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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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84 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Electroluminescence property of organic light emitting diode (OLED)

Transport properties of electrons and holes were investigated not only in a anthracene-containing poly(p-phenylene-ethynylene)- alt - poly(p-phenylene-vinylene) (PPE-PPV) polymer (AnE-PVstat) light emitting diodes (OLED) but also in an ITO/Ag/polymer/Ag electron and ITO/PEDOT:PSS/polymer/Au hole only devices. Mobility of injected carriers followed the Poole-Frenkel type conduction mechanism and distinguished in the frequency range due to the difference of transit times in admittance measurement. Beginning of light output took place at the turn-on voltage (or flat band voltage), 1.8 V, which was the difference of energy band gap of polymer and two barrier offsets between metals and polymer.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Optically readout write once read many memory with single active organic layer

An optically readable write once read many memory (WORM) in Ag/Poly[2-methoxy-5-(2-ethylhexyloxy)-1,4-phenylenevinylene] (MEH PPV)/ITO is demonstrated in this work. Utilising characteristics of the organic light emitting diode structure of Ag/MEH PPV/ITO and electrochemical metallization of Ag, a WORM with light emitting capability can be realised. The simple fabrication process and multifunction capability of the device can be useful for future wearable optoelectronics and photomemory applications, where fast and parallel readout can be achieved by photons.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

ASTROCHEMICAL CORRELATIONS IN MOLECULAR CLOUDS

We investigate the spectral correlations between different species used to observe molecular clouds. We use hydrodynamic simulations and a full chemical network to study the abundances of over 150 species in typical Milky Way molecular clouds. We perform synthetic observations in order to produce emission maps of a subset of these tracers. We study the effects of different lines of sight and spatial resolution on the emission distribution and perform a robust quantitative comparison of the species to each other. We use the Spectral Correlation Function (SCF), which quantifies the root mean squared difference between spectra separated by some length scale, to characterize the structure of the simulated cloud in position-position-velocity (PPV) space. We predict the observed SCF for a broad range of observational tracers, and thus identify homologous species. In particular, we show that the pairs C and CO, C{sup +} and CN, and NH{sub 3} and H{sub 2}CS have very similar SCFs. We measure the SCF slope variation as a function of beam size for all species and demonstrate that the beam size has a distinct effect on different species emission. However, for beams of up to 10'', placing the cloud at 1 kpc, the change is not large enough to move the SCF slopes into different regions of parameter space. The results from this study provide observational guidance for choosing the best tracer to probe various cloud length scales.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

A case study evaluating the portability of an executable computable phenotype algorithm across multiple institutions and electronic health record environments

Abstract Electronic health record (EHR) algorithms for defining patient cohorts are commonly shared as free-text descriptions that require human intervention both to interpret and implement. We developed the Phenotype Execution and Modeling Architecture (PhEMA, http://projectphema.org) to author and execute standardized computable phenotype algorithms. With PhEMA, we converted an algorithm for benign prostatic hyperplasia, developed for the electronic Medical Records and Genomics network (eMERGE), into a standards-based computable format. Eight sites (7 within eMERGE) received the computable algorithm, and 6 successfully executed it against local data warehouses and/or i2b2 instances. Blinded random chart review of cases selected by the computable algorithm shows PPV ≥90%, and 3 out of 5 sites had >90% overlap of selected cases when comparing the computable algorithm to their original eMERGE implementation. This case study demonstrates potential use of PhEMA computable representations to automate phenotyping across different EHR systems, but also highlights some ongoing challenges.

Pacheco, Jennifer A.↗
DOE OSTI2015

Origin of the positive spin- 1 2 photoluminescence-detected magnetic resonance in π-conjugated materials and devices

The spin-1/2 single-modulation (SM) and double-modulation (DM) photoluminescence (PL) detected magnetic resonance (PLDMR) in poly(2-methoxy-5-(2'-ethyl)–hexoxy-1,4- phenylene vinylene) (MEH-PPV) films and poly(3-hexylthiophene) (P3HT) films is described, analyzed, and discussed. In particular, the models based on spin-dependent recombination of charge pairs (SDR) and triplet-polaron quenching (TPQ) are evaluated. By analyzing the dependence of the resonance amplitude on the microwave chopping (modulation) frequency using rate equations, it is demonstrated that the TPQ model can well explain the observed resonance behavior, while SDR model cannot reproduce the results of the observed DM-PLDMR. As a result, the observed spin-1/2 PLDMR is assigned to TPQ rather than SDR, even though the latter may also be present.

36 MATERIALS SCIENCE↗
DOE OSTI2016

SU-C-207B-03: A Geometrical Constrained Chan-Vese Based Tumor Segmentation Scheme for PET

Purpose: Accurate segmentation of tumor in PET is challenging when part of tumor is connected with normal organs/tissues with no difference in intensity. Conventional segmentation methods, such as thresholding or region growing, cannot generate satisfactory results in this case. We proposed a geometrical constrained Chan-Vese based scheme to segment tumor in PET for this special case by considering the similarity between two adjacent slices. Methods: The proposed scheme performs segmentation in a slice-by-slice fashion where an accurate segmentation of one slice is used as the guidance for segmentation of rest slices. For a slice that the tumor is not directly connected to organs/tissues with similar intensity values, a conventional clustering-based segmentation method under user’s guidance is used to obtain an exact tumor contour. This is set as the initial contour and the Chan-Vese algorithm is applied for segmenting the tumor in the next adjacent slice by adding constraints of tumor size, position and shape information. This procedure is repeated until the last slice of PET containing tumor. The proposed geometrical constrained Chan-Vese based algorithm was implemented in Matlab and its performance was tested on several cervical cancer patients where cervix and bladder are connected with similar activity values. The positive predictive values (PPV) are calculated to characterize the segmentation accuracy of the proposed scheme. Results: Tumors were accurately segmented by the proposed method even when they are connected with bladder in the image with no difference in intensity. The average PPVs were 0.9571±0.0355 and 0.9894±0.0271 for 17 slices and 11 slices of PET from two patients, respectively. Conclusion: We have developed a new scheme to segment tumor in PET images for the special case that the tumor is quite similar to or connected to normal organs/tissues in the image. The proposed scheme can provide a reliable way for segmenting tumors.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

In-situ crystal structure determination of seifertite SiO 2 at 129 GPa: Studying a minor phase near Earth’s core–mantle boundary

Seifertite SiO₂ likely exists as a minor phase near the core–mantle boundary. By simulating the pressure and temperature conditions near the core–mantle boundary, seifertite was synthesized as a minor phase in a coarse-grained, polycrystalline sample coexisting with the (Mg,Fe)SiO₃ post-perovskite (pPv) phase at 129 GPa and 2500 K. Here we report the first in situ single-crystal structure determination and refinement of seifertite at high pressure and after a temperature quench from laser heating. We improved the data coverage of a minor phase from a diamond-anvil cell (DAC) by merging single-crystal data of seifertite from six selected grains that had different orientations. Observed systematic absences of reflections from the six individual grains allowed only one space group: Pbcn . The refined results of seifertite are in good agreement with the predictions from previous first-principles calculations at high pressure. This approach provides a method for structure determination of a minor phase in a mineral assemblage synthesized under P-T conditions representative of the deep Earth.

58 GEOSCIENCES↗
DOE OSTI2019

CTF 4.0 User's Manual

The deck version is specified using the PPV flag on Card 1.1. In general, you should always use the latest version of the CTF input deck in order to make sure your model is treated correctly in CTF. This feature was added to retain backwards compatibility for older input decks. When an input deck is created with the CTF pre-processor, the latest version will always be used. Table 1 provides the revision history of the CTF input deck. The first column gives the version number of the deck and the second columns gives a description of what changed since the previous version of the input deck. This document describes how to make a CTF input deck. A CTF input deck is organized into Card Groups and Cards. A Card Group is a collection of Cards. A Card is defined as a line of input. Each Card may contain multiple data. A Card is terminated by making a new line. This document has been organized so that each Card Group is discussed in its own dedicated chapter. Each card is discussed in its own dedicated section. Each data in the card is discussed in its own block. The block gives information about the data, including the number of the input, the title, a description of the meaning of the data, units, data type, and so on. An example block is shown below to discuss the meaning of each entry in the block.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Application of Gaussian Bayes classifier to differentiate chlorine-based chemical agents

The Portable Isotopic Neutron Spectroscopy (PINS) is a commercialized system developed by Idaho National Laboratory (INL) to examine chemical warfare agents (CWA) non-destructively, utilizing Prompt Gamma Neutron Activation Analysis (PGNAA) techniques. The PINS system takes advantage of a high-resolution gamma-ray spectrum from a mechanically-cooled high-purity germanium (HPGe) detector. One of the difficult technical challenges is to discriminate the chlorine-based chemical agents. Especially, CN, CNB, CNS and CG have similar chemical compositions to make it hard to discriminate them with a higher confidence. Current identification algorithms for PINS systems with 252-Cf sources have been improved and updated continuously as more field data became available, and new algorithms was studied to complement the current algorithms by adopting the Gaussian Bayes classifier. These new algorithms were intended to be applied to a subset of chlorine-based chemical agents, and their main goal is discriminate CN, CNB, CNS and CG with their ratios of the chlorine neutron inelastic 1763keV peak to the chlorine thermal neutron capture 1959keV peak, which is referred to as the “Cl i/c” or “clic” ratio in this study. The Cl i/c ratios were assumed to follow Gaussian distributions with the means and the standard deviations unique to their corresponding chemical agents. The prior probabilities of these four chemical agents were optimized with a collection of field data to achieve the best performance in terms of precision or positive predictive value (PPV). Finally, their posterior probabilities as functions of the Cl i/c ratio were implemented in the current version of PINS analysis software in order to be tested with more field data.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
NASA NTRS1993

ATMOS/ATLAS 1 measurements of sulfur hexafluoride (SF6) in the lower stratosphere and upper troposphere

Vertical profiles of sulfur hexafluoride (SF6) in the lower stratosphere and upper troposphere have been retrieved from 0.01/cm resolution infrared solar occultation spectra recorded by the Atmospheric Trace Molecule Spectroscopy (ATMOS) Fourier transform spectrometer during the ATLAS (Atmospheric Laboratory for Applications and Science) 1 shuttle mission of March 24 to April 2, 1992. Based on measurements of the unresolved absorption by the SF6 mu(sub 3) band Q branch at 947.9/cm, average SF6 volume mixing ratios and 1-sigma uncertainties of 3.20 +/- 0.54 parts per trillion by volume (pptv; 10(exp -12) ppv) at 200 mbar (approximately 11.8 km) declining to 2.86 +/- 0.29 pptv at 100 mbar (approximately 16.2 km) and 1.95 +/- 0.50 pptv at 30 mbar (approximately 23.9 km) have been retrieved. The profiles show no obvious dependence with latitude over the range of the measurements (eight occultations spanning 28 deg S to 54 deg S). Assuming an exponential growth model and applying a correction for the interhemispheric concentration difference, an average SF6 rate of increase of 8.7 +/- 2.2% per year, 2 sigma, between 12 and 18 km has been derived by fitting the present measurements, ATMOS measurements from the April-May 1985 Spacelab 3 mission, and balloon-borne IR measurements obtained in March 1981 and June 1988.

Rinsland, C. P.↗
DOE OSTI2022

Resilient Observer Design for Cyber-Physical Systems with Data-Driven Measurement Pruning

Resilient observer design for Cyber-Physical Systems (CPS) in the presence of adversarial false data injection attacks (FDIA) is an active area of research. The existing state-of-the-art algorithms tend to break down as more and more knowledge of the system is built into the attack model; also as the percentage of attacked nodes increases. From the view of optimization theory, the problem is often cast as a classical error correction problem for which a theoretical limit of has been established as the maximum percentage attacked nodes for which state recovery is guaranteed. Beyond this limit, the performance of -minimization based schemes, for instance, deteriorates rapidly. Similar performance degradation occurs for other types of resilient observers beyond certain percentages of attacked nodes. In order to increase the corresponding percentage of attacked nodes for which state recoveries can be guaranteed, researchers have begun to incorporate prior information into the underlying resilient observer design framework. For the most pragmatic cases, this prior information is often obtained through a data-driven machine learning process. Existing results have shown a strong positive correlation between the maximum attacked percentages that can be tolerated and the accuracy of the data-driven model. Motivated by these results, this chapter examines the case for pruning algorithms designed to improve the Positive Prediction Value (PPV) of the resulting prior information, given stochastic uncertainty characteristics of the underlying machine learning model. Theoretical quantification of the achievable improvement is given. Simulation results show that the pruning algorithm significantly increases the maximum correctable percentage of attacked nodes, even for machine learning model whose prediction power is comparable to the random flip of a coin.

Resilient Observer, Cyber-physical Systems, Data-D↗
DOE OSTI2018

Utah FORGE: Ground Motion Study Report

Paragon Geophysical contracted Urban Seismic Specialists to conduct A Ground Motion Study, on their Forge 3D project located near in Milford Utah .The test was conducted to measure the effects of the vibrator array on a pipeline owned by Kern River. Testing began November 22nd, and was completed on November 23rd. Demobilizing was completed on November 24, 2017

15 GEOTHERMAL ENERGY↗