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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Reactive Extrusion of Waste Plastics with Compatibilizer and Lightly Pyrolyzed Crumb Rubber for Asphalt Modification

Modifying asphalt is a potentially high-value application for reusing waste plastics because of the high-volume usage of asphalt in highway construction. However, simply blending hot plastics and asphalt encounters difficulties related to the poor solubility of polymers, which limits the formation of a swollen network with asphalt molecules. The polymer phases also tend to coalesce and separate from asphalt during high-temperature storage in static conditions. The present study developed an innovative process to stabilize waste plastics in asphalt and improve binder storage stability by using lightly pyrolyzed crumb rubber together with a chemical compatibilizer. Both polymers were extruded to produce a thermoplastic elastomer (TPE) for asphalt modification. The mechanical performance and chemical reactions of TPEs were characterized via tension test and Fourier transform infrared spectroscopy. The storage stability and rheological properties of modified binder blends were evaluated through laboratory asphalt stability test and dynamic shear rheometer test. Polymer phases and network structures were characterized through optical microscopy. It was found that the pyrolyzed and reactive extrusion process improved the rubber solubility and polymer interaction, and therefore the storage stability of modified binder blends. The co-existence of rigid plastic and soft rubbery regimes in an entangled network provided a promising pathway to improve the mechanical performance of asphalt binders in both high- and low-temperature domains.

Ma, Yuetan↗
DOE OSTI2018

Crosscut report: Exascale Requirements Reviews, March 9–10, 2017 – Tysons Corner, Virginia. An Office of Science review sponsored by: Advanced Scientific Computing Research, Basic Energy Sciences, Biological and Environmental Research, Fusion Energy Sciences, High Energy Physics, Nuclear Physics

The mission of the U.S. Department of Energy Office of Science (DOE SC) is the delivery of scientific discoveries and major scientific tools to transform our understanding of nature and to advance the energy, economic, and national security missions of the United States. To achieve these goals in today’s world requires investments in not only the traditional scientific endeavors of theory and experiment, but also in computational science and the facilities that support large-scale simulation and data analysis. The Advanced Scientific Computing Research (ASCR) program addresses these challenges in the Office of Science. ASCR’s mission is to discover, develop, and deploy computational and networking capabilities to analyze, model, simulate, and predict complex phenomena important to DOE. ASCR supports research in computational science, three high-performance computing (HPC) facilities — the National Energy Research Scientific Computing Center (NERSC) at Lawrence Berkeley National Laboratory and Leadership Computing Facilities at Argonne (ALCF) and Oak Ridge (OLCF) National Laboratories — and the Energy Sciences Network (ESnet) at Berkeley Lab. ASCR is guided by science needs as it develops research programs, computers, and networks at the leading edge of technologies. As we approach the era of exascale computing, technology changes are creating challenges for science programs in SC for those who need to use high performance computing and data systems effectively. Numerous significant modifications to today’s tools and techniques will be needed to realize the full potential of emerging computing systems and other novel computing architectures. To assess these needs and challenges, ASCR held a series of Exascale Requirements Reviews in 2015–2017, one with each of the six SC program offices,1 and a subsequent Crosscut Review that sought to integrate the findings from each. Participants at the reviews were drawn from the communities of leading domain scientists, experts in computer science and applied mathematics, ASCR facility staff, and DOE program managers in ASCR and the respective program offices. The purpose of these reviews was to identify mission-critical scientific problems within the DOE Office of Science (including experimental facilities) and determine the requirements for the exascale ecosystem that would be needed to address those challenges. The exascale ecosystem includes exascale computing systems, high-end data capabilities, efficient software at scale, libraries, tools, and other capabilities. This effort will contribute to the development of a strategic roadmap for ASCR compute and data facility investments and will help the ASCR Facility Division establish partnerships with Office of Science stakeholders. It will also inform the Office of Science research needs and agenda. The results of the six reviews have been published in reports available on the web at http://exascaleage.org/. This report presents a summary of the individual reports and of common and crosscutting findings, and it identifies opportunities for productive collaborations among the DOE SC program offices.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Construction of Blaze at the University of Illinois at Chicago: A Shared, High-Performance, Visual Computer for Next-Generation Cyberinfrastructure-Accelerated Scientific, Engineering, Medical and Public Policy Research

The Blaze high-performance visual computing system serves the high-performance computing research and education needs of University of Illinois at Chicago (UIC). Blaze consists of a state-of-the-art, networked, computer cluster and ultra-high-resolution visualization system called CAVE2(TM) that is currently not available anywhere in Illinois. This system is connected via a high-speed 100-Gigabit network to the State of Illinois' I-WIRE optical network, as well as to national and international high speed networks, such as the Internet2, and the Global Lambda Integrated Facility. This enables Blaze to serve as an on-ramp to national cyberinfrastructure, such as the National Science Foundation’s Blue Waters petascale computer at the National Center for Supercomputing Applications at the University of Illinois at Chicago and the Department of Energy’s Argonne Leadership Computing Facility (ALCF) at Argonne National Laboratory. DOE award # DE-SC005067, leveraged with NSF award #CNS-0959053 for “Development of the Next-Generation CAVE Virtual Environment (NG-CAVE),” enabled us to create a first-of-its-kind high-performance visual computing system. The UIC Electronic Visualization Laboratory (EVL) worked with two U.S. companies to advance their commercial products and maintain U.S. leadership in the global information technology economy. New applications are being enabled with the CAVE2/Blaze visual computing system that is advancing scientific research and education in the U.S. and globally, and help train the next-generation workforce.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Understanding important features of deep learning models for segmentation of high-resolution transmission electron microscopy images

Cutting edge deep learning techniques allow for image segmentation with great speed and accuracy. However, application to problems in materials science is often difficult since these complex models may have difficultly learning meaningful image features that would enable extension to new datasets. In situ electron microscopy provides a clear platform for utilizing automated image analysis. In this work, we consider the case of studying coarsening dynamics in supported nanoparticles, which is important for understanding, for example, the degradation of industrial catalysts. By systematically studying dataset preparation, neural network architecture, and accuracy evaluation, we describe important considerations in applying deep learning to physical applications, where generalizable and convincing models are required. With a focus on unique challenges that arise in high-resolution images, we propose methods for optimizing performance of image segmentation using convolutional neural networks, critically examining the application of complex deep learning models in favor of motivating intentional process design.

36 MATERIALS SCIENCE↗
DOE OSTI2024

CdZnTeSe: Recent advances for radiation detector applications

The quest for cost-effective, high performing room temperature semiconductor detector (RTSD) materials for high energy gamma rays has been continuing for more than three decades. The requirements for RTSD materials, however, are more stringent as compared to other applications unrelated to detection of X- and gamma-rays, mainly due to the requirement of thick detectors for sufficient absorption of high-energy electromagnetic radiation and excellent charge-transport properties. The II-VI compound CdZnTe (CZT) with the composition of 10 atomic % Zn (Cd0.9Zn0.1Te) has been the material of choice over the past several years, and it has dominated the commercial market for RTSD materials and detectors. Despite its commercial success as a room temperature radiation detection material, CZT suffers from a lack of compositional homogeneity on both a micro- and macro-scale and the presence of high concentrations of sub-grain boundary (dislocation walls) networks and secondary phases (Te-rich inclusions). This chapter focuses on the presence of performance-limiting defects in CZT that hinder the yield and elevate the cost of high-quality detectors. The presence of such performance-limiting defects has restricted widespread deployment of CZT for a variety of potential applications, particularly for uses of relatively large detectors where the demands on material perfection are significantly greater. In the recent past, replacing some of the tellurium with selenium in the CZT matrix was found to be very effective in drastically reducing the Te-rich secondary phases and dislocation networks, plus

Roy, Utpal N.↗
DOE OSTI2015

Synthesis of carbon core–shell pore structures and their performance as supercapacitors

High-power supercapacitors require excellent electrolyte mobility within the pore network and high electrical conductivity for maximum capacitance and efficiency. Achieving high power typically requires sacrificing energy densities, as the latter demands a high specific surface area and narrow porosity that impedes ion transport. Here, we present a novel solution for this optimization problem: a nanostructured core–shell carbonaceous material that exhibits a microporous carbon core surrounded by a mesoporous, graphitic shell. The tunable synthesis parameters yielded a structure that features either a sharp or a gradual transition between the core and shell sections. Electrochemical supercapacitor testing using organic electrolyte revealed that these novel core–shell materials outperform carbons with homogeneous pore structures. The hybrid core–shell materials showed a combination of good capacitance retention, typical for the carbon present in the shell and high specific capacitance, typical for the core material. These materials achieved power densities in excess of 40 kW kg -1 at energy densities reaching 27 Wh kg -1 .

25 ENERGY STORAGE↗
DOE OSTI2019

Optimizing Lossy Compression Rate-Distortion from Automatic Online Selection between SZ and ZFP

With ever-increasing volumes of scientific data produced by high-performance computing applications, significantly reducing data size is critical because of limited capacity of storage space and potential bottlenecks on I/O or networks in writing/reading or transferring data. SZ and ZFP are two leading BSD licensed open source C/C++ libraries for compressed floating-point arrays that support high throughput read and write random access. However, their performance is not consistent across different data sets and across different fields of some data sets, which raises the need for an automatic online (during compression) selection between SZ and ZFP, with minimal overhead. In this paper, the automatic selection optimizes the rate-distortion, an important statistical quality metric based on the signal-to-noise ratio. To optimize for rate-distortion, we investigate the principles of SZ and ZFP. We then propose an efficient online, low-overhead selection algorithm that predicts the compression quality accurately for two compressors in early processing stages and selects the best-fit compressor for each data field. Here, we implement the selection algorithm into an open-source library, and we evaluate the effectiveness of our proposed solution against plain SZ and ZFP in a parallel environment with 1,024 cores. Evaluation results on three data sets representing about 100 fields show that our selection algorithm improves the compression ratio up to 70 percent with the same level of data distortion because of very accurate selection (around 99 percent) of the bestfit compressor, with little overhead (less than 7 percent in the experiments).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Hydrous ruthenium oxide nanoparticles anchored to graphene and carbon nanotube hybrid foam for supercapacitors

In real life applications, supercapacitors (SCs) often can only be used as part of a hybrid system together with other high energy storage devices due to their relatively lower energy density in comparison to other types of energy storage devices such as batteries and fuel cells. Increasing the energy density of SCs will have a huge impact on the development of future energy storage devices by broadening the area of application for SCs. Here, we report a simple and scalable way of preparing a three-dimensional (3D) sub-5 nm hydrous ruthenium oxide (RuO₂) anchored graphene and CNT hybrid foam (RGM) architecture for high-performance supercapacitor electrodes. This RGM architecture demonstrates a novel graphene foam conformally covered with hybrid networks of RuO₂ nanoparticles and anchored CNTs. SCs based on RGM show superior gravimetric and per-area capacitive performance (specific capacitance: 502.78 F g⁻¹, areal capacitance: 1.11 F cm⁻²) which leads to an exceptionally high energy density of 39.28 Wh kg⁻¹ and power density of 128.01 kW kg⁻¹. The electrochemical stability, excellent capacitive performance, and the ease of preparation suggest this RGM system is promising for future energy storage applications.

25 ENERGY STORAGE↗
DOE OSTI2023

Making coordination networks ionic: a unique strategy to achieve solution-processable hybrid semiconductors

The development of high-performance, solution-processable semiconducting materials is crucial for the advancement of emerging clean-energy technologies such as light-emitting diodes and photovoltaics. While hybrid perovskites have shown considerable promise for implementation in these technologies, their reliance on toxic metals and relatively low stability towards moisture and chemical environments remain to be addressed. In this Chemistry Frontiers article, we describe a unique strategy to build nontoxic, robust and solution-processable hybrid semiconductors based on copper halide by incorporating ionic bonds in coordination complexes (molecular or extended network structures). Specifically, these compounds are made of anionic copper(I) halide and cationic organic ligands that form both coordinate and ionic bonds at the inorganic/organic interfaces and are referred to as all-in-one (AIO)-type structures. Here, the unique bonding nature renders the AIO-type structures with greatly enhanced solubility, excellent optical tunability and remarkable framework stability, all highly desirable for thin-film based optoelectronic devices. We will highlight the most recent progress in the development of this material group, including their design strategies, important properties and potential for clean-energy related applications. We will also briefly discuss the existing challenges and future outlook of these materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Performance Study of Virtual Frisch Grid CdZnTeSe Detectors

Nuclear detectors for x-ray and gamma-ray spectroscopy and imaging are a vital tool in many homeland security, medical imaging, astrophysics and other applications. Most of these applications require room-temperature operation due to the operational constraints imposed by a cryogenic cooling system. CdZnTe (CZT) has been the main material with the desired detection properties, and CZT crystals have been used commercially for three decades. However, CdZnTe still suffers from long-standing issues of high densities of performance-limiting intrinsic defects such as Te inclusions and networks of dislocation walls (sub-grain boundaries). A recently invented new quaternary material CdZnTeSe showed excellent material properties for radiation detection. The material was found to be free from dislocation networks, possess reduced Te inclusions, and have better compositional homogeneity. Virtual Frisch grid detectors were fabricated from crystals taken from a CdZnTeSe ingot that was grown by the traveling heater method. The detectors were fabricated from an as-grown ingot, bypassing the post-growth annealing process commonly practiced for industrial-grade CZT. The performances of the detectors were studied with different Frisch grid lengths using an amplifier shaping time ranging from 1–6 µs. The detectors showed high-quality spectroscopic performance with an as-measured energy resolution of ~1.1% at 662 keV for an optimum Frisch grid length of 3 mm. The charge collection was observed to enhance for longer Frisch grids.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

App2Net: Moving App Functions to Network & a Case Study on Low-latency Feedback

Recent advances in programmable networks enable custom processing of data at hundreds of gigabits per second. These advances can boost the performance of many distributed applications. Yet the high-level languages used by application developers are different from the data plane programming languages (such as P4 and NPL) used by network equipment. This language barrier slows innovation. Our hourglass-shaped architectural solution aims to lower this language barrier. This enables the application developer community to leverage programmable networks for achieving better performance. In this paper we propose a JSON-based intermediate representation to bridge the gap between applications and in-network computing. We demonstrate an instance of the solution in the context of a low-latency feedback application that enables SQL-based data filtering in a P4-based programmable environment. We also present a prototype compiler to convert an intermediate representation in JSON to P4 source.

Sankaran, Ganesh↗
DOE OSTI2023

Snowmass 2021 Computational Frontier CompF4 Topical Group Report Storage and Processing Resource Access

Computing plays a significant role in all areas of high energy physics. The Snowmass 2021 CompF4 topical group's scope is facilities R&D, where we consider "facilities" as the computing hardware and software infrastructure inside the data centers plus the networking between data centers, irrespective of who owns them, and what policies are applied for using them. In other words, it includes commercial clouds, federally funded High Performance Computing (HPC) systems for all of science, and systems funded explicitly for a given experimental or theoretical program. This topical group report summarizes the findings and recommendations for the storage, processing, networking and associated software service infrastructures for future high energy physics research, based on the discussions organized through the Snowmass 2021 community study.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Impact of Concurrent Solubilization and Fines Migration on Fracture Aperture Growth in Shales during Acidized Brine Injection

Acidic hydraulic fracturing fluid chemically and physically alters shale rock fabric during injection and shut-in, creating a “reaction-altered zone” along the fracture faces. To better characterize the variable thickness and composition of this reaction-altered zone under advective flow, we take a coupled experimental and modeling approach. A fluidic cell, with six fiducial markers, is first fabricated to keep the rock sample in place during the core floods and to allow image alignment of acquired images. Then, we conduct a series of reactive core floods in a clay-rich siliceous Wolfcamp shale sample with 10 wt % carbonate, using a synthetic fracturing fluid under no confining stress and at room temperature. High-resolution computed tomography (CT) scans are periodically conducted to observe the spatial alteration of the fracture network. We then perform scanning electron microscopy (SEM-EDS) on the two orthogonal surfaces (fracture surface and freshly cut profile face) to generate high-resolution elemental maps that show the change in mineralogy, both with distance along a given flow path along a fracture surface and with depth from the fracture surface into the shale matrix. These results are contrasted against a two-dimensional (2D) advection-diffusion reaction model developed previously for batch reactions between shale and synthetic fracturing fluids. The model simulates the geochemical interaction occurring at the fracture/matrix interface and penetrating into the shale matrix during the reactive core flood. Both model and experimental results show that the acidic brine is neutralized during the core flood, corresponding to an increase in fracture aperture as a function of fluid volume injected with the greatest change near the inlet. SEM-EDS scans reveal significant dissolution of carbonates on the fracture surface without pyrite oxidation. The reactive transport model indicates that carbonate depletion into the shale interior should be observable, yet SEM-EDS shows no discernible loss of carbonate in the orthogonal profile face. The combination of these observations suggests an additional fracture evolution mechanism in the reactive system, i.e., fines migration. We show that fines migration enhances the access of fracturing fluid to the matrix resulting in a more pronounced fracture widening. Finally, we conclude that coupled mineral dissolution and fines migration govern fracture aperture growth during acidized brine injection. In this work, we effectively show the underlying risk of relying solely on models that do not include an important (transport) process that can alter the system significantly and propose a combined chemomechanical mechanism for fracture evolution appropriate for this shale mineralogy.

58 GEOSCIENCES↗
DOE OSTI2016

Ceria nanoparticles uniformly decorated on graphene nanosheets with coral-like morphology for high-performance supercapacitors

Graphical abstract: The study reported the synthesis of coral-like CeO{sub 2}/GNs for supercapacitors. The unique architecture with overall connected framework and good conducting network of the graphene greatly boosts the Faradaic redox reaction. Therefore, the CeO{sub 2}/GNs delivers an excellent electrochemical performance. - Highlights: • The study reported the synthesis of CeO{sub 2}/GNs. • The graphene was woven into CeO{sub 2}, acting as a good conducting network. • The CeO{sub 2}/GNs shows a coral-like structure. • The architecture creates an overall connected framework. • The CeO{sub 2}/GNs delivers good capacitive performances. - Abstract: CeO{sub 2}/graphene was synthesized by a simple microwave method along with subsequent calcination. CeO{sub 2} nanoparticles with an average size of 68.8 nm are uniformly decorated on graphene nanosheets (CeO{sub 2}/GNs). The CeO{sub 2}/GNs displays a like-coral morphology. The architecture including overall connected framework, abundant intercrossed and interconnected nanochannels and perfect conducting network of the graphene, endows the CeO{sub 2}/GNs material with a superior electron and mass transport. As a result, the CeO{sub 2}/GNs gives a high specific capacitance of 503.4 F/g at 2 A/g and good cycle performance with 91.8% capacitance retention after 3000 cycles. Further, an asymmetric supercapacitors was assembled by using CeO{sub 2}/GNs as the positive electrode and activated carbon as the negative electrode, the asymmetric device demonstrate a favorable energy density of 30.2 Wh/kg at the power density of 750.0 W/kg and superior cycle life with 86.4% the capacitance retenion at 5 A/g after 3000 cycles.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Flexible and high-performance electrochromic devices enabled by self-assembled 2D TiO 2 /MXene heterostructures

Transition metal oxides (TMOs) are promising electrochromic (EC) materials for applications such as smart windows and displays, yet the challenge still exists to achieve good flexibility, high coloration efficiency and fast response simultaneously. MXenes (e.g. Ti 3 C 2 T x ) and their derived TMOs (e.g. 2D TiO 2 ) are good candidates for high-performance and flexible EC devices because of their 2D nature and the possibility of assembling them into loosely networked structures. Here we demonstrate flexible, fast, and high-coloration-efficiency EC devices based on self-assembled 2D TiO 2 /Ti 3 C 2 T x heterostructures, with the Ti 3 C 2 T x layer as the transparent electrode, and the 2D TiO 2 layer as the EC layer. Benefiting from the well-balanced porosity and connectivity of these assembled nanometer-thick heterostructures, they present fast and efficient ion and electron transport, as well as superior mechanical and electrochemical stability. We further demonstrate large-area flexible devices which could potentially be integrated onto curved and flexible surfaces for future ubiquitous electronics.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Hierarchical 3D Nanolayered Duplex-Phase Zr with High Strength, Strain Hardening, and Ductility

Nanolayered, bimetallic composites are receiving increased attention due to an exceptional combination of strength and thermal stability not possible from their coarse-layered counterparts or constituents alone. Yet, due to their 2D planar, unidirectional arrangement, they are highly anisotropic, which results in limited strain hardening and ductility. Therefore, like many high-performance, ultrastrong materials of our time, they succumb to the usual strength-ductility trade-offs. Here we present the formation of a novel hierarchical microstructure, comprised of crystals consisting of 3D nanolayered α/β–Zr networks. By direct comparison with coarse-layered material of the same chemistry, we show that the unusual hierarchical 3D structure gives rise to high strain hardening, high strength, and high ductility. Using TEM analysis and hysteresis testing, we discovered that the 3D randomly oriented biphase boundaries result in progressively dispersive rather than localized slip with increasing strain. Dislocation activity in the α–Zr lamellae transitions from single slip to multislip and eventually to multimodal slip as strain increases. Furthermore, the diffusive slip-promoting properties of 3D layered networks can potentially invoke simultaneous high strength, strain hardening, and ductility, and reveal a new target in the microstructural design of high performance structural materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Study of interconnect errors, network congestion, and applications characteristics for throttle prediction on a large scale HPC system

Today’s High Performance Computing (HPC) systems contain thousand of nodes which work together to provide performance in the order of petaflops. The performance of these systems depends on various components like processors, memory, and interconnect. Among all, interconnect plays a major role as it glues together all the hardware components in an HPC system. A slow interconnect can impact a scientific application running on multiple processes severely as they rely on fast network messages to communicate and synchronize frequently. Unfortunately, the HPC community lacks a study that explores different interconnect errors, congestion events and applications characteristics on a large-scale HPC system. In our previous work, we process and analyze interconnect data of the Titan supercomputer to develop a thorough understanding of interconnects faults, errors, and congestion events. In this work, we first show how congestion events can impact application performance. We then investigate application characteristics interaction with interconnect errors and network congestion to predict applications encountering congestion with more than 90% accuracy.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Entanglement Traffic Engineering in Quantum Optical Fiber Networks based on High-Dimensional Kerr Optical Frequency Combs

The purpose of the project was to explore the performance of entanglement protocols based on microresonator Kerr optical frequency combs. We have addressed these challenges by developing a rigorous frequency-bin approach that allowed us to determine an explicit steady-state density operator for quantum microcombs below threshold. Our novel approach has allowed us to derived an explicit formula for the density operator on the frequency-bin basis, and to propose a complete description of quantum Kerr combs regardless of the number of sidemodes or loss-induced coupling to the environment. This formalism also allows for the explicit determination of their fidelity, purity, and entropy. These results are expected to permit the exploitation of the full potential of entangled microcombs for quantum technology.

42 ENGINEERING↗