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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

Computational analysis of pathogen-borne metallo β-lactamases reveals discriminating structural features between B1 types

Background: Genes conferring antibiotic resistance to groups of bacterial pathogens are cause for considerable concern, as many once-reliable antibiotics continue to see a reduction in efficacy. The recent discovery of the metallo b-lactamase blaNDM-1 gene, which appears to grant antibiotic resistance to a variety of Enterobacteriaceae via a mobile plasmid, is one example of this distressing trend. The following work describes a computational analysis of pathogen-borne MBLs that focuses on the structural aspects of characterized proteins. Results: Using both sequence and structural analyses, we examine residues and structural features specific to various pathogen-borne MBL types. This analysis identifies a linker region within MBL-like folds that may act as a discriminating structural feature between these proteins, and specifically resistance-associated acquirable MBLs. Recently released crystal structures of the newly emerged NDM-1 protein were aligned against related MBL structures using a variety of global and local structural alignment methods, and the overall fold conformation is examined for structural conservation. Conservation appears to be present in most areas of the protein, yet is strikingly absent within a linker region, making NDM-1 unique with respect to a linker-based classification scheme. Variability analysis of the NDM-1 crystal structure highlights unique residues in key regions as well as identifying several characteristics shared with other transferable MBLs. Conclusions: A discriminating linker region identified in MBL proteins is highlighted and examined in the context of NDM-1 and primarily three other MBL types: IMP-1, VIM-2 and ccrA. The presence of an unusual linker region variant and uncommon amino acid composition at specific structurally important sites may help to explain the unusually broad kinetic profile of NDM-1 and may aid in directing research attention to areas of this protein, and possibly other MBLs, that may be targeted for inactivation or attenuation of enzymatic activity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Improving Thermal Management Strategies for Data Centers: A Physical Testbed Incorporating Small Modular Reactor and Microreactor Technology

This study aims to accelerate the demonstration of various thermal management systems for data centers using nuclear-generated heat to enhance energy and grid reliability. Utilizing mobile containerized and stationary test beds at INL's High Performance Computing (HPC) facility, this project integrates with various nuclear-related energy systems testing facilities. Key components include immersion cooling apparatus, absorption chillers, and adjustable thermal management simulators. Tasks involve acquiring necessary hardware, sensors, and cooling apparatus, engaging with data center industry stakeholders, and providing a testing platform for algorithms, models, tools, and software. The objective is to expedite the deployment of nuclear-powered data centers, thereby improving energy reliability and affordability.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
DOE OSTI2017

Understanding of the Elemental Diffusion Behavior in Concentrated Solid Solution Alloys

As one of the core effects on the high-temperature structural stability, the so-called “sluggish diffusion effect” in high-entropy alloy (HEA) has attracted much attention. Experimental investigations on the diffusion kinetics have been carried out in a few HEA systems, such as Al-Co-Cr-Fe-Ni and Co-Cr-Fe-Mn-Ni. However, the mechanisms behind this effect remain unclear. To better understand the diffusion kinetics of the HEAs, a combined computational/experimental approach is employed in the current study. In the present work, a self-consistent atomic mobility database is developed for the face-centered cubic (fcc) phase of the Co-Cr-Fe-Mn-Ni quinary system. The simulated diffusion coefficients and concentration profiles using this database can well describe the experimental data both from this work and the literatures. The validated mobility database is then used to calculate the tracer diffusion coefficients of Ni in the subsystems of the Co-Cr-Fe-Mn-Ni system with equiatomic ratios. The comparisons of these calculated diffusion coefficients reveal that the diffusion of Ni is not inevitably more sluggish with increasing number of components in the subsystem even with homologous temperature. Taking advantage of computational thermodynamics, the diffusivities of alloying elements with composition and/or temperature are also calculated. Furthermore, these calculations provide us an overall picture of the diffusion kinetics within the Co-Cr-Fe-Mn-Ni system.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Transforming Energy Through Computational Excellence: A Virtual Test-Drive of Energy Scenarios

Researchers at the National Renewable Energy Laboratory (NREL) are conducting groundbreaking research to decarbonize transportation systems and reduce emissions. As they plan for growing populations and related demands on aging infrastructure and energy systems, local transportation departments and city planners are facing significant, complex challenges. New approaches to planning and operations, as well as capitalizing on rapidly advancing technology, can address mobility and energy-centric challenges, including cost and energy efficiency, emissions reduction, decarbonization, and congestion.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

N-Doping improves charge transport and morphology in the organic non-fullerene acceptor O-IDTBR

Molecular doping has been shown to improve the performance of various organic (opto)electronic devices. When compared to p-doped systems, research into n-doped organic small-molecules is relatively limited, primarily due to the lack of suitable dopants and the often encountered unfavourable microstructural effects. These factors have prevented the use of n-doping in a wider range of existing materials, such as non-fullerene acceptors (NFAs), that have already shown great promise for a range of (opto)electronic applications. Here, we show that several different molecular n-dopants, namely [1,2-b:2',1'-d]benzo[i][2.5]benzodiazocine potassium triflate adduct (DMBI-BDZC), tetra-n-butylammonium fluoride (TBAF) and 4-(2,3-dihydro-1,3-dimethyl-1H-benzimidazol-2-yl)-N,N-dimethylbenzenamine (N-DMBI), can be used to n-dope the molecular semiconductor O-IDTBR, a promising NFA, and increase the electron field-effect mobility to >1 cm 2 V -1 s -1 . By combining complementary experimental techniques with computer simulations of doping and charge carrier dynamics, we show that improved charge transport arises from synergistic effects of n-type doping and morphological changes. Specifically, a new, previously unreported dopant-induced packing orientation results in one of the highest electron mobility values reported to-date for an NFA molecule. Overall, this work highlights the importance of dopant–semiconductor interactions and their impact on morphology, showing that dopant-induced molecular packing motifs may be generic and a key element of the charge transport enhancement observed in doped organics.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Performance analysis of Wald-statistic based network detection methods for radiation sources

There have been increasingly large deployments of radiation detection networks that require computationally fast algorithms to produce prompt results over ad-hoc sub-networks of mobile devices, such as smart-phones. These algorithms are in sharp contrast to complex network algorithms that necessitate all measurements to be sent to powerful central servers. In this work, at individual sensors, we employ Wald-statistic based detection algorithms which are computationally very fast, and are implemented as one of three Z-tests and four chi-square tests. At fusion center, we apply the K-out-of-N fusion to combine the sensors hard decisions. We characterize the performance of detection methods by deriving analytical expressions for the distributions of underlying test statistics, and by analyzing the fusion performances in terms of K, N, and the false-alarm rates of individual detectors. We experimentally validate our methods using measurements from indoor and outdoor characterization tests of the Intelligence Radiation Sensors Systems (IRSS) program. In particular, utilizing the outdoor measurements, we construct two important real-life scenarios, boundary surveillance and portal monitoring, and present the results of our algorithms.

Sen, Satyabrata↗
DOE OSTI2024

In Silico Human Mobility Data Science: Leveraging Massive Simulated Mobility Data (Vision Paper)

Human mobility data science using trajectories or check-ins of individuals has many applications. Recently, we have seen a plethora of research efforts that tackle these applications. However, research progress in this field is limited by a lack of large and representative datasets. The largest and most commonly used dataset of individual human trajectories captures fewer than 200 individuals, while datasets of individual human check-ins capture fewer than 100 check-ins per city per day. Thus, it is not clear if findings from the human mobility data science community would generalize to large populations. Since obtaining massive, representative, and individual-level human mobility data is hard to come by due to privacy considerations, the vision of this work is to embrace the use of data generated by large-scale socially realistic microsimulations. Informed by both real data and leveraging social and behavioral theories, massive spatially explicit microsimulations may allow us to simulate entire megacities at the person level. The simulated worlds, which do not capture any identifiable personal information, allow us to perform “in silico” experiments using the simulated world as a sandbox in which we have perfect information and perfect control without jeopardizing the privacy of any actual individual. In silico experiments have become commonplace in other scientific domains such as chemistry and biology, permitting experiments that foster the understanding of concepts without any harm to individuals. This work describes challenges and opportunities for leveraging massive and realistic simulated alternate worlds for in silico human mobility data science.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Preliminary Logistics Modeling of the Integrated Wash Aid Treatment Emergency Reuse System - 19495

We employed Analysis of Mobility Platform (AMP) and GoldSim software to model the logistics of deploying materials to implement the Integrated Wash Aid Treatment Emergency Reuse System (IWATERS) in a hypothetical cesium-contamination scenario covering a four-block strip of downtown Chicago, IL. In this deployment of IWATERS, buildings were washed down via fire-hosing and contaminated wash solution was collected in the city's waste/stormwater collection system. The contaminated wash water was treated to remove Cs via ad hoc sand/clay filtration beds, and the treated wash solution was recycled during continuing decontamination operations. A detailed task timeline for the IWATERS deployment and information (or assumptions) on the availability and location of required resources for operations provided input parameters, as well as a framework, to enable the AMP and GoldSim simulations. From the decision to deploy IWATERS to the end of operations, including the completion of processing all contaminated wash water, took 49 days with decontamination teams active for 35 days and treatment bed teams active for 37 days. The modeling results showed the availability of vermiculite clay (based on data supplied by its commercial vendors/distributors) as the limiting factor for deploying treatment bed teams and, consequentially, the recycling rate of wash water and the timeline for decontamination operations. These simulations represent the first attempt at understanding the material and personnel requirements for large-scale IWATERS operation. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Measuring Fundamental Improvements in Sustainable Urban Mobility: The Mobility-Energy Productivity Metric

Recent technological advancements in mobility are creating many options for connecting citizens with employment, goods, and services, particularly in urban areas where modes such as bike and car shares, electric scooters, ridesourcing, and ridesharing are proliferating at a rapid pace. Analysis and tools for overall transportation planning are dominated by urban regional travel demand models whose roots in highway operations poorly reflect the system dynamics in denser areas where parking costs, convenience, and availability - not to mention sustainability concerns and quality of life - are driving people to an ever-greater spectrum of mobility services. In this paper, we present a new paradigm for evaluating mobility options within an urban area. First developed for the U.S. Department of Energy's Energy Efficient Mobility System research program, this metric is termed the mobility-energy productivity (MEP) metric. At its heart, the MEP metric measures accessibility and appropriately weights it with travel time, cost, and energy of modes that provide access to opportunities in any given location. The proposed metric is versatile in that it can be computed from readily available data sources or derived from outputs of regional travel demand models. End times associated with parking, curb access, cost, and reliability and frequency of service need to be carefully considered to obtain an appropriate and accurate perspective when computing the metric. Ultimately, the MEP metric can be used to reflect the impacts of new mobility technologies (transportation network companies, electric scooters), business models (car shares and bike shares), and land-use practices (such as transit-oriented development) on sustainable urban mobility. This paper lays out the need, requirements, and framework for this new metric, and offers it, in collaboration with the American Society for Civil Engineers (ASCE), as a foundational metric for smart city assessment.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2019

Measuring Fundamental Improvements in Sustainable Urban Mobility: The Mobility-Energy Productivity Metric: Preprint

Recent technological advancements in mobility are creating many options for connecting citizens with employment, goods, and services, particularly in urban areas where modes such as bike and car shares, electric scooters, ridesourcing, and ridesharing are proliferating at a rapid pace. Analysis and tools for overall transportation planning are dominated by urban regional travel demand models whose roots in highway operations poorly reflect the system dynamics in denser areas where parking costs, convenience, and availability - not to mention sustainability concerns and quality of life - are driving people to an ever-greater spectrum of mobility services. In this paper, we present a new paradigm for evaluating mobility options within an urban area. First developed for the U.S. Department of Energy's Energy Efficient Mobility System research program, this metric is termed the Mobility-Energy Productivity (MEP) metric. At its heart, the MEP metric measures accessibility and appropriately weights it with travel time, cost, and energy of modes that provide access to opportunities in any given location. The proposed metric is versatile in that it can be computed from readily available data sources or derived from outputs of regional travel demand models. End times associated with parking, curb access, cost, and reliability and frequency of service need to be carefully considered to obtain an appropriate and accurate perspective when computing the metric. Ultimately, the MEP metric can be used to reflect the impacts of new mobility technologies (transportation network companies, electric scooters), business models (car shares and bike shares), and land-use practices (such as transit-oriented development) on sustainable urban mobility. This paper lays out the need, requirements, and framework for this new metric, and offers it, in collaboration with the American Society for Civil Engineers (ASCE), as a foundational metric for Smart City assessment.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2019

Full in silico DFT characterization of lanthanum and yttrium based oxynitride semiconductors for solar fuels

Finding new solar-energy absorber materials is one of the most significant challenges in artificial photosynthesis. Starting from the experimentally available LaTaON 2 and LaTiO 2 N oxynitrides, we use DFT to propose new sunlight absorbing semiconductors. The synthetically unknown YTaON 2 and YTiO 2 N are semiconductors with indirect band gaps of 2.7 eV and 2.9 eV, respectively. For the first time, we compute within Boltzmann transport theory the DOS-averaged effective mass and mobility of LaTaON 2 , LaTiO 2 N, YTaON 2 and YTiO 2 N. Our first principles calculations indicate that the Y-based materials possess advantageous dielectric (ε r ≥ 47), optical (α ≥ 10 4 cm –1 near band edge), and charge transport properties (m e,h*DOS ≈ 0.2; μ e,h ≈ 10 2 cm 2 V –1 s –1 ) for the conversion of solar energy into storable fuels. Furthermore, our work leads to the complete in silico design of semiconductors for water splitting.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

The Next Stage for Smart Cities: Metrics to Spur an Evolution from Technology for Efficiency to Technology for People's Needs

The Smart Cities movement is about a decade old, energized by the USDOT Smart Cities grant that sparked cities to dream big. Now, 10 years later, and multitudes of conferences and papers later, the biggest question regarding Smart Cities is whether any progress has been made? Smart Cities forums are typically led by the technology sector, either telecommunications, internet access, or most recently artificial intelligence (AI) concerns. Each of these areas have grown and found new applications in the context of Smart Cities, however, these technology applications are just tools toward ends. Do digital communications and assistance enable or foster improved access to real, tactile, non-virtual goods and services such as transportation, food, housing, trash removal, health care, education, social interaction? These and other topics are not 'big tech', but are each critical to quality of life outcomes and are day-to-day necessities, comprising many of the touch points through which citizens interact with municipal agencies. Regarding Smart Cities, relationships have not been fully refined as to how best to merge the emerging generation of technology and related trends with more mundane but essential requirements of tactile services. How should municipal managers and operators bring the range of new technology tools (e.g. on-demand transit, automated vehicles, digital connectivity) to bear to improve functions serving real- physical- non-virtual needs? How do we make cities more efficient in providing access to services and opportunities for improved quality of life? This paper examines the current Smart City movement, emerging trends, and the need to put metrics with respect to the delivery, access, and provision of real-life needs. Using a few case studies of past, present, and projected future scenarios, this paper attempts to bring Smart Cities into the real cities domain, perhaps pushing the moniker away from 'Smart' to 'Efficient' - something that can be measured, counted, and assessed. Through the consideration of the next stage of the evolution of cities from 'Smart' to 'Efficient', the combined efforts and experience of multiple researchers at the NREL and their network of collaborators highlights the need for updates metrics that can be used to start guiding efforts toward productive initiatives to improve quality of life.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2014

Los Alamos National Laboratory 4D Database

4D is an integrated development platform - a single product comprised of the components you need to create and distribute professional applications. You get a graphical design environment, SQL database, a programming language, integrated PHP execution, HTTP server, application server, executable generator, and much more. 4D offers multi-platform development and deployment, meaning whatever you create on a Mac can be used on Windows, and vice-versa. Beyond productive development, 4D is renowned for its great flexibility in maintenance and modification of existing applications, and its extreme ease of implementation in its numerous deployment options. Your professional application can be put into production more quickly, at a lower cost, and will always be instantly scalable. 4D makes it easy, whether you're looking to create a classic desktop application, a client-server system, a distributed solution for Web or mobile clients - or all of the above!

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Resolving local ordering and structure in Mn x Ge 1- x Te alloys through thermodynamic ensembles of pair distribution functions

Characterizing local bonding environments in complex materials is essential for understanding and optimizing their properties. Equally as important is the ability to predict local motifs as a function of synthesis conditions, enhancing chemists’ ability to design properties into materials. In this study, we present an approach to leverage statistical mechanics to generate temperature- and energy-informed ensemble averaged pair distribution functions (PDFs). This method, which we have named Thermodynamic Ensemble Averages of PDFs for Ordering and Transformations (TEAPOT), utilizes density functional theory (DFT) to relax supercells while incorporating energetic penalties for local order, enabling accurate and computationally efficient analysis of local structure. We apply this method to the neutron PDF measurements of the pseudobinary MnTe–GeTe (MGT) alloy, demonstrating its capability to resolve complex local distortions and chemical ordering. Our results reveal detailed insights into phase transformations and local distortions driven by Mn substitution. For compositions that globally present as rock salt, our analysis reveals that Ge coordination geometry is heavily impacted by synthesis temperature. We propose that high temperature synthesis conditions promote a lowered Ge polyhedra distortion, promoting high charge carrier mobility due to the alignment of local and global structure. Incorporating statistical mechanics and computation into experimental analysis thus guides synthesis of tailored local structure.

36 MATERIALS SCIENCE↗
DOE OSTI2014

On the origin of the two-dimensional electron gas at AlGaN/GaN heterojunctions and its influence on recessed-gate metal-insulator-semiconductor high electron mobility transistors

It is commonly accepted that interface states at the passivation surface of AlGaN/GaN heterostructures play an important role in the formation of the 2DEG density. Several interface state models are cited throughout literature, some with discrete levels, others with different kinds of distributions, or a combination of both. The purpose of this article is to compare the existing interface state models with both direct and indirect measurements of these interface states from literature (e.g., through the hysteresis of transfer characteristics of Metal-Insulator-Semiconductor High Electron Mobility Transistors (MISHEMTs) employing such an interface in the gate region) and Technology Computer Aided Design (TCAD) simulations of 2DEG densities as a function of the AlGaN thickness. The discrepancies between those measurements and TCAD simulations (also those commonly found in literature) are discussed. Then, an alternative model inspired by the Disorder Induced Gap State model for compound semiconductors is proposed. It is shown that defining a deep border trap inside the insulator can solve these discrepancies and that this alternative model can explain the origin of the two dimensional electron gas in combination with a high-quality interface that, by definition, has a low interface state density.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Evaluating Time Varying Connectivities and System Throughput in Opportunistic Networks for Smart Grid Applications

With increasing proliferation of smart phones, there is an opportunity to employ mobile ad hoc networks to connect to distributed energy assets located in remote areas. With embedded intelligence and edge computing capabilities, autonomous ‘edge control nodes’ can enable a decentralized energy nexus, without the need for on-demand communications. Authors have developed an opportunistic networking framework using Bluetooth Low Energy and a specialized mobile phone application that enables delay tolerant networking for the above framework. Here, this paper presents the analysis of time varying graph connectivity for such an opportunistic mobile ad hoc network. Dependence of connectivity on different network parameters such as radio characteristics, the mobility of data mules and parameters governing how connections are established are explored. Simulation results showing the variation of above trends have been presented.

Bluetooth↗
DOE OSTI2024

Seasonal Patterns in Mobile Colistin Resistance Gene Variants in Wastewater Bioaerosols and Liquid Sludge

To address the growing threat of global antimicrobial resistance, a one-health approach is needed to understand the complex socioecological cycling of antibiotic resistance genes. In this study, a metagenomics approach using DNA shotgun sequencing, metagenome assembly, and antibiotic resistance gene (ARG) annotation was used to examine seasonal patterns in the abundance of mobile colistin resistance (mcr) gene variants in bioaerosols and liquid sludge in three wastewater treatment plants (WWTPs). ARGs represented 0.2–0.8 and 0.1–0.2% of the bioaerosol and liquid sludge metagenomes, respectively, while mcr genes represented 0–0.3 and 0–0.5% of the identified ARGs in bioaerosol and liquid sludge metagenomes. Seven of the ten known mcr variants were detected in wastewater bioaerosol and liquid samples, with mcr-5 and mcr-8 being the most prevalent across all seasons and sites. Furthermore, additional functional and taxonomic annotation of mcr-containing metagenomic contigs showed that mcr genes were often located on contigs with other co-occurring ARGs and mobile genetic elements and may be harbored by opportunistic human pathogens and other bacterial taxa not previously associated with mcr genes. Atmospheric dispersion modeling showed that mcr-containing bioaerosols can be transported kilometers away from the WWTPs, resulting in the possible dissemination of these ARGs into surrounding environments and communities.

Antimicrobial agents↗
DOE OSTI2021

The Role of Mobility Data Hubs in an Integrated Decarbonized Transportation Future

The landscape for connected mobility ecosystems is evolving rapidly as information and communication technologies lower the cost and complexity of connecting people to places, integrating transportation modes and collecting data regarding such movements. These developments have been key to unlocking new business opportunities, particularly through mobility services. While the mechanisms for data collection, processing, and transfer have made significant advances in the past decade, the broader landscape of mobility data architectures and data users remains largely unresolved. It is unclear as to whether the result will converge towards a framework that resembles a coherent quilt or a disjointed patchwork of competing visions. Initial approaches to mobility data collection and provisioning have been largely siloed - by mode or software - or held for exclusive use, however several key players are quickly realizing the need and opportunities enabled through integrated mobility data eco-systems, or mobility data hubs as referred to in this paper. As the business case for hosting mobility data hubs evolves, there is great uncertainty regarding their impact to either advance or exacerbate sustainable mobility (e.g., seamless connectivity across modes, decreased energy consumption and greenhouse gas emissions, etc.). Groups such as the United Nations and World Bank have identified data platforms as a key enabler of realizing environmental and social benefits. If designed with decarbonization in mind, we hypothesize that enhanced observability provided by these ever-expanding mobility data hubs can facilitate energy and emissions reductions that are otherwise limited by transactional barriers and knowledge asymmetry that is inherent to a more siloed approach. In this sense, integration of mobility data can help to create a competitive playing field where value is not determined by exclusivity of data, but rather the quality and uniqueness of a given service. The goals of this paper are to 1) identify key players and data architectures that are emerging in a service-based mobility market, 2) explore several use cases where mobility data hubs have enabled greater sustainability outcomes, and 3) discuss key issues that will need to be resolved to fully leverage emerging mobility data hubs towards a sustainable transportation future.

ADVANCED PROPULSION SYSTEMS,MATHEMATICS AND COMPUT↗