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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Few-view cone-beam CT reconstruction with deformed prior image

Purpose: Prior images can be incorporated into the image reconstruction process to improve the quality of subsequent cone-beam CT (CBCT) images from sparse-view or low-dose projections. The purpose of this work is to develop a deformed prior image-based reconstruction (DPIR) strategy to mitigate the deformation between the prior image and the target image. Methods: The deformed prior image is obtained by a projection-based registration approach. Specifically, the deformation vector fields used to deform the prior image are estimated through iteratively matching the forward projection of the deformed prior image and the measured on-treatment projections. The deformed prior image is then used as the prior image in the standard prior image constrained compressed sensing (PICCS) algorithm. A simulation study on an XCAT phantom and a clinical study on a head-and-neck cancer patient were conducted to evaluate the performance of the proposed DPIR strategy. Results: The deformed prior image matches the geometry of the on-treatment CBCT more closely as compared to the original prior image. Consequently, the performance of the DPIR strategy from few-view projections is improved in comparison to the standard PICCS algorithm, based on both visual inspection and quantitative measures. In the XCAT phantom study using 20 projections, the average root mean squared error is reduced from 14% in PICCS to 10% in DPIR, and the average universal quality index increases from 0.88 in PICCS to 0.92 in DPIR. Conclusions: The present DPIR approach provides a practical solution to the mismatch problem between the prior image and target image, which improves the performance of the original PICCS algorithm for CBCT reconstruction from few-view or low-dose projections.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Characterizing Time Series Data Diversity for Wind Forecasting

Wind forecasting plays an important role in integrating variable and uncertain wind power into the power grid. Various forecasting models have been developed to improve the forecasting accuracy. However, it is challenging to accurately compare the true forecasting performances from different methods and forecasters due to the lack of diversity in forecasting test datasets. This paper proposes a time series characteristic analysis approach to visualize and quantify wind time series diversity. The developed method first calculates six time series characteristic indices from various perspectives. Then the principal component analysis is performed to reduce the data dimension while preserving the important information. The diversity of the time series dataset is visualized by the geometric distribution of the newly constructed principal component space. The volume of the 3-dimensional (3D) convex polytope (or the length of 1D number axis, or the area of the 2D convex polygon) is used to quantify the time series data diversity. The method is tested with five datasets with various degrees of diversity.

big data visualization↗
DOE OSTI2021

X-Ray Spectra and Multiwavelength Machine Learning Classification for Likely Counterparts to Fermi 3FGL Unassociated Sources

We conduct X-ray spectral fits on 184 likely counterparts to Fermi-LAT 3FGL unassociated sources. Characterization and classification of these sources allows for more complete population studies of the high-energy sky. Most of these X-ray spectra are well fit by an absorbed power-law model, as expected for a population dominated by blazars and pulsars. A small subset of seven X-ray sources have spectra unlike the power law expected from a blazar or pulsar and may be linked to coincident stars or background emission. We develop a multiwavelength machine learning classifier to categorize unassociated sources into pulsars and blazars using gamma-ray and X-ray observations. Training a random forest (RF) procedure with known pulsars and blazars, we achieve a cross-validated classification accuracy of 98.6%. Applying the RF routine to the unassociated sources returned 126 likely blazar candidates (defined as P {sub bzr} ≥ 90%) and five likely pulsar candidates (P {sub bzr} ≤ 10%). Our new X-ray spectral analysis does not drastically alter the RF classifications of these sources compared to previous works, but it builds a more robust classification scheme and highlights the importance of X-ray spectral fitting. Our procedure can be further expanded with UV, visual, or radio spectral parameters or by measuring flux variability.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Characterizing Time Series Data Diversity for Wind Forecasting: Preprint

Wind forecasting plays an important role in integrating variable and uncertain wind power into the power grid. Various forecasting models have been developed to improve the forecasting accuracy. However, it is challenging to accurately compare the true forecasting performances from different methods and forecasters due to the lack of diversity in forecasting test datasets. This paper proposes a time series characteristic analysis approach to visualize and quantify wind time series diversity. The developed method first calculates six time series characteristic indices from various perspectives. Then the principal component analysis is performed to reduce the data dimension while preserving the important information. The diversity of the time series dataset is visualized by the geometric distribution of the newly constructed principal component space. The volume of the 3-dimensional (3D) convex polytope (or the length of 1D number axis, or the area of the 2D convex polygon) is used to quantify the time series data diversity. The method is tested with five datasets with various degrees of diversity.

17 WIND ENERGY↗
DOE OSTI2023

Interpretation of Fracture Initiation Points by In-Well Low-Frequency Distributed Acoustic Sensing in Horizontal Wells

Summary Low-frequency distributed acoustic sensing (LF-DAS) exploits the optical phase shift of Rayleigh backscatter in fiber-optic cables to obtain distributed measurements of changes in strain and temperature. Fiber-optic cables are often installed for multistage hydraulic fracture diagnostics in horizontal wells. LF-DAS in an untreated well provides far-field strain measurements, while offset wells are hydraulically fractured. Such a configuration is called crosswell LF-DAS sensing. Crosswell LF-DAS measurements have proved useful in diagnosing fracture hits, fracture azimuth, planarity, cluster efficiency, fracture propagation rates, and the dynamic distance to the fracture front. In contrast, in-well LF-DAS is conducted on the actively fractured well. Due to cool fracture fluid being injected at high injection rates, the strain component of the LF-DAS response is largely obscured by temperature changes. In permanent fiber-optic cable installations, distributed temperature sensing (DTS) is often conducted simultaneously with LF-DAS. An opportunity exists to decouple the temperature and strain components of LF-DAS sensors to observe strain changes on in-well LF-DAS. The LF-DAS response is modeled as linearly dependent on strain and temperature changes. Theoretical LF-DAS temperature and strain sensitivity coefficients are derived based on the changes to the index of refraction and length of the fiber. Using the DTS measurements, temperature changes are computed, smoothed, filtered, and compared to the LF-DAS response. Crossplots of the in-well LF-DAS measurements and temperature changes from DTS measurements far from the actively fractured region are used to validate the theoretical sensitivity coefficients. Uncertainty in the temperature component of the LF-DAS response is quantified. The difficulty in corresponding the different spatial and temporal resolutions of the DTS and LF-DAS measurements is overcome by comparing the responses over a moving temporal and spatial window. If the LF-DAS response at the center of the window agrees with the DTS response within uncertainty, the measurement is filtered out. After filtering, the remaining nonzero in-well LF-DAS measurements are due to changes in strain. The data are then visualized in waterfall plots. The results indicate that the theoretical and observed strain and temperature coefficients agree within 10%. After the temperature component of the in-well LF-DAS response is extracted, the remaining nonzero measurements are located primarily within the actively treated region. Locations with peaks in the strain response are interpreted to indicate fracture initiation points. These fracture initiation points are compared with in-well DTS and high-frequency DAS noise measurements across multiple stages to better understand fracture initiation along the horizontal well.

Engineering↗
DOE OSTI2018

A generative graph model for electrical infrastructure networks

We propose a generative graph model for electrical infrastructure networks that accounts for heterogeneity in both node and edge type. To inform the design of this model, we analyze the properties of power grid graphs derived from the U.S. Eastern Interconnection, Texas Interconnection, and Poland transmission system power grids. Across these datasets, we find subgraphs induced by nodes of the same voltage level exhibit shared structural properties atypical to small-world networks, including low local clustering, large diameter and large average distance. On the other hand, we find subgraphs induced by transformer edges linking nodes of different voltage types contain a more limited structure, consisting mainly of small, disjoint star graphs. The goal of our proposed model is to match both these inter and intra-network properties by proceeding in two phases: we first generate subgraphs for each voltage level and then generate transformer edges that connect these subgraphs. The first phase of the model adapts the Chung-Lu random graph model, taking desired vertex degrees and desired diameter as inputs, while the second phase of the model is based on a simpler random star graph generation process. We test the performance of our model by comparing its output across many runs to the aforementioned real data. In nearly all categories tested, we find our model is more accurate in reproducing the unusual mixture of properties apparent in the data than the Chung-Lu model. We also include graph visualization comparisons, as well as a brief analysis of edge-deletion resiliency. Ultimately, our model may be used to generate synthetic graph data, test hypotheses and algorithms at different scales, and serve as a baseline model on top of which further electrical network properties, device models, and interdependencies to other networks, may be appended.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2015

Impact of Pretreatment Combined {sup 18}F-Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography Staging on Radiation Therapy Treatment Decisions in Locally Advanced Breast Cancer

Purpose: To assess the diagnostic performance of pretreatment {sup 18}F-fluorodeoxyglucose positron emission tomography/computed tomography ({sup 18}F-FDG PET/CT) and its impact on radiation therapy treatment decisions in patients with locally advanced breast cancer (LABC). Methods and Materials: Patients with LABC with Eastern Cooperative Oncology Group performance status <2 and no contraindication to neoadjuvant chemotherapy, surgery, and adjuvant radiation therapy were enrolled on a prospective trial. All patients had pretreatment conventional imaging (CI) performed, including bilateral breast mammography and ultrasound, bone scan, and CT chest, abdomen, and pelvis scans performed. Informed consent was obtained before enrolment. Pretreatment whole-body {sup 18}F-FDG PET/CT scans were performed on all patients, and results were compared with CI findings. Results: A total of 154 patients with LABC with no clinical or radiologic evidence of distant metastases on CI were enrolled. Median age was 49 years (range, 26-70 years). Imaging with PET/CT detected distant metastatic disease and/or locoregional disease not visualized on CI in 32 patients (20.8%). Distant metastatic disease was detected in 17 patients (11.0%): 6 had bony metastases, 5 had intrathoracic metastases (pulmonary/mediastinal), 2 had distant nodal metastases, 2 had liver metastases, 1 had pulmonary and bony metastases, and 1 had mediastinal and distant nodal metastases. Of the remaining 139 patients, nodal disease outside conventional radiation therapy fields was detected on PET/CT in 15 patients (10.8%), with involvement of ipsilateral internal mammary nodes in 13 and ipsilateral level 5 cervical nodes in 2. Conclusions: Imaging with PET/CT provides superior diagnostic and staging information in patients with LABC compared with CI, which has significant therapeutic implications with respect to radiation therapy management. Imaging with PET/CT should be considered in all patients undergoing primary staging for LABC.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2017

H-Mediated Magnetic Interactions between Layers in a 2D Mn II -Dicyanamide Polymer: Neutron Diffraction, DFT, and Quantum Monte Carlo Calculations: H-Mediated Magnetic Interactions between Layers in a 2D Mn II -Dicyanamide Polymer: Neutron Diffraction, DFT, and Quantum Monte Carlo Calculations

We report neutron-diffraction investigations of the quasi-2D Mn-II(dca)(2)(pym)(H2O) (pym = N2C4H4) compound, where high-spin Mn-II ions are bridged by dicyanamide anions, [N(CN)(2)](-) (herein abbreviated dca). Inside the layers, Mn2+ ions are connected by single or double dca bridges. The magnetic phase diagram was established by neutron diffraction on a single crystal. In the low-field phase, the Mn-II ions are antiferro-magnetically ordered in the layers, with moments nearly parallel to the c axis, and the layers are antiferromagnetically coupled. The spin-flop phase corresponds to ferromagnetic coupling between the antiferromagnetic layers, in which the Mn-II moments are nearly perpendicular to the c axis. The induced spin-density distribution in the paramagnetic phase, determined by polarized neutron diffraction, visualizes the super-exchange pathways through the dca ligands within the layers and through H bonding between neighboring layers. The theoretical spin density obtained by bidimensional periodic DFT calculations is compared with the experimental results. Furthermore, quantum Monte Carlo simulations have been performed to compare the DFT results with experimental susceptibility measurements.

density functional calculations↗
DOE OSTI2018

Dual-Energy CT Pulmonary Angiography: Quantification of Disease Burden and Impact on Management

Purpose of Review: Computed tomography pulmonary angiography (CTPA) has become the imaging modality of choice for patients with suspected pulmonary embolism (PE). Post-processing techniques currently available for dual-energy CT pulmonary angiography (DE-CTPA) enhance image quality and provide additional value in the diagnosis of PE. The objective of this article is to summarize these recent developments and discuss the appropriate use of DE-CTPA post-processing applications. Recent Findings: DE-CTPA post-processing applications enable reconstruction of virtual monoenergetic images (VMI) and color-coded iodine-perfusion maps to increase contrast conditions and visualize lung perfusion defects in case of embolic occlusion of pulmonary arteries. Both techniques revealed a superior diagnostic performance for the detection of pulmonary emboli and assessment of the pulmonary perfusion compared to the standard image reconstructions. Summary: DE-CTPA is a well-established method for excluding or diagnosing PE. Continued developments in DE-CTPA post-processing techniques improve patient management and allow for a quantification of disease burden.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2023

Investigation of Nanoparticle Degradation in Hydrogen Fuel Cell Systems through Automated Electron Microscopy

Proton exchange membrane fuel cells (PEMFC) are promising devices for the deployment of hydrogen-powered heavy-duty vehicles, providing a higher efficiency for similar driving range and fueling time than the existing ones. However, PEMFCs still encounter durability challenges mainly due to catalyst degradation in the cathode. Mitigating these performance losses requires a better understanding of the degradation mechanisms under heavy-duty accelerated stress tests (ASTs) [1]. Scanning transmission electron microscopy (STEM) combined with energy dispersive X-ray spectroscopy (EDS) are key tools for the analysis of Pt and PtCo nanoparticle size, spatial distribution and composition [2]. Electron tomography is also used to determine the rate and type of degradation of catalyst nanoparticles as a function of their position on the carbon support. In this work, automated data acquisition software, paired with a custom Python code, have been used to study the effect of different accelerated stress tests (ASTs) on nanoparticle coarsening [2]. Figure 1 shows high-angle annular dark-field (HAADF)-STEM images and EDS maps comparing the cathodes of membrane electrode assemblies (MEAs) following an electrocatalyst AST performed under H2/N2 with that of the heavy-duty AST performed under H2/air. We will discuss how AST conditions affect considerably the spatial distribution of the nanoparticles across the electrode between the membrane and microporous layer. Although the median particle size increased more in the MEA aged under the heavy-duty AST, as determined using a high-throughput image analysis, the quantitative EDS measurements demonstrate that the electrocatalyst AST resulted in more Pt and Co dissolution from the cathode, which is another important indicator of electrocatalyst degradation. We will further present the impact of the relative humidity (% RH) on the degradation mechanisms demonstrated using the same approach. Electron tomography has been used to distinguish the Pt nanoparticles residing on the carbon support surface (exterior) from those within the pore structure (interior) in order to determine the relative stability of interior and exterior nanoparticles. As shown in Figure 2, we will compare the Pt catalyst particle size at the beginning of test (BOT) and end of test (EOT), and discuss the importance of automating the electron tomography workflow, i.e. acquisition, reconstruction, and visualization, to increase sampling and determine the standard deviation of these measurement. The outlook for utilizing low-dose cryo-tomography for limiting damage to the catalyst, support, and especially proton-conducting ionomer will also be discussed [3].

Amichi, Lynda↗
DOE OSTI2020

Supercooled liquid sulfur maintained in three-dimensional current collector for high-performance Li-S batteries

In lithium-sulfur (Li-S) chemistry, the electrically/ionically insulating nature of sulfur and Li 2 S leads to sluggish electron/ion transfer kinetics for sulfur species conversion. Sulfur and Li 2 S are recognized as solid at room temperature, and solid-liquid phase transitions are the limiting steps in Li-S batteries. Here, we visualize the distinct sulfur growth behaviors on Al, carbon, Ni current collectors and demonstrate that (i) liquid sulfur generated on Ni provides higher reversible capacity, faster kinetics, and better cycling life compared to solid sulfur; and (ii) Ni facilitates the phase transition (e.g., Li 2 S decomposition). Accordingly, light-weight, 3D Ni-based current collector is designed to control the deposition and catalytic conversion of sulfur species toward high-performance Li-S batteries. This work provides insights on the critical role of the current collector in determining the physical state of sulfur and elucidates the correlation between sulfur state and battery performance, which will advance electrode designs in high-energy Li-S batteries.

25 ENERGY STORAGE↗
DOE OSTI2014

Estimating contact rates at a mass gathering by using video analysis: a proof-of-concept project

Current approaches for estimating social mixing patterns and infectious disease transmission at mass gatherings have been limited by various constraints, including low participation rates for volunteer-based research projects and challenges in quantifying spatially and temporally accurate person-to-person interactions. We developed a proof-of-concept project to assess the use of automated video analysis for estimating contact rates of attendees of the GameFest 2013 event at Rensselaer Polytechnic Institute (RPI) in Troy, New York. Video tracking and analysis algorithms were used to estimate the number and duration of contacts for 5 attendees during a 3-minute clip from the RPI video. Attendees were considered to have a contact event if the distance between them and another person was ≤1 meter. Contact duration was estimated in seconds. We also simulated 50 attendees assuming random mixing using a geospatially accurate representation of the same GameFest location. The 5 attendees had an overall median of 2 contact events during the 3-minute video clip (range: 0 6). Contact events varied from less than 5 seconds to the full duration of the 3- minute clip. The random mixing simulation was visualized and presented as a contrasting example. We were able to estimate the number and duration of contacts for five GameFest attendees from a 3-minute video clip that can be compared to a random mixing simulation model at the same location. In conclusion, the next phase will involve scaling the system for simultaneous analysis of mixing patterns from hours-long videos and comparing our results with other approaches for collecting contact data from mass gathering attendees.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Extrapolation Domains for Aggregating Environmental Outcomes from Local to Regional Levels

Billions of dollars are invested every year to run field experiments to quantify the response of crops to new technologies and associated environmental outcomes. Given the diversity of environments where crop production occurs, conducting these research studies without a robust framework for research site selection and upscaling results to larger spatial scales is inefficient. In this project, researchers from the University of Nebraska-Lincoln used their unique Technology Extrapolation Domains framework (TED) as a tool to guide the selection of experimental sites and as basis for aggregating and validating environmental outcomes from local to regional levels. In the present project, we first used the TED framework to evaluate the current distribution and area coverage of the current SMARTFARM sites. The purpose was to showcase how it is possible to use the TED framework to guide site selection and extrapolate results over space. Additionally, the original TED framework was expanded to account for other factors influencing environmental outcomes by inclusion of three additional variables: soil organic matter, soil texture, and topographic wetness index. The resulting expanded framework (TED-E) was validated using nitrogen (N) losses from corn in the United States as a case study. To do so, we used N balance as a proxy to N losses and we evaluated the capacity of the framework to explain variation in N balance across fields and across countries. We found that the TED-E has substantially higher predictive power than the original TED framework to explain spatial variation in N balance. However, improvements in predictive power with the TED-E tool come at the expense of a higher number of TEDs needed to achieve a given crop area coverage compared with the original TED framework. We conclude that the new TED-E framework can help aggregate and extrapolate environmental outcomes from research sites to regional levels and improve the visualization of their spatial patterns across the United States. An online version of the framework is available at: https://www.toolted.org/

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Lightfall v0.0.1

Lightfall is a desktop application for synchrotron beamline instrument control, data acquisition, and live analysis at the Advanced Light Source (ALS). Built on Python and Qt, it provides a native graphical interface for operating beamline hardware, configuring and executing experimental scans, and visualizing results in real time. Key features include direct integration with EPICS control systems, a built-in electronic logbook, remote beamline access over secure tunnels, and an interprocess communication (IPC) architecture that coordinates with external analysis applications via ZMQ and EPICS process variables. This IPC approach allows Lightfall to orchestrate specialized analysis tools—including GPU-accelerated streaming correlators—without embedding them, avoiding the dependency conflicts common in monolithic scientific software platforms. Compared to prior approaches such as Xi-CAM's plugin-based architecture, Lightfall's design cleanly separates instrument control from domain-specific analysis, enabling feedback-driven acquisition where live analysis results can adjust scan parameters during an experiment. Its native Qt interface provides responsive performance for real-time data visualization that web-based alternatives struggle to match. Lightfall is designed for use by beamline scientists and staff operating synchrotron instruments at national user facilities.

Pandolfi, Ronald [Lawrence Berkeley National Labor↗
DOE OSTI2014

SU-E-T-13: A Feasibility Study of the Use of Hybrid Computational Phantoms for Improved Historical Dose Reconstruction in the Study of Late Radiation Effects for Hodgkin's Lymphoma

Purpose: Radiation-induced cancer effects are well-documented following radiotherapy. Further investigation is needed to more accurately determine a dose-response relationship for late radiation effects. Recent dosimetry studies tend to use representative patients (Taylor 2009) or anthropomorphic phantoms (Wirth 2008) for estimating organ mean doses. In this study, we compare hybrid computational phantoms to patient-specific voxel phantoms to test the accuracy of University of Florida Hybrid Phantom Library (UFHP Library) for historical dose reconstructions. Methods: A cohort of 10 patients with CT images was used to reproduce the data that was collected historically for Hodgkin's lymphoma patients (i.e. caliper measurements and photographs). Four types of phantoms were generated to show a range of refinement from reference hybrid-computational phantom to patient-specific phantoms. Each patient is matched to a reference phantom from the UFHP Library based on height and weight. The reference phantom is refined in the anterior/posterior direction to create a ‘caliper-scaled phantom’. A photograph is simulated using a surface rendering from segmented CT images. Further refinement in the lateral direction is performed using ratios from a simulated-photograph to create a ‘photograph and caliper-scaled phantom’; breast size and position is visually adjusted. Patient-specific hybrid phantoms, with matched organ volumes, are generated and show the capabilities of the UF Hybrid Phantom Library. Reference, caliper-scaled, photograph and caliper-scaled, and patient-specific hybrid phantoms are compared with patient-specific voxel phantoms to determine the accuracy of the study. Results: Progression from reference phantom to patient specific hybrid shows good agreement with the patient specific voxel phantoms. Each stage of refinement shows an overall trend of improvement in dose accuracy within the study, which suggests that computational phantoms can show improved accuracy in historical dose estimates. Conclusion: Computational hybrid phantoms show promise for improved accuracy within retrospective studies when CTs and other x-ray images are not available.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

A butterfly diagram and carrington maps for century-long Ca II K spectroheliograms from the Kodaikanal observatory

The century-long (1907–2007) Ca ii K spectroheliograms from the Kodaikanal Solar Observatory (KSO) are calibrated, processed, and analyzed to follow the evolution of the bright on-disc structures called plages, possible representatives of magnetic activity on the Sun. This is the longest data set studied in Ca ii K to date, covering about 9.5 cycles of 11 yr periods. Plages are segmented with area ⩾1 arcmin{sup 2} using global thresholds for individual full disc images and subsequent application of a morphological closing operation. The plage index is calculated and is seen to have a close positive correlation with the fractional disc area covered by plages. The newly generated plage area cycle (from KSO) was compared with the same from the Mount Wilson Observatory (correlation 95.6%) for the overlapping years, i.e., 1915–2000. This study illustrates the time–latitude distribution of plage centroids by rendering a butterfly diagram (as observed for sunspots). The 3D visualization of the diagram shows one-to-one mapping between plage location, time, and area. This work further delineates the positional correlation between magnetic patches and plage regions through the comparison of synoptic maps derived from both KSO Ca ii K images and space-based full disc line-of-sight magnetograms. Regular synoptic magnetograms from ground-based observatories are available only after 1970s. Thus the long term Ca ii K data from KSO can be used as a proxy for estimating magnetic activity locations and their strengths at earlier times.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

High-Pressure Apparatus for Monitoring Solid–Liquid Phase Transitions

This work presents a new technique for observing the solid–liquid phase transformations in complex diesel fuel blends and diesel surrogates under high-pressure conditions intended to simulate those occurring in vehicle fuel injectors. A high-pressure apparatus based on a visual identification of freezing and thawing has been designed and built to monitor phase behavior and determine the crystallization temperature of complex fuels to predict wax precipitation. The proposed methodology was validated using pure substances—n-hexadecane (C16H34), cyclohexane (C6H12), and a binary cyclohexane/n-hexadecane mixture—all of which have been well-characterized previously. The crystallization temperatures of these compounds were measured from atmospheric pressure to 400 MPa for temperatures varying from 290 to 363 K and compared to those reported in the literature. The standard error of the estimated temperatures, based on a given pressure, between the experimental data obtained in this work was compared to data in the literature from Domanska et al. This methodology is being extended to investigate the properties of more complex fuel mixtures.

High-Pressure, phase change, diesel, solidificatio↗
DOE OSTI2017

Comparing Submillimeter Polarized Emission with Near-infrared Polarization of Background Stars for the Vela C Molecular Cloud

We present a large-scale combination of near-infrared (near-IR) interstellar polarization data from background starlight with polarized emission data at submillimeter wavelengths for the Vela C molecular cloud. The near-IR data consist of more than 6700 detections probing a range of visual extinctions between 2 and 20 mag in and around the cloud. The submillimeter data were collected in Antarctica by the Balloon-borne Large Aperture Submillimeter Telescope for Polarimetry. This is the first direct combination of near-IR and submillimeter polarization data for a molecular cloud aimed at measuring the “polarization efficiency ratio” (R{sub eff}), a quantity that is expected to depend only on grain-intrinsic physical properties. It is defined as p{sub 500}/(p{sub I}/τ{sub V}), where p {sub 500} and p {sub I} are polarization fractions at 500 μm and the I band, respectively, and τ{sub V} is the optical depth. To ensure that the same column density of material is producing both polarization from emission and from extinction, we conducted a careful selection of near-background stars using 2MASS, Herschel, and Planck data. This selection excludes objects contaminated by the Galactic diffuse background material as well as objects located in the foreground. Accounting for statistical and systematic uncertainties, we estimate an average R{sub eff} value of 2.4 ± 0.8, which can be used to test the predictions of dust grain models designed for molecular clouds when such predictions become available. The ratio R{sub eff} appears to be relatively flat as a function of the cloud depth for the range of visual extinctions probed.

79 ASTRONOMY AND ASTROPHYSICS↗