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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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32 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Striking luminescence phenomena of carbon dots and their applications as a double ratiometric fluorescence probes for H2S detection

Here, we report some new observations on the luminescence of carbon dots (CDs) that are passivated with polyethylene glycol, and explored them, for the first time, as highly sensitive H2S detection probe. The as-prepared CDs have an ultraviolet (UV) emission at 350 nm and a green emission at 540 nm when excited at 270 nm, but they have only a green emission at 523 nm when excited at 365 nm. As Na2S is added to the CDs, the UV emission decreases gradually, while the green emission increases slightly, and interestingly a new emission appears at 455 nm is increased linearly in intensity with the increase of Na2S concentration. The blue emission at 455 nm is from the intrinsic core of CDs, and the green emissions at 540 or 523 nm are from their surface states, while the UV emission at 350 nm is from the anchored PEG. Both the emission intensity ratios of F-450/F-350 and F-455/F-523 show an excellent linear relationship with the Na2S concentration in the range of 0-800 mu M, and the detection limit estimated from both of them is approximately 7.0 nM, indicating our method is the most sensitive H2S CDs based detection method reported thus far. Furthermore, the detection was tested successfully for H2S imaging in live cells. We propose that the interactions of H2S with the CDs and the anchored ligands, as well as the energy transfer between the ligands and the CDs, are responsible for the luminescence responses for H2S detection. Our studies enrich the world of carbon dots with plenty of potential applications. (C) 2020 Elsevier Ltd. All rights reserved.

Bioimaging↗
DOE OSTI2021

Automated theoretical chemical kinetics: Predicting the kinetics for the initial stages of pyrolysis

Large scale implementation of high level computational theoretical chemical kinetics offers the prospect for dramatically improving the fidelity of combustion chemical modeling. To facilitate such efforts, we have developed a suite of codes, collectively referred to as AutoMech, that allow for the automatic prediction of the kinetics for large sets of reactions via ab initio transition-state-theory based master-equation calculations. The primary input is simply the mechanism, a dictionary relating chemically identifiable species descriptors (e.g., SMILES or InChIs) to species labels in the mechanism, and a specification of the electronic structure and transition state theory models to be implemented. Here we illustrate the current utility of AutoMech through a study of the initial stages of pyrolysis for 3 sets of fuels: sequences of alkanes, alcohols, and aldehydes. For simplicity, the analysis focuses on abstractions from the fuel by H, CH 3 , and OH, and the decomposition of the resulting radicals. Altogether, there are a total of 166 input channels in these sets (more than 363 forward reactions when expanded to the full set of elementary reactions). The code successfully produces high quality rate estimates (with apparent uncertainties less than a factor of two in limited comparisons with experiment) for > 95% of these. For the radical decomposition reactions, the analysis includes predictions for the pressure dependence of the kinetics. This wide-ranging exploration illustrates (i) the effect of different levels of prediction on the expected accuracy, (ii) the branching between abstractions at different sites for different abstractors, (iii) the dependence of the rates on the chemical structure, and (iv) the variation in radical stabilities across chemical families. These results, as well as the demonstrated feasibility of the methodology, should find further utility in the development of accurate rate expressions for arbitrary fuels. (c) 2020 The Combustion Institute. Published by Elsevier Inc. All rights reserved.

Elliott, Sarah N.↗
DOE OSTI2021

Ring Opening in Cycloheptane and Dissociation of 1-Heptene at High Temperatures

Cycloalkanes and alkenes are important components of real fuels but there is little kinetic and mechanistic data on the dissociation of most large cyclic and olefinic molecules at elevated temperatures. We present here the first experimental and theoretical investigation of dissociation of cycloheptane and the initial product from ring opening, 1-heptene. Experiments were performed in a diaphragmless shock tube using laser schlieren densitometry. Pyrolysis of cycloheptane (0.5-4% in Kr) was studied over 1450-2000 K and 30-120 Torr. Experiments with 1-heptene (1-4% in Kr) covered 1200-1650 K and 30-120 Torr. A newly developed chemical kinetic mechanism for pyrolysis of cycloheptane and 1-heptene is presented herein. Simulations are in very good agreement with the experimental measurements. Rate coefficients for the initial ring-opening process in cycloheptane, k 1 , and dissociation of 1-heptene, k 2 , were determined from the experiments. Both k 1 and k 2 are in falloff, and the pressure and temperature dependencies were well reproduced by theoretical calculations allowing extrapolation to conditions beyond the scope of this work. These calculations yielded the following expressions for k 1 and k 2 with the uncertainties estimated as +/- 40% and +/- 50% respectively: k 1 , infinity = 5 . 94 & times; 10 17 exp ( & minus;44 T, 521 ) s & minus;1 and k 2 , infinity = 8 . 86 & times; 10 16 exp ( & minus;35 , 887 T ) s & minus;1 . The results of this study indicate that cycloheptane dissociates similarly to cyclopentane and cyclohexane, i.e. ring-opening via C -C scission to a diradical that rapidly isomerizes to a conjugate 1-alkene. The secondary chemistry is dominated by the dissociation products of the 1-alkenes i.e. allyl and n-alkyl radicals. Furthermore, rates of dissociation of the cycloalkanes are size dependent and k cyclopentane << k cyclohexane < k cycloheptane . (c) 2020 The Combustion Institute. Published by Elsevier Inc. All rights reserved.

Chemical kinetics↗
DOE OSTI2020

A Repositioning Method for Shared Autonomous Vehicles Operation

Shared fully-automated, or autonomous, mobility (SAVs) is anticipated to be the likely choice for future urban travel. SAVs boast many operational benefits but will add congestion in the form of unoccupied miles. The fleet's success further depends on service measures like the wait times for pickup trips. Agent-based simulation tools have closely looked at SAV operations but typically lack the integration between the supply and demand sides when simulating a population at scale. This paper focuses on the impact of SAV relocation on traveler wait times using a novel algorithm for repositioning. POLARIS, an agent-based tool, is used for a case study of Bloomington, Illinois to quantify the benefits of allowing SAV repositioning. On average, the wait times were lower with repositioning for all adequate fleet sizes. SAVs were available more uniformly across the region's zones, and proportional to trip-making at different times of day. In addition, with repositioning enable a higher share of demands were served. Finally, the increase in empty fleet miles from SAV repositioning may be justified with more trips being served, and an overall improvement in SAV wait times. (C) 2020 The Authors. Published by Elsevier B.V.

Agent-Based Simulation↗
DOE OSTI2020

Hazard-Based Model of Activity Generation Using Vehicle Trajectory Data

Travel behavior modeling suffers from lack of longitudinal data due to the high cost of procurement and difficulty with ensuring data quality. In the recent years ubiquitous data intercepted from social media, cell detail record, GPS traces are increasingly being explored to analyze human mobility. However, these data lack key demographic information which limits their use for developing causal models of traveler behavior. The primary contribution of the paper lies in using vehicle trajectory data from Ann Arbor along with multiple other data sources for developing a hazard-based activity generation model. The different category of data used in the analysis include (i) vehicle trajectory data (VTD), (ii) American Census Survey (ACS), (iii) land use data, (iv) household travel survey (HTS) data, and (v) smart location data from Environmental Protection Agency (EPA). Home and work are identified as the two most frequently visited locations from the VTD and validated against land use categories of the region. Next a random utility-based model is developed using HTS data to identify other activity purposes as a function of the polynomials of distance from home, activity duration and departure time. The developed model is then applied to identify the non-home activity purposes in the VTD. Demographic and accessibility information are appended to the VTD from ACS and smart location databases respectively. The fmal database is then used to develop a hazard-based activity generation model. (C) 2020 The Authors. Published by Elsevier B.V.

activity generation↗
DOE OSTI2022

A thermoelectric materials database auto-generated from the scientific literature using ChemDataExtractor

An auto-generated thermoelectric-materials database is presented, containing 22,805 data records, automatically generated from the scientific literature, spanning 10,641 unique extracted chemical names. Each record contains a chemical entity and one of the seminal thermoelectric properties: thermoelectric figure of merit, ZT; thermal conductivity, κ; Seebeck coefficient, S; electrical conductivity, σ; power factor, PF; each linked to their corresponding recorded temperature, T. The database was auto-generated using the automatic sentence-parsing capabilities of the chemistry-aware, natural language processing toolkit, ChemDataExtractor 2.0, adapted for application in the thermoelectric-materials domain, following a rule-based sentence-simplification step. Data were mined from the text of 60,843 scientific papers that were sourced from three scientific publishers: Elsevier, the Royal Society of Chemistry, and Springer. To the best of our knowledge, this is the first automatically-generated database of thermoelectric materials and their properties from existing literature. The database was evaluated to have a precision of 82.25% and has been made publicly available to facilitate the application of data science in the thermoelectric-materials domain, for analysis, design, and prediction.

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

A database of thermally activated delayed fluorescent molecules auto-generated from scientific literature with ChemDataExtractor

A database of thermally activated delayed fluorescent (TADF) molecules was automatically generated from the scientific literature. It consists of 25,482 data records with an overall precision of 82%. Among these, 5,349 records have chemical names in the form of SMILES strings which are represented with 91% accuracy; these are grouped in a subsidiary database. Each data record contains one of the following four properties: maximum emission wavelength (λ EM ), photoluminescence quantum yield (PLQY), singlet-triplet energy splitting (ΔE ST ), and delayed lifetime (τ D ). The databases were created through text mining using ChemDataExtractor, a chemistry-aware natural-language-processing toolkit, which has been adapted for TADF research. The text-mined corpus consisted of 2,733 papers from the Royal Society of Chemistry and Elsevier. To the best of our knowledge, these databases are the first databases that have been auto-generated for TADF molecules from existing publications. The databases have been publicly released for experimental and computational applications in the TADF research field.

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

Software Citation in HEP: Current State and Recommendations for the Future

In November 2022, the HEP Software Foundation and the Institute for Research and Innovation for Software in High-Energy Physics organized a workshop on the topic of Software Citation and Recognition in HEP. The goal of the workshop was to bring together different types of stakeholders whose roles relate to software citation, and the associated credit it provides, in order to engage the community in a discussion on: the ways HEP experiments handle citation of software, recognition for software efforts that enable physics results disseminated to the public, and how the scholarly publishing ecosystem supports these activities. Reports were given from the publication board leadership of the ATLAS, CMS, and LHCb experiments and HEP open source software community organizations (ROOT, Scikit-HEP, MCnet), and perspectives were given from publishers (Elsevier, JOSS) and related tool providers (INSPIRE, Zenodo). This paper summarizes key findings and recommendations from the workshop as presented at the 26th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2023).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Introduction to Fuel Cycle Front End: From Mining Through Utilization

This book chapter introduces the Fuel Cycle Front End: Mining through Utilization Section of this Encyclopedia, providing context for the chapters that follow. It presents an overview of the nuclear fuel cycle and describes design considerations important to fuel technology. This manuscript version of a book chapter from the Encyclopedia of Nuclear Energy (Elsevier, 2021) that was not reviewed in LRS prior to being sent to the book general editor for review or for final publication. It also has not yet been uploaded to SORT/OSTI. The content includes classified subject matter topics, but does not include any classified information (judgement of the author as a Derivative Classifier).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Deformable phrase level attention: A flexible approach for improving AI based medical coding

Objective: Improving the AI-driven automated medical encoding of clinical text plays a vital role in gathering information on the occurrence of diseases to improve population-level health. This work presents a novel attention mechanism designed to enhance text classification models and ensure appropriate classification of medical concepts in unstructured electronic health records. Materials and Methods: We developed a deformable, phrase-level attention mechanism to identify important lexical word-level and contextual phrase-level information from clinical text documents. We evaluated conventional and transformer-based deep learning models that we extended with our attention mechanism on the extraction of critical cancer information (e.g., site, subsite, laterality, histology, behavior) from 629,908 electronic pathology reports and on the automated medical encoding of 52,722 hospital discharge summaries. Results: Transformer-based models with the deformable, phrase-level attention mechanism achieved the best performance on the extraction of critical cancer information from pathology reports. Conventional- and transformer-based models show similar or better performance than their baseline counterparts on the automated medical encoding of clinical documents. Discussion: The addition of phrase-level information allowed models extended with our proposed method to outperform standard word-level attention. Our method showed favorable properties for the real-world application in terms of model robustness and phenotyping. These results indicate that our method is promising for automated data harmonization for common data models. Conclusion: This work proposes a novel deformable, phrase-level attention mechanism that enhances text classification models in the extraction of medical concepts from clinical text documents. We demonstrate strong performances on two clinical text datasets and showcase real-world deployability of our method.

Automated medical encoding↗
DOE OSTI2020

Illuminating White Dwarf Spectra through Laboratory Experiments at Cosmic Conditions

We establish the work on white dwarf stars in the larger context of the experiments of the Wootton Center for Astrophysical Plasma Properties (WCAPP); these experiments are conducted at the plasma conditions found in the cosmos, without the need for scaling. We briefly summarize the results of these experiments to-date and their astrophysical and physical import, before focusing on the white dwarf experiments. Over 97% of stars either are, or will become, white dwarf stars, giving them broad relevance. We describe the astrophysical and physical problems associated with white dwarf photospheres, the plasma where the observed light arises. Here, the astrophysical questions include the age of the universe, the age and history of star formation in our Galaxy's varied morphological components and the evolution of stars. The compact nature of these ubiquitous stars means that the atomic physics is not well constrained even in the outermost layers. Further, it suggests that many important processes, including crystallization in dense Coulomb plasma, occur and have a significant effect on the evolution and structure of these stars and thus all their many applications.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Precision Møller polarimetry for PREX-2 and CREX

The PREX-2 and CREX experiments in Hall A at Jefferson Lab are precision measurements of parity violating elastic electron scattering from complex nuclei. One requirement was that the incident electron beam polarization, typically , be known with 1% precision. We commissioned and operated a Møller polarimeter on the beam line that exceeds this requirement, achieving a precision of 0.89% for PREX-2, and 0.85% for CREX. The uncertainty is purely systematic, accumulated from several different sources, but dominated by our knowledge of the target polarization. Our analysis also demonstrates the need for accurate atomic wave functions in order to correct for the Levchuk Effect. We describe the details of the polarimeter operation and analysis, as well as (for CREX) a comparison to results from a different polarimeter based on Compton scattering.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Mondo: integrating disease terminology across communities

Precision medicine aims to enhance diagnosis, treatment, and prognosis by integrating multimodal data at the point of care. However, challenges arise due to the vast number of diseases, differing methods of classification, and conflicting terminological coding systems and practices used to represent molecular definitions of disease. This lack of interoperability artificially constrains the potential for diagnosis, clinical decision support, care outcome analysis, as well as data linkage across research domains to support the development or repurposing of therapeutics. There is a clear and pressing need for a unified system for managing disease entities⁠—including identifiers, synonyms, and definitions. To address these issues, we created the Mondo disease ontology—a community-driven, open-source, unified disease classification system that harmonizes diverse terminologies into a consistent, computable framework. Mondo integrates key medical and biomedical terminologies, including Online Mendelian Inheritance in Man (OMIM), Orphanet, Medical Subject Headings (MeSH), National Cancer Institute Thesaurus (NCIt), and more, to provide a comprehensive and accurate representation of disease concepts with fully provenanced and attributed links back to the sources. Mondo can be used as the handle for curation of gene–disease associations utilized in diagnostic applications, research applications such as computational phenotyping, and in clinical coding systems in clinical decision support by pointing the clinician to the numerous knowledge resources linked to the Mondo identifier. Mondo's community-centric approach, stewarded by the Monarch Initiative's expertise in ontologies, ensures that the ontology remains adaptable to the evolving needs of biomedical research and clinical communities, as well as the knowledge providers.

biomedical informatics↗