobilization. Therefore, the search for the limitation of their number and cost easily conflicts with the necessity to perform a dense screening for sampling (to maximize the representativeness of the samples), in installations of thousands of square meters (floors, wells, ceilings), plus furniture, pipes, and other wastes. To overcome this contradiction, Digital Autoradiography (D. A.) was re-routed from bio molecular research to radiological mapping of nuclear installations under dismantling and to waste and sample analysis. After in-situ exposure to the possibly-contaminated areas to investigate, commercial reusable radiosensitive phosphor screens (of a few 100 cm{sup 2}) were scanned in the proper laboratory device and sharp quantitative images of the radioactivity could be obtained. The implementation of geostatistical tools in the data processing software enabled the exhaustive characterization of concrete floors at a rate of 2 weeks / 100 m{sup 2}, at lowest costs. Various samples such as drilled cores, or tank and wood pieces, were also successfully evaluated with this method, for decisive results. Thanks to the accurate location of potential contamination spots, this approach ensures relevant and representative sampling for further laboratory analyses and should be inserted in the range of common tools used in dismantling. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

A novel proposal for all optical half-subtractor based on photonic crystals

Optical logic devices are the inevitable need for the future all optical computing and data processing. In this paper we are going to design and propose an all optical half subtractor using photonic crystal structure. The proposed structure will be realized using both threshold switching and beam interference. Finite difference time domain method used for analyzing the proposed structure. The simulation results show that the contrast ratio for D and B ports are 8 dB and 12 dB respectively. Also the maximum the maximum rise and fall times are 1 ps and 0.6 ps respectively.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Particle Markov Chain Monte Carlo Approach to Inference in Transient Surface Kinetics

Here, in this work, we develop a novel Bayesian approach to study the adsorption and desorption of CO onto a Pd(111) surface, a process of great importance in natural sciences. The motivation for this work comes from the recent availability of time-resolved infrared spectroscopy data and the need for model interpretability and uncertainty quantification in chemical processes. The objective is to learn the relevant parameters that characterize the process: coverage with time, rate constants, activation energies, and pre-exponential factors. Our approach consists of three main schemes: (i) a problem design and probabilistic model for the whole system, (ii) a particle Markov chain Monte Carlo sampler to learn the hidden coverages and rate constant parameters, and (iii) two Bayesian formulations to infer the activation energies and pre-exponential factors. The flexibility of the Bayesian framework allows for uncertainty quantification where possible and integration of mathematical constraints in the model to reflect the system physically. We found that our results for the activation energies and pre-exponential factor are in agreement with those reported in the experimental literature, independently, and we provide discussions on the advantages and disadvantages as well as applicability to other systems.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Data-scarce surrogate modeling of shock-induced pore collapse process

Understanding the mechanisms of shock-induced pore collapse is of great interest in various disciplines in sciences and engineering, including materials science, biological sciences, and geophysics. However, numerical modeling of the complex pore collapse processes can be costly. To this end, a strong need exists to develop surrogate models for generating economic predictions of pore collapse processes. Here, in this work, we study the use of a data-driven reduced-order model, namely dynamic mode decomposition, and a deep generative model, namely conditional generative adversarial networks, to resemble the numerical simulations of the pore collapse process at representative training shock pressures. Since the simulations are expensive, the training data are scarce, which makes training an accurate surrogate model challenging. To overcome the difficulties posed by the complex physics phenomena, we make several crucial treatments to the plain original form of the methods to increase the capability of approximating and predicting the dynamics. In particular, physics information is used as indicators or conditional inputs to guide the prediction. In realizing these methods, the training of each dynamic mode composition model takes only around 30 s on CPU. In contrast, training a generative adversarial network model takes 8 h on GPU. Moreover, using dynamic mode decomposition, the final-time relative error is around 0.3% in the reproductive cases. We also demonstrate the predictive power of the methods at unseen testing shock pressures, where the error ranges from 1.3 to 5% in the interpolatory cases and 8 to 9% in extrapolatory cases.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

ORNL Second Target Station Project: Biological & Environmental Science Workshop

Recent advances in neutron sources and instrumentation have opened up many new opportunities for the application of neutron scattering techniques in the biological and environmental sciences. Neutrons enable studies of the structure and dynamics of biological and environmental samples with a particular sensitivity to light elements, such as hydrogen, which is a key component of biological and environmental samples. Studies using neutrons are complementary to X-rays and have the unique advantage of being non-destructive and highly-penetrating. Oak Ridge National Laboratory’s upcoming Spallation Neutron Source (SNS) Second Target Station (STS) will provide high brightness cold neutron sources that significantly advance the scientific capabilities of neutron scattering instruments. The STS will advance our understanding of biological and environmental processes across spatial and temporal scales. The capabilities will enhance our ability to discover, design, and develop new materials essential for advanced sustainable technologies to address society’s most pressing needs. This report summarizes the discussions and recommendations from a joint workshop held by the STS Project and the Biological and Environmental Systems Science Directorate (BESSD) in June 2022. The purpose of the workshop was to explore science opportunities and capabilities related to biological and environmental systems that could be incorporated into both current and future STS instrument designs, as well as additional instruments at the SNS First Target Station (FTS) and High Flux Isotope Reactor (HFIR). With six breakout sessions, each with two invited plenary speakers from other institutions, the participants discussed a wide range of topics relevant to biological and environmental research. Based on the input from participants, a number of recommendations on instrumentation, sample environments, complementary multi-modal methods, data processing and analysis and sample deuteration are provided in the report. The participants also identified science opportunities that are emerging from the planned instrument capabilities at STS. Selected recommendations and science opportunities are listed in the Executive Summary.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

COMBIgor (A data assistant for combinatorial scientists in Igor Pro) [SWR-19-16]

Combinatorial materials science experiments involve synthesis and spatially-resolved characterization of thin film sample libraries. As a result, the modern combinatorial materials science laboratory produces large, diverse, and complex data sets, requiring automation of analysis and visualization techniques. COMBIgor is a software package aimed to assist a combinatorial material scientists with large volumes of experimental data. This package, written in Igor Pro, offers a systematic approach to the loading, processing, and visualizing combinatorial data sets. COMBIgor is designed to be expanded on a laboratory, group, or individual basis to adopt additional loading, processing and visualization capabilities. By utilizing COMBIgor software package the burden of data management in combinatorial materials science experiments can be significantly reduced.

Bauers, Sage↗
DOE OSTI2019

In Situ Visualization for Computational Science (Dagstuhl Seminar 18271)

In situ visualization, i.e., visualizing simulation data as it is generated, is an emerging processing paradigm in response to trends in the area of high-performance computing. This paradigm holds great promise in its ability to access increased spatio-temporal resolution and leverage extensive computational power. However, the paradigm is also widely viewed as limiting when it comes to exploration-oriented use cases and further will require visualization systems to become more and more complicated and constrained. Additionally, there are many open research topics with in situ visualization. The Dagstuhl seminar 18271 “In Situ Visualization for Computational Science” brought together researchers and practitioners from three communities (computational science, high-performance computing, and scientific visualization) to share interesting findings, to identify lines of open research, and to determine a medium-term research agenda that addresses the most pressing problems. This report summarizes the outcomes and findings of the seminar.

97 MATHEMATICS AND COMPUTING↗