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1,331 records · Page 74
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Crosslinked polymers with tunable coefficients of thermal expansion

Curatives and their resulting thermosets and other crosslinked polymers can reduce thermal expansion mismatch between an encapsulant and objects that are encapsulated. This can be accomplished by incorporating a negative CTE moiety into the thermoset resin or polymer backbone. The negative CTE moiety can be a thermal contractile unit that shrinks as a result of thermally induced conversion from a twist-boat to chair or cis/trans isomerization upon heating. Beyond CTE matching, other potential uses for these crosslinked polymers and thermosets include passive energy generation, energy absorption at high strain rates, mechanophores, actuators, and piezoelectric applications.

Redline, Erica Marie↗
DOE OSTI2023

Expandable implant and implant system

An embodiment of the invention includes an expandable implant to endovascularly embolize an anatomical void or malformation, such as an aneurysm. An embodiment is comprised of a chain or linked sequence of expandable polymer foam elements. Another embodiment includes an elongated length of expandable polymer foam coupled to a backbone. Another embodiment includes a system for endovascular delivery of an expandable implant (e.g., shape memory polymer) to embolize an aneurysm. The system may include a microcatheter, a lumen-reducing collar coupled to the distal tip of the microcatheter, a flexible pushing element detachably coupled to an expandable implant, and a flexible tubular sheath inside of which the compressed implant and pushing element are pre-loaded. Other embodiments are described herein.

Wilson, Thomas S.↗
DOE OSTI2023

Polymers having stable cationic pendant groups for use as anion exchange membranes

Poly(aryl alkylene) polymers or poly(aryl-crown ether-alkylene) polymers with pendant cationic groups are provided which have an alkaline-stable cation, such as imidazolium, introduced into a rigid aromatic polymer backbone free of ether bonds. Hydroxide exchange membranes or hydroxide exchange ionomers formed from these polymers exhibit superior chemical stability, hydroxide conductivity, decreased water uptake, good solubility in selected solvents, and improved mechanical properties in an ambient dry state as compared to conventional hydroxide exchange membranes or ionomers. Hydroxide exchange membrane fuel cells and hydroxide exchange membrane electrolyzers comprising the poly(aryl alkylene) polymers or poly(aryl-crown ether-alkylene) polymers with pendant cationic groups exhibit enhanced performance and durability at relatively high temperatures.

Yan, Yushan↗
DOE OSTI2024

Sustainable Public Transport: Providing Responsive, On-Demand Service with Clean Energy

The National Renewable Energy Laboratory (NREL) uses the Mobility Energy Productivity (MEP) as a metric and a lens to guide applied research into high performance public mobility. In the current initiative to abate global warming, the US needs not only zero-emission vehicles in the transit fleet (such as buses and shuttles) but also time- and cost-effective services to connect people with goods, services and employment toward a high-quality of life. Our current transportation system is overly dependent on personally-owned automobiles for high quality mobility, with public modes being less viable in many areas. Simply electrifying the drivetrains of existing public transit modes will fail to improve the quality of mobility for those that do not have access to private automobiles. The slow rebound by transit from the pandemic reveals the need to reinvent public transit service. Using the MEP lens, NREL researchers have tracked various novel developments in the public mobility space, with the confluence of shared, on-demand transit (ODT) services using light duty vehicles emerging as a key enabler of high-efficiency public mobility. Deployments such as those in Arlington, TX, Dallas, TX, Fort Erie, ON, and Innisfil, ON showcase the use of fleets of light-duty vehicles as the basis for community circulation and first/last mile to intra-regional transit. ODT services have demonstrated improvements in being more time efficient for riders, more energy efficient in operation (even before the introduction of fully electric vehicles), as well as being cost effective. It appears that aspects of the long-awaited promise of Personal Rapid Transit from the 1970s are beginning to be realized through ODT deployments, leveraging transportation network company (TNC) logistics, popularized by Uber and Lyft, but applied to public mobility. Currently, manually driven ODT operations are already cost competitive with traditional transit systems on a cost per ride basis, and full automation promises to reduce costs by 50% while providing additional safety and verified customer service. Connecting these ODT systems with efficient and effective intra-regional backbone transit service is the next step, with transit agencies like DART providing early results. This discussion will walk through the evidence for this postulated outcome and show results from a series of case-studies.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗
DOE OSTI2024

Analysis of NCERC Critical Experiments with ENDF/B Nuclear Data Libraries

Nuclear data (ND) libraries are the backbone of the nuclear industry, as they are the collections of tabulated probabilities that define sub-atomic particle interactions with matter. In the areas of criticality safety and experiments, no evaluated nuclear data files (ENDF) are more important than those containing neutron cross section data. It is upon these files, and accompanying radiation transport codes, that practitioners are enabled to safely design both subcritical and critical systems. Likewise, in a symbiotic fashion, it is the same critical assemblies which are used primarily to validate that the cross sections are correct. The ENDF/B library, the United States’ national library maintained by the National Nuclear Data Center (NNDC) at Brookhaven National Laboratory (BNL), is soon releasing a new version, ENDF/B-VIII.1. Prior to the official release, several beta versions of the library were prepared and tested in simulation suites. The work presented here are results comparing the newest ENDF/B beta release (ENDF/B-VIII.1b3) and ENDF/B-VIII.0 with recent experiments done at the National Criticality Experiments Research Center (NCERC) as well as correlated experiments from the Los Alamos Critical Experiments Facility (LACEF). These NCERC and LACEF experiments were performed in part to provide validation for various cross sections that were identified as insufficient in the ENDF/B-VIII.0. In particular, lead, copper, fluorine, and chlorine, as well as the major actinides, were targeted from the last decade of critical experiments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Herbaceous Feedstock 2022 State of Technology Report

The U.S. Department of Energy promotes production of advanced liquid transportation fuels from lignocellulosic biomass by funding fundamental and applied research that advances the state of technology (SOT). As part of its involvement in this mission, Idaho National Laboratory completes an annual SOT report for nth-plant and 1st-plant herbaceous biomass feedstock logistics. The purpose of the SOT is to provide the status of feedstock supply system technology development for herbaceous biomass to biofuels relative to technical targets and cost goals from specific design cases, based on data and experimental results. Although conventional feedstock supply systems form the backbone of the emerging biofuels industry, they have limitations that restrict widespread implementation on a national scale. To meet the demands of the future industry, the feedstock supply system must shift from the conventional system to what has been termed “advanced” supply systems. In advanced designs, a distributed network of aggregation and processing centers, termed “depots,” are employed near the points of biomass production (i.e., the field or forest) to reduce feedstock variability and produce feedstocks of a uniform format, moving toward biomass commoditization. The 2022 Herbaceous SOT is part of a vision of achieving an implemented advanced feedstock supply system, which produces a stable, tradable commodity at the decentralized distributed depot. It utilizes feedstock fractionation by incorporating technologies that can separate the biomass into its anatomical fractions (leaves, husks, stems and cobs) to reduce impurities and produce fractions that satisfy downstream quality considerations. By using a series of air classification steps, this strategy can reduce the extrinsic ash in corn stover and produce enriched tissue fractions that can be blended to a conversion specification or converted individually in optimized biochemical conversion campaigns. Additionally, a majority of the leaves (which do not meet the quality specification) are separated out early and can be supplied to alternate markets. The 2022 Herbaceous SOT incorporates an advanced biomass fractionation and processing system to produce pellets enriched tissues from three-pass corn stover. The resulting enriched pellets are delivered to the biorefinery individually where they can be blended to a specification or converted in campaigns where the conditions are optimized for each tissue. Unused fractions can be sent to a a midstream market or to a different conversion process that is better suited to their properties to offset the cost of the delivered feedstock. The main benefits from the proposed system can be summarized as: (1) $6.86/dry ton (2016$) lower cost for the air classification due to elimination of the requirement to discard the high ash lights fraction; (2) $1.56/dry ton lower delivered cost by selling the unsuitable leaf fraction into the feed market as a midstream co-product (assuming a selling price that is 11% higher than their cost of production); (3) 0.98% increase in carbohydrate content (from 60.16% to 61.14%); and (4) 0.97% decrease in ash content (from 6.00% to 5.03%) compared to the 2021 Herbaceous SOT. Overall, the 2022 nth-plant Herbaceous SOT predicts a modeled delivered feedstock cost of $78.64/dry ton (2016$) if it is assumed that the enriched leaf fraction is sold at its production cost; this is a slight increase of $0.43/dry ton increase from the 2021 Herbaceous SOT nth-Supply case cost. The increased cost derived from a $0.38/dry ton increase in transportation and handling cost to procure more biomass (to replace the enriched leaf fraction that was not delivered to the biorefinery. The total preprocessing cost was $0.27/dry ton higher than the 2021 result because of updates to energy consumption, purchasing price and dry matter loss data for the rotary shear ($3.00/dry ton increase) and the pelleting mill ($4.52/dry ton increase). The data utilized were generated in pilot-scale tests in the Biomass Feedstock National User Facility (BFNUF) at INL and at Forest Concepts, including tests for rotary shear and pelleting of the air classified fractions. A greenhouse gas emissions analysis was performed by Argonne National Laboratory using the most up to date version of the Greenhouse Gases, Regulated Emissions, and Energy use in Transportation model (GREET®). The analysis showed an increase of 17.34 kg CO2e/dry ton from the 2021 SOT (67.71 kg CO2e/ton in the 2021 Herbaceous SOT to 85.05 kg CO2e/ton in the 2022 Herbaceous SOT). The net increase is primarily attributed to increased energy consumption in pelleting mill.

09 BIOMASS FUELS↗
DOE OSTI2024

A Method for Producing Hierarchical and Statistically Calibrated Predictions of Nuclear Material Properties from Existing Models

Computer vision-based analysis of micrographs of nuclear materials is an emerging technique for property prediction, synthetic route identification, and other material analysis tasks. These analysis tasks play a pivotal role in many material characterization applications such as signature development for treaty verification, process optimization, etc. The backbone in many of the recent computer vision-based techniques is a deep learning model, which takes a fixed-size set of pixels and provides a class prediction for that set of pixels. For example, previous work developed a deep convolutional neural network (CNN) to predict the synthetic route from a 256 px x 256 px patch taken from a larger image of uranium ore concentrates. In this work, we present several methods for first calibrating these models in a manner that they can provide accurate probabilities of their predictions’ veracity, and several methods of combining these probabilities. Overall, the combination of these two steps into a pipeline allows for full-image and even full-sample (where a sample has many images) predictions with associated confidence values. Finally, we show that one can also use the patch predictions and confidence to produce a visualization to map predicted constituents through the image. Results and examples for predicting and mapping uranium ore concentrates’ synthetic process from imagery will be presented.

artificial intelligence↗
DOE OSTI2024

Crosslinked polymers with tunable coefficients of thermal expansion

Curatives and their resulting thermosets and other crosslinked polymers can reduce thermal expansion mismatch between an encapsulant and objects that are encapsulated. This can be accomplished by incorporating a negative CTE moiety into the thermoset resin or polymer backbone. The negative CTE moiety can be a thermal contractile unit that shrinks as a result of thermally induced conversion from a twist-boat to chair or cis/trans isomerization upon heating. Beyond CTE matching, other potential uses for these crosslinked polymers and thermosets include passive energy generation, energy absorption at high strain rates, mechanophores, actuators, and piezoelectric applications.

Redline, Erica M.↗
DOE OSTI2024

Polymers depolymerizable by metathesis of a cleavable unit

Novel polymers are depolymerizable by metathesis of a cleavable unit. As an example, a series of linear and crosslinked polyurethanes were prepared that can be selectively depolymerized under mild conditions. Two unique polyols were synthesized bearing unsaturated units in a configuration designed to favor ring-closing metathesis to five- and six-membered cycloalkenes. These polyols were co-polymerized with toluene diisocyanate to generate linear polyurethanes and trifunctional hexamethylene- and diphenylmethane-based isocyanates to generate crosslinked polyurethanes. The polyol design is such that the ring-closing metathesis reaction cleaves the backbone of the polymer chain. Upon exposure to dilute solutions of Grubbs' catalyst under ambient conditions, the polyurethanes were rapidly depolymerized to low molecular weight, soluble products bearing vinyl and cycloalkene functionalities. These functionalities enabled further re-polymerization by traditional strategies for polymerization of double bonds. This general approach can be expanded to develop a range of chemically recyclable condensation polymers that are readily depolymerized by orthogonal metathesis chemistry.

Jones, Brad Howard↗
DOE OSTI2024

Gas permeable fluoropolymers and ionomers

Novel copolymers that are fluoropolymers including a first repeat unit that is fluorinated and cyclic and a second repeat unit from a trifluorovinyl methylene ether monomer having sulfur or sulfone functionality in the pendant group are disclosed. The copolymers have relatively high gas permeability as a result of a cyclic repeat unit in the copolymer backbone and ionomers from oxidation of the sulfur containing functionality are particularity useful in the cathode structure of a proton exchange membrane fuel cell.

Lousenberg, Robert Daniel↗
DOE OSTI2024

3D printable feedstock inks for signal control or computation

In one aspect the present disclosure relates to a 3D printed signal control backbone apparatus. The apparatus may have a filament including a first material section and a plurality of second material sections. The first material section is bounded on opposing ends by the second material sections. The first material section is formed by an ink having a percolating network of a plurality of chiplets infused in a non-conductive polymer. The plurality of chiplets form electrically responsive elements imparting a predetermined logic function and which are responsive to a predetermined electrical signal. The second material sections are formed by an ink which is electrically conductive.

Murialdo, Maxwell↗
DOE OSTI2025

A Guide to Current Limiting and Stability with Grid-Forming Inverters

The electric power grid is changing. For many decades, the synchronous generator - an electromechanical device invented in 1887 - has been the workhorse and backbone of power grids across the globe. Our entire infrastructure is built around it. But times change, and so does the power grid. Since the early 21st century, we have seen a gradual shift in modern power grids away from synchronous generators to ones dominated by power electronic inverter-based resources (IBRs). Sources such as photovoltaics, wind turbines, battery storage, fuel cells, and other technologies like high-voltage DC transmission interconnections all rely on an inverter to connect and interface with the grid. They are increasingly being installed on the grid to augment, or even replace, traditional energy sources. This change is a fundamental shift that brings tremendous technical challenges and questions: Can a power grid remain stable with many more inverter-based resources? How do we avoid more blackouts on the grid? How do we keep the grid secure and resilient during disturbances? After all, power electronic inverters are nothing like the big, rotating, iron-and-copper machines that the grid heavily relies on. Many of these questions can be answered by using grid-forming (GFM) inverters, yet many research challenges remain. This document explores GFM inverters and how they can help stabilize the future grid, especially during disturbances and contingencies. It summarizes a two-year research and development fellowship program at NREL. We point interested readers to more detailed works developed during the project along the way. Let's dive in

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Efficient Anomaly Detection Driven By Different Machine Learning Architectures And Models

The rapid growth and ubiquitous adoption of the internet and cyber-physical systems (CPS) have fundamentally transformed modern communication, work, and human-system interactions. While networks now form the backbone of critical digital ecosystems, enabling seamless data transmission across diverse, interconnected systems, this increased connectivity also expands the attack surface, making real-time detection of network intrusions and anomalies a pressing challenge. Detecting unusual activities within network infrastructure requires advanced data traffic analysis to differentiate between legitimate and malicious interactions. Traditional approaches to network anomaly detectionâ??such as rule-based and signature-based systemsâ??often depend on predefined patterns to identify known anomalies, limiting their effectiveness against emerging, stealthy, or previously unseen threats. These conventional methods suffer from high false alarm rates and fail to adapt to the ever-evolving nature of network traffic, particularly in large-scale, decentralized environments where data volume, velocity, and variety are constantly increasing. This dissertation presents artificial intelligence (AI)-driven approaches to anomaly detection that leverage graphics processing unit (GPU)-enabled high-performance computing (HPC) platforms for processing massive network traffic data and monitoring the components of cyber-physical systems (CPS) for potentially hazardous conditions. The research advances several key contributions: (1) Designing efficient machine learning techniques for CPS condition monitoring and anomaly detection; (2) enabling federated learning (FL) frameworks that enable distributed detection while preserving data privacy and system resilience; (3) exploring graph-based methodologies combining graph neural networks (GNN) and graph machine learning (ML) approaches for the Internet of Things (IoT) and automotive network security, and (4) performing distributed edge computing optimizations that integrate FL with scalable technologies for reduced communication overhead. Through extensive experiments, these methodologies demonstrate that complex anomaly detection and condition monitoring tasks can be achieved while balancing computational efficiency and detection accuracy through fine-grained network information processing. The frameworks developed in this research establish a robust foundation for network anomaly detection, providing scalable, adaptive, and privacy-preserving solutions for safeguarding CPS and IoT networks in an increasingly interconnected digital landscape. The practical implications of these research findings are significant, as they can inform the development of next-generation network security systems and contribute to the protection of critical infrastructure against sophisticated cyber attacks.

Marfo, William↗
DOE OSTI2026

Toxicity of Common Fluoropolymers and PFAS on C. Elegans and an Innovative Strategy to Promote in Situ Remediation - 26128

Per- and polyfluoroalkyl substances (PFAS) are a broad class of synthetic chemicals used in a variety of modern technologies and consumer products. PFAS have an alkyl backbone with all or most of the hydrogen (H) atoms replaced with fluorine (F) atoms. PFAS generally fall into one of two categories, they can be non-polymeric with relatively low molecular weights, or long-chain polymers. PFAS are a diverse group of organic compounds that can be solids, liquids, dispersions, or gases. Their mobility and toxicity are influenced by their chain lengths and functional groups. Non-polymeric PFAS are common building blocks for the manufacturing of fluoropolymers. Non-polymeric PFAS are known to be mobile in the environment and some are considered contaminants of emerging concern. Polymeric PFAS, or fluoropolymers, are typically thought to be of low concern, however few systematic investigations into their toxicity have been completed. PFAS, including fluoropolymers and microplastics, have been found in pristine environments and animals located far from site of origin including the arctic and deep ocean.

Jacobs, Stephanie [Savannah River National Laborat↗
NASA NTRS2002

NEPTUNE: an under-sea plate scale observatory

The NEPTUNE project will establish a linked array of undersea observatories on the Juan de Fuca tectonic plate. This observatory will provide a new kind of research platform for real-time, long-term, plate-scale studies in the ocean and Earth sciences.

shore station backbone↗