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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Predicting content consumption from content-to-content relationships

As the majority of Internet traffic today is attributed to content-centric applications, there has been ever-increasing demand for highly scalable and efficient content delivery. An accurate prediction on future content consumption is essential for such demand. To address such an issue, this paper introduces a new computational approach, Content Network (CN) that can capture the relations among contents, and its potential applications. We conduct a measurement study to investigate how contents are inter-related from the viewpoint of content spreading on one of the popular BitTorrent portals: The Pirate Bay. Based on the large-scale dataset that contains 18 K torrents and 9 M users, we construct the CN and investigate its structural properties. Our key finding is that contents in the same community in the CN (i) belong to the same content category with 94% probability, (ii) are uploaded by the same content publisher with 76% probability, and (iii) have the similar titles with 51% probability, which implies that contents in the same community collectively contain common (shared) interests of users. Our trace-driven study demonstrates that the proposed CN model is useful in (i) content recommendation for increasing sales and (ii) content caching for networking efficiency. We believe our work can provide an important insight for content stakeholders, e.g., content providers for efficient publishing strategies, network engineers for networking efficiency, or content marketers for accurate recommendation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Ride-hailing and taxi versus walking: Long term forecasts and implications from large-scale behavioral data

Introduction: Although ride-hailing and taxi trips can potentially reduce single-occupant vehicle trips and auto ownership, they can also replace pedestrian trips. Because physical activity is associated with improved health outcomes, the extent to which ride-hailing and taxi travel captures walking's mode share is of interest to policymakers. Methods: Based on large-scale behavioral data from the 2017 U.S. National Household Travel Survey, this paper reports on the development of a full Bayesian logistic regression model for determining the mode split between (1) ride-hailing and taxi and (2) walk while accounting for unobserved heterogeneity. The results from the stand-alone model inform two longer-term travel forecasting scenarios: a) higher risk of walk trips converting to ride-hailing and taxi, specifically in the future with high prevalence of automated vehicles, b) higher probability of such trips remaining as walking. Results: The results revealed that some of the important characteristics that increase the likelihood of a traveler using the ride-hailing and taxi mode versus walking include having a longer trip, using a smartphone to access the internet, having an interest in technologies, having a medical condition, and living in a metropolitan area with rail access. Further, the results from the first scenario suggest that an overall increase of up to 2.9% in the ride-hailing and taxi mode share may be expected. The second scenario shows that between 68% and 76% of ride-hailing and taxi trips could be diverted to walking if supportive pedestrian infrastructure were provided in the case study locations. The planning process can be adapted to consider not only congestion, crash, and emissions impacts of such shifts but also the effects of a loss of physical activity. Conclusions: The study findings show how the ride-hailing and taxi mode competes with walking. Further, the findings enable planners to update their regional travel forecasting models; policy makers can thus encourage active travel by prioritizing pedestrian infrastructure investments that may divert ride-hailing and taxi trips to walking. However, equity should be a key consideration to ensure that addressing the competition between these two modal choices does not hinder the provision of pedestrian facilities in communities that depend on walking.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Additive manufacturing and applications of nanomaterial-based sensors

Nanoscale materials possess distinct physical and chemical attributes including size-dependent properties, quantum confinement, high surface-to-volume ratio, and superior catalytic activity. These unique qualities enable sensors with high sensitivity, robustness, and fast time response. As the emergence of the Internet of Things (IoT) demands increased production of sensors, it also provides an impetus for concentrated nanomaterial-based sensor research. Meanwhile, additive manufacturing (AM) of nanomaterial-based sensors is critical to bridge the gap between one-off, lab-scale fabrication and cost-effective, industrial-scale production with high reproducibility. By applying the design flexibility and cost savings of AM techniques, a new generation of nanomaterial-based sensing platforms can be integrated with IoT devices in the consumer space. Furthermore, emergent research in human-machine interfaces, food safety, and point-of-care diagnostics will be expedited by the development of sensors that can be printed with irregular form factors. In this Review, the relative strengths and weaknesses of printed sensor systems based on zero-, one-, and two-dimensional nanomaterials are discussed. In addition, sensors enabled by printable soft nanomaterials, heterostructures, and nanocomposites are surveyed due to their synergistic advantages for wearable healthcare monitoring and soft robotics. Lastly, a roadmap for the next decade of research on this topic is provided.

36 MATERIALS SCIENCE↗
DOE OSTI2014

JANIS 4: An Improved Version of the NEA Java-based Nuclear Data Information System

JANIS is software developed to facilitate the visualization and manipulation of nuclear data, giving access to evaluated data libraries, and to the EXFOR and CINDA databases. It is stand-alone Java software, downloadable from the web and distributed on DVD. Used offline, the system also makes use of an internet connection to access the NEA Data Bank database. It is now also offered as a full web application, only requiring a browser. The features added in the latest version of the software and this new web interface are described.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Hybrid classical-quantum communication networks

Over the past several decades, the proliferation of global classical communication networks has transformed various facets of human society. Concurrently, quantum networking has emerged as a dynamic field of research, driven by its potential applications in distributed quantum computing, quantum sensor networks, and secure communications. This prompts a fundamental question: rather than constructing quantum networks from scratch, can we harness the widely available classical fiber-optic infrastructure to establish hybrid quantum–classical networks? This paper aims to provide a comprehensive review of ongoing research endeavors aimed at integrating quantum communication protocols, such as quantum key distribution, into existing lightwave networks. This approach offers the substantial advantage of reducing implementation costs by allowing classical and quantum communication protocols to share optical fibers, communication hardware, and other network control resources—arguably the most pragmatic solution in the near term. In the long run, classical communication will also reap the rewards of innovative quantum communication technologies, such as quantum memories and repeaters. Accordingly, our vision for the future of the Internet is that of heterogeneous communication networks thoughtfully designed for the seamless support of both classical and quantum communications.

Fiber-optic communication↗
DOE OSTI2023

Analysis of hydrogen infrastructure for the feasibility, economics, and sustainability of a fuel cell powered data center

Data centers used for internet data services, cloud computing, and/or data storage consume vast amounts of electricity and are increasing rapidly in capacity. Consequently, their power consumption has raised concerns about energy sustainability and environmental impacts. Large-scale, on-site renewable energy could help reduce data centers’ carbon footprint; however, wind and solar power alone cannot provide an uninterrupted power supply to computer servers due to their natural variability. Instead, reliable power integration can be achieved by using fuel cells powered by hydrogen from sustainable resources (e.g., wind and solar energy). Establishing a hydrogen infrastructure will be critical for realizing these benefits and establishing fuel cells as a viable power source for data centers. Here, to facilitate the development of novel carbon-free fuel cell data enters, this paper presents renewable power integrated with hydrogen infrastructures in four scenarios to provide reliable hydrogen supply from production to storage. Various paths were analyzed toward a hydrogen supply infrastructure by determining the proper component sizes and calculating the cost of meeting the server load. We used a microgrid modeling software, Hybrid Optimization of Multiple Energy Resources (HOMER), and studied the feasibility of fuel cell powered data centers employing renewable hydrogen. The modeling results show various renewable integration configurations to meet reliable and sustainable power requirement under four scenarios for a carbon-free data center.

08 HYDROGEN↗
DOE OSTI2020

The energy footprint of automotive electronic sensors

We discuss how Information and communication technologies (ICT) have emerged as one of the leading technologies to reduce global emissions, particularly in the mobility sector. Automotive electronics, such as sensors/actuators and microcontrollers (commonly known as electronic control units (ECU) which control one or more of the electrical systems or subsystems in a vehicle), play a key role in ICT. Sensors/actuators are key in electronic ICT devices, starting with the data collection and data communication with the internet. The latest two big trends of electrification and automation in vehicles, are projected to increase the use of worldwide automotive sensors from 7.5 billion units in 2017 to 11.0 billion units by the year 2024. A representative state-of-the art automotive sensor system, (i.e., an ultrasonic backup system), including the ECUs controlling the vehicle electrical systems/subsystems, has been considered to estimate the energy footprint in terms of manufacturing and operational energy of global automotive sensors use. A widely used life cycle energy assessment method (i.e., cumulative energy demand) was used as both direct and indirect (including the extraction, manufacturing, and disposal of the raw and auxiliary materials) energy use can be considered for the energy footprint estimation. The embodied manufacturing energy impacts of the system was estimated to be 559 MJ/system, compared to the 417 MJ/system for lifetime system power and additional gasoline use. The share of purchased energy to the embodied energy where the upstream energy isn't included in the former case, is less than 10% and ~ 85% for the component manufacturing and vehicle operation energy uses, respectively. As the purpose of this ultrasonic backup system is to prevent rear crashes, an estimated 1.0 MJ/system is avoided from reduced lifetime vehicular repairs (from an estimated 11% chance of requiring a rear bumper replacement). While all of this is small compared to the overall automotive manufacturing and use energy, the 11 billion automotive sensors expected to be produced in 2024 could require 1540 PJ for manufacturing and those sensors would require an additional 780–1150 PJ for lifetime energy use.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Accounting for multi-dimensional dependencies among decision-makers within a generalized model framework: An application to understanding shared mobility service usage levels

Activity-travel choices of individuals are influenced by spatial dependency effects. As individuals interact and exchange information with, or observe the behaviors of, those in close proximity of themselves, they are likely to shape their behavioral choices accordingly. For this reason, econometric choice models that account for spatial dependency effects have been developed and applied in a number of fields, including transportation. However, spatial dependence models to date have largely defined the strength of association across behavioral units based on spatial or geographic proximity. In the current context of social media platforms and ubiquitous internet and mobile connectivity, the strength of associations among individuals is no longer solely dependent on spatial proximity. Rather, the strength of associations among individuals may be based on shared attitudes and preferences as well. In other words, behavioral choice models may benefit from defining dependency effects based on attitudinal constructs in addition to geographical constructs. In this paper, frequency of usage of car-sharing and ride-hailing services is modeled using a generalized heterogeneous data model (GHDM) framework that incorporates multi-dimensional dependencies among decision-makers. The model system is estimated on the 2014-2015 Puget Sound Regional Travel Study survey sample, with proximity in latent attitudinal constructs defined by a number of personality trait variables. Model estimation results show that social dependency effects arising from similarities in attitudes and preferences are significant in explaining shared mobility service usage. Ignoring such effects may lead to erroneous estimates of the adoption and usage of future transportation technologies and mobility services.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Stakeholder analysis for designing an urban air quality data governance ecosystem in smart cities

Cities, the world over, are fuelling economic growth. At the same time, rapid urbanization is a root cause of serious environmental damage. Recent WHO global air pollution guidelines highlight air pollution as a critical environmental threat along with climate change. To address these threats, smart cities and clean air programs are on a rise. In smart cities, data and Information and Communication Technologies (ICT) are major drivers of city transformations. The 4th Industrial Revolution (4IR) technologies such as the Internet of Things (IoT), big data, artificial intelligence (AI), and cloud computing have the potential to accelerate these transformations toward urban resilience. However, the success of smart cities and clean air programs depends on cohesive multi-sector stakeholder contributions. This study conducted interdisciplinary participative stakeholder analysis to understand the data, and sectorial challenges, to outline the technological opportunities to facilitate clean air programs in Indian smart cities. The research highlights gaps due to siloed stakeholder operations, lack of data calibration, non-alignment of smart city and air quality management services, non-availability of health exposure data, and difficulty in translating scientific data into implementable actions. Stakeholders expressed potential ‘fit for the purpose’ use of IoT devices, satellites, smartphones, and mobility data augmented by AI methods in bridging these gaps. In conclusion, the analysis points toward a need to develop an easily accessible and ubiquitous urban data governance ecosystem enabling seamless cross-sector data exchanges to build trusting relationships among the stakeholders across the air quality management value chain.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

The role of peer review and science for advancing public understanding

We live in a time of rapid change. The Covid-19 pandemic has united the world to understand and develop solutions to protect the health and wellbeing of society. At the same time, access to information on the internet and social media has exploded. People are exposed to information with many claims. Some of the information is relevant and accurate. A significant fraction may be inaccurate, biased, and potentially dangerous. With Covid-19, the information might point to cures that are toxic or risks that are not relevant. The scientific community has developed a process to develop and convey knowledge. The validation of results and their interpretation is critical to advancing knowledge. The core of the scientific process is based on developing a hypothesis-driven concept, designing and executing an experimental approach to prove or disprove the hypothesis, conducting a statistical analysis of the results to confirm their validity, and interpreting their meaning and impact. When their work is completed the scientist prepares to publish the work. Publication requires peer review. Hypotheses, experimental approaches, results, and interpretation of results are independently and anonymously reviewed by a scientific peer. The reviewers are selected based on their expertise in the field. The peer review process is essential for the integrity of the scientific process. Without a robust scientific process, society cannot discriminate between validated results and interpretations and biased, inaccurate, and potentially dangerous conjecture. With inaccurate science society and policy makers may make poor decisions that could hurt people and the world around them. While scientists should not censor information available to the public, scientists have a responsibility to inform the public. We must articulate what the scientific process is and why it is essential when considering the validity of information. Scientist are responsible for pointing out when public information has not been vetted through a scientific process and therefore cannot be considered conclusive. Scientists are responsible for highlighting information that has been generated and vetted with the scientific process. Over time, our goal is for the public to value the scientific process based on peer review. The public could become enlightened to the necessity for peer review to support decisions and action. Scientists need to contribute to advancing public knowledge. When invited to serve as a peer reviewer, scientists have a responsibility to contribute to the process. We all are extremely busy making peer review a distraction. While peer review does not directly benefit our own work and career, it benefits our chosen field of science. This is very important for the research area that our journal, Water-Energy Nexus, is focusing on. We cover the convergence of science and technology integrating across large spatial ranges (micro to global) in environmental pollution and the balance of remediation issues with energy use. Water-Energy Nexus wants to provide scientists with a platform for scientific debate and discussion on this rich and complicated topic. With the manuscripts submitted to WEN cover integrated research topics across a broad range of subjects from environment sciences through energy engineering, the role of peer review is essential. Peer review on a new submission to WEN should not be biased towards a specific science field. It should be done considering the complex nature of issues in the water-energy nexus. Scientists need to contribute to the public dialog. To accomplish these goals, we need to be honest, accurate, articulate, and use understandable language. The impact of WEN is very diverse affecting society in many ways. The scientific audience for WEN is diverse and readers may not fully understand the content of the papers outside their research expertise. Therefore, scientists, especially those who want to contribute to WEN, should work with communications specialists to convey message to benefit society. The audience includes the general public and researchers outside the author’s core specialty. While the peer-reviewed journal article is the cornerstone of our careers and critical for advancing scientific knowledge, a general interest story could benefit society even more. The author cannot lose sight that our work has two audiences, the science community, and more importantly, our family, friends, neighbors, and policy makers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Delivering real-time multi-modal materials analysis with enterprise beamlines

Contemporary advancements in low-cost automation and computation, reduced barrier to entry in developing artificial intelligence/machine learning (AI/ML), and increased ability to represent complex materials in digital form have led to a number of accelerated materials discovery platforms. However, many of these approaches operate with completely rigid vertical integration in an isolated feedback loop using limited modalities. In order to make a substantial impact on discovering new energy materials, AI-driven experiments must operate collaboratively with each other and researchers and over multiple measurement modalities. Herein, we describe the potential for an “internet of things” approach to self-driving enterprise beamlines that merges core information technologies, robotics, and multi-modal AI. The approach will enable full utility of light sources, collaborate effectively with other remote materials acceleration platforms, and help stride toward the world’s energy future.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Next Steps for Compressively Sensed Video in Transmission Electron Microscopy

Here, compressive sensing (CS) is a fast-emerging approach for improving data throughput by taking advantage of the inherent compressibility of real world data—the same kind of compressibility that allows millions of users to stream full-screen video without breaking the internet. Transmission electron microscope (TEM) users regularly collect multi-GB data sets and then use aggressive data reduction strategies to draw out the tiny residual of Shannon entropy that answers the question they wanted to ask. Much of the raw-byte-count information in an acquisition is random, redundant, or irrelevant, yet its collection still represents substantial cost in terms of instrumentation bandwidth and sample damage.

47 OTHER INSTRUMENTATION↗
DOE OSTI2016

ENVIRONMENTAL REVIEWS AND CASE STUDIES: Addressing the Public Outreach Responsibilities of the National Historic Preservation Act: Argonne National Laboratory’s Box Digital Display Platform

Federal agencies are made responsible for managing the historic properties under their jurisdiction by the National Historic Preservation Act of 1966, as amended. A component of this responsibility is to mitigate the effect of a federal undertaking on historic properties through mitigation often through documentation. Providing public access to this documentation has always been a challenge. To address the issue of public access to mitigation information, personnel from Argonne National Laboratory created the Box Digital Display Platform, a system for communicating information about historic properties to the public. The platform, developed for the US Army Dugway Proving Ground, uses short introductory videos to present a topic but can also incorporate photos, drawings, GIS information, and documents. The system operates from a small, self-contained computer that can be attached to any digital monitor via an HDMI cable. The system relies on web-based software that allows the information to be republished as a touch-screen device application or as a website. The system does not connect to the Internet, and this increases security and eliminates the software maintenance fees associated with websites. The platform is designed to incorporate the products of past documentation to make this information more accessible to the public; specifically those documentations developed using the Historic American Building Survey/ Historic American Engineering Record (HABS/HAER) standards. Argonne National Laboratory’s Box Digital Display Platform can assist federal agencies in complying with the requirements of the National Historic Preservation Act. Environmental Practice 18: 209–213 (2016)

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Colloidal Quantum Dot Photovoltaics: Current Progress and Path to Gigawatt Scale Enabled by Smart Manufacturing

Colloidal quantum dots (QDs) have lately been pursued with intense vigor for optoelectronic applications such as photovoltaics (PV), flexible electronics, displays, mid-infrared photodetectors, lasers, and single-photon emitters. These nanometer-sized semiconducting crystals can be suitably mass-produced and size-tuned via cost-effective solution-based synthetic routes to operate in the quantum size confinement regime, endowing them with a wide array of exotic optical and electronic properties. While the first potential market entry could be in displays and in niche applications such as “internet-of-things”, ultimately, the technology has the potential to influence large-scale terrestrial power generation, because it is amenable to high-throughput synthesis from Earth-abundant materials and large-area solution-based coating techniques and can be air-stable. In this Review, we chronicle the recent advances that have propelled QD PV toward commercialization and highlight potential areas for further progress. We present an account of the material compositions being explored as QDs and their various benefits, major chemical passivation and doping strategies that have been developed to allay QD surface traps, and advanced device designs deployed to maximize charge extraction. We also discuss pathways to >20% efficient QD PV and describe recent advances in high-precision and autonomous synthesis of such materials. With recent demonstrations of scalable synthesis of high-quality QDs, smart manufacturing of QDs and QD solids, and fabrication of stable solar cells under ambient conditions, we suggest that the technology is on the road to achieving maturity and technological relevance and that gigawatt per year distributed panel production sites may be within reach.

14 SOLAR ENERGY↗
DOE OSTI2018

Plasma Jet Printing and in Situ Reduction of Highly Acidic Graphene Oxide

Miniaturization of electronic devices and the advancement of Internet of Things pose exciting challenges to develop technologies for patterned deposition of functional nanomaterials. Printed and flexible electronic devices and energy storage devices can be embedded onto clothing or other flexible surfaces. Graphene oxide (GO) has gained much attention in printed electronics due its solution processability, robustness, and high electrical conductivity in the reduced state. We introduce an approach to print GO films from highly acidic suspensions with in situ reduction using an atmospheric pressure plasma jet. Low-temperature plasma of a He and H 2 mixture was used successfully to reduce a highly acidic GO suspension (pH < 2) in situ during deposition. This technique overcomes the multiple intermediate steps required to increase the conductivity of deposited GO. X-ray spectroscopic studies confirmed that the reaction intermediates and the concentration of oxygen functionalities bonded to GO have been reduced significantly by this approach without any additional steps. Moreover, the reduced GO films showed enhanced conductivity. Hence, this technique has a strong potential for printing conducting patterns of GO for a range of large-scale applications.

42 ENGINEERING↗
DOE OSTI2018

Design and Integration of Flexible Sensor Matrix for in Situ Monitoring of Polymer Composites

Sensory polymer composites are highly desirable for applications such as in situ and real-time production processes and structural health monitoring, and for technologies that include human–machine interfaces for the next generation of Internet of Things. However, the development of these materials is still in its infancy: these materials have been reported, but large-scale fabrication of polymer composites with versatile and customizable sensing capabilities has yet to be demonstrated. Here, we report on a scalable fabrication strategy that enables such materials by designing and integrating PCB technology-inspired large-area flexible sensor matrices into polymer composites. The integrated sensor matrices successfully monitored in situ the production processes and structural health of an industrial polymer composite: from the application of vacuum, resin flow and polymerization, production defects, and temperature distribution. Our results demonstrate that the proposed strategy is a simple and effective solution as a distributed monitoring platform for polymer composites and shows the potential towards next generation of sensory polymer composites.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Life Cycle Inventory Availability: Status and Prospects for Leveraging New Technologies

The demand for life cycle assessments (LCA) is growing rapidly, which leads to an increasing demand of life cycle inventory (LCI) data. While the LCA community has made significant progress in developing LCI databases for diverse applications, challenges still need to be addressed. This perspective summarizes the current data gaps, transparency, and uncertainty aspects of existing LCI databases. Additionally, we survey and discuss novel techniques for LCI data generation, dissemination, and validation. We propose key future directions for LCI development efforts to address these challenges, including leveraging scientific and technical advances such as the Internet of Things (IoT), machine learning, and blockchain/cloud platforms. Adopting these advanced technologies can significantly improve the quality and accessibility of LCI data, thereby facilitating more accurate and reliable LCA studies.

blockchain platforms↗
DOE OSTI2016

Multidimensional materials and device architectures for future hybrid energy storage

Electrical energy storage plays a vital role in daily life due to our dependence on numerous portable electronic devices. Moreover, with the continued miniaturization of electronics, integration of wireless devices into our homes and clothes and the widely anticipated ‘Internet of Things’, there are intensive efforts to develop miniature yet powerful electrical energy storage devices. Here, this review addresses the cutting edge of electrical energy storage technology, outlining approaches to overcome current limitations and providing future research directions towards the next generation of electrical energy storage devices whose characteristics represent a true hybridization of batteries and electrochemical capacitors.

36 MATERIALS SCIENCE↗