Search NASA⌕ Search

SEARCH · Search NASA

Results for “research work”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Data Federation Challenges in Remote Near-Real-Time Fusion Experiment Data Processing

Fusion energy experiments and simulations provide critical information needed to plan future fusion reactors. As next-generation devices like ITER move toward long-pulse experiments, analyses, including AI and ML, should be performed in a wide range of time and computing constraints, from near-real-time constraints, between-shot analysis, and to campaign-wide long-term analysis. However, the data volume, velocity, and variety make it extremely challenging for analyses using only local computational resources. Researchers need the ability to compose and execute workflows spanning edge resources to large-scale high-performance computing facilities.We present Delta, a system to address data analysis challenges, including AI/ML, in fusion science, by leveraging the ADIOS I/O library and middleware, to support executing science workflows over the wide area network for near-real-time streaming. We discuss the data federation challenges in performing remote workflows, focusing on on-going research work in (1) managing, reducing, and streaming data to minimize I/O and data movement overheads, (2) decompressing and reorganizing data for analysis, and (3) executing workflows for automated data analysis. We introduce examples for deep-learning based data analysis for the fusion domain and demonstrate how we use Delta to construct end-to-end workflows for a fusion device in Korea, connecting a remote DOE facility in the USA. The capability demonstrated by this project is the basis for improving the state of the art for near-real-time data federation amongst remote facilities.

Choi, Jong Youl↗
DOE OSTI2023

ProvSec: Open Cybersecurity System Provenance Analysis Benchmark Dataset with Labels

System provenance forensic analysis has been studied by a large body of research work. This area needs fine granularity data such as system calls along with event fields to track the dependencies of events. While prior work on security datasets has been proposed, we found a useful dataset of realistic attacks and details that are needed for high-quality provenance tracking is lacking. We created a new dataset of eleven vulnerable cases for system forensic analysis. It includes the full details of system calls including syscall parameters. Realistic attack scenarios with real software vulnerabilities and exploits are used. For each case, we created two sets of benign and adversary scenarios which are manually labeled for supervised machine-learning analysis. In addition, we present an algorithm to improve the data quality in the system provenance forensic analysis. We demonstrate the details of the dataset events and dependency analysis of our dataset cases.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Special Issue from the Advances in Fossil Energy R&D topical sessions held at the 2019 American Institute of Chemical Engineers Annual Fall Meeting

This special issue entitled “Catalysis for Energy Related Activities” represents a collection of research works presented during the Advances in Fossil Energy R&D topical sessions at the 2019 American Institute of Chemical Engineers (AIChE) Annual Meeting in Orlando, Florida November 10–15, 2019.

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

Robust optimization of flexible diafiltration systems for critical mineral separations

This paper provides major contributions in expanding the literature for membrane process design with critical mineral recovery applications and showcasing the importance of robust design techniques for reducing risks of underperformance in such systems. Here, a membrane process flowsheet featuring PrOMMiS membrane models for recovering lithium/cobalt from spent batteries is showcased, uncertainty in membrane sieving and localized fouling are considered, and robust designs are obtained using the PyROS toolset. This paper is intended for a general audience of researchers working in critical minerals, membranes, and optimization related areas.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Investigation of methane and ethane pyrolysis with highly active and durable iron-alumina catalyst to produce hydrogen and valuable nano carbons: Continuous fluidized bed tests and reaction rate analysis

The goal of this research work was to evaluate a novel iron-alumina catalyst for methane and ethane pyrolysis with high conversion rates to H 2 with a long life time to address two major issues reported with previous catalysts. Fluidized bed tests demonstrated continuous hydrogen production while collecting carbon containing fines. During the 230 h fluid bed test the methane conversion rate to hydrogen at 700 °C remained above 80% for 160 h while creating valuable nano carbons. Similarly high catalyst lifetimes with high methane conversions have not been reported before. Ethane was more active than methane for pyrolysis with 100% conversion to H 2 . Transmission electron microscopy and Raman analysis of the carbon showed single and multiwall nanotubes and conglomerate nano-fibers. Ethane did not impact the allotrope of carbon formed. TGA was used to create a data array that was used for kinetic analysis and reaction model parametric regressions. Ethane had a higher rate of pyrolysis that was 2.3–2.8 times that of methane. Ethane pyrolysis was found to be more sensitive to temperature with a higher activation energy of 62 kJ/mol as compared to methane at 43 kJ/mol. The frequency factor, A i , was significantly higher for ethane at 0.73 [[kmol/m 3 -sec]/[N/m2] n ] compared to 0.03 for methane on the same basis. Both gases had a functional partial pressure order dependence of ~0.6 based on the regression analysis.

08 HYDROGEN↗
DOE OSTI2022

Electronic, magnetic, and structural properties of CrMnSb 0.5 Si 0.5

Half-metallic Heusler compounds are among the most actively studied materials for applications in spin-based devices. Largely, this is due to their higher Curie temperature compared with the other half-metallic compounds, and relative ease of fabrication. Here we theoretically study one such Heusler alloy CrMnSb 0.5 Si 0.5 . In particular, we demonstrate a potential stability of this compound by estimating its formation energy, its half-metallic electronic structure (stable under a considered range of biaxial strain), and ferrimagnetic alignment. The calculated Curie temperature of this material is 787 K, much higher than room temperature. At the same time, we have shown that in thin-film geometry the spin-polarization of this material is strongly reduced due to the emergence of surface states in the minority-spin energy gap. In addition, one of the considered termination surfaces is thermodynamically unstable, while the other is stable. Here, the presented results may be useful for researchers working on practical applications in the field of spintronics.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Editorial for Multiscale & Multifield Coupling in Geomechanics

We are delighted to serve as guest editors for this special issue in the Journal of Rock Mechanics and Geotechnical Engineering. The purpose of this special issue is dedicated to gathering the latest research work on Multiscale & Multifield Coupling in Geomechanics, where we delve into the intricate interplay of various fields and scales that govern the behavior of geomaterials. In total, 30 manuscripts from USA, China, UK, Germany, Canada, India and United Arab Emirates are selected to be included in this issue.

58 GEOSCIENCES↗
DOE OSTI2023

Desiccants enabling energy-efficient buildings: A review

Buildings account for about 39% of the total energy consumption in the United States. Developing highly energy-efficient and environmentally friendly systems that are either actively or passively integrated into buildings plays a crucial role in decarbonizing the building sector. Among various technologies, desiccant-based energy systems have received particular attention in recent years due to their unique advantages, such as being thermally driven using low-grade waste or solar energies and being reliable over a wide range of operating ranges. Extensive research efforts have been exerted on desiccant-enabled technologies at both material and system levels aiming to increase their performance and achieve high technological readiness levels. The present review paper comprehensively discusses research works made at the system level. It overviews desiccant-based air conditioning systems, desiccant-based humidity pumps, desiccant-based thermal energy storage systems, and desiccant-based appliances. The study identifies challenges and opportunities to accelerate the commercialization of desiccant-enabled technologies. It is found that desiccant materials offer great promise to improve energy efficiency and functionality of future buildings through decoupling the latent and sensible cooling loads in air conditioning systems, humidity pumps integrated into building facades, and next-generation appliances. However, commercial viability and widespread acceptance of desiccant-based systems have been hampered by several major obstacles, including liquid and air flow mal-distribution and inferior thermo-physical properties of desiccant materials resulting in low ab/adsorption and regeneration rates and bulky/costly systems.

25 ENERGY STORAGE↗
DOE OSTI2025

Tutorial: Machine-Learning-Based CREASE-2D Analysis of 2D SAXS Profiles to Characterize Anisotropic Nanostructures in Soft Materials

We present a tutorial to guide users on how to extend the Computational Reverse Engineering Analysis of Scattering Experiments-2D (CREASE-2D) framework to interpret their experimental two-dimensional small-angle scattering (SAS) data from soft materials (e.g., polymers, peptide amphiphiles, biomolecular fibrils). Unlike most traditional SAS analysis approaches, which typically rely on azimuthally averaged onedimensional (1D) profiles, CREASE-2D utilizes the complete 2D scattering profile to reveal information about anisotropy in the structure. In past applications, CREASE has provided insights into complex structural features, including the cross-sectional shapes of assembled nanostructures and dispersity in these features, which are difficult to discern with existing analytical models. While (1D- ) CREASE has been applied to SANS and SAXS data, this tutorial shares the steps for implementing CREASE-2D using an example of a dipeptide solution system, for which we have SAXS data. We present details for these steps involved in using CREASE-2D to interpret SAXS profiles: how to preprocess SAXS data, define relevant structural features, generate three-dimensional real-space structures for specific values of these features, train a machine learning (ML) surrogate model to predict scattering profiles for given structural features, and optimize these features using genetic algorithms (GA). Then, we use these steps to interpret complex 2DSAXS data collected from dipeptide solutions that, in microscopy images, exhibit nanoscale structures that could be elliptical tubes/ flat tapes/cylinders or a combination of these cross sections. Open-source codes, computational hardware, and software requirements, as well as the strengths and limitations of this protocol, are also presented. We expect researchers working with (soft) biomaterials, peptide amphiphiles, amphiphilic polymer solutions, polymer nanocomposites, and blends of particles/polymers will find this CREASE-2D method and this tutorial of use.

CREASE↗
DOE OSTI2021

Expanding the application of a UV-visible reporter for transient gene expression and stable transformation in plants

Abstract Green fluorescent protein (GFP) has been widely used for monitoring gene expression and protein localization in diverse organisms. However, highly sensitive imaging equipment, like fluorescence microscope, is usually required for the visualization of GFP, limitings its application to fixed locations in samples. A reporter that can be visualized in real-time regardless the shape, size and location of the target samples will increase the flexibility and efficiency of research work. Here, we report the application of a GFP-like protein, called eYGFPuv, in both transient expression and stable transformation, in two herbaceous plant species ( Arabidopsis and tobacco) and two woody plant species (poplar and citrus). We observed bright fluorescence under UV light in all of the four plant species without any effects on plant growth or development. eYGFPuv was shown to be effective for imaging transient expression in leaf and root tissues. With a focus on in vitro transformation, we demonstrated that the transgenic events expressing 1x eYGFPuv could be easily identified visually during the callus stage and the shoot stage, enabling early and efficient selection of transformants. Furthermore, whole-plant level visualization of eYGFPuv revealed its ubiquitous stability in transgenic plants. In addition, our transformation experiments showed that eYGFPuv can also be used to select transgenic plants without antibiotics. This work demonstrates the feasibility of utilizing 1x eYGFPuv in studies of gene expression and plant transformation in diverse plants.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Effect of the grain arrangements on the thermal stability of polycrystalline nickel-rich lithium-based battery cathodes

One of the most challenging aspects of developing high-energy lithium-based batteries is the structural and (electro)chemical stability of Ni-rich active cathode materials at thermally-abused and prolonged cell cycling conditions. Here, we report in situ physicochemical characterizations to improve the fundamental understanding of the degradation mechanism of charged polycrystalline Ni-rich cathodes at elevated temperatures (e.g., ≥ 40 °C). Using multiple microscopy, scattering, thermal, and electrochemical probes, we decouple the major contributors for the thermal instability from intertwined factors. Our research work demonstrates that the grain microstructures play an essential role in the thermal stability of polycrystalline lithium-based positive battery electrodes. We also show that the oxygen release, a crucial process during battery thermal runaway, can be regulated by engineering grain arrangements. Furthermore, the grain arrangements can also modulate the macroscopic crystallographic transformation pattern and oxygen diffusion length in layered oxide cathode materials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Machine-learning-assisted material discovery of oxygen-rich highly porous carbon active materials for aqueous supercapacitors

Abstract Porous carbons are the active materials of choice for supercapacitor applications because of their power capability, long-term cycle stability, and wide operating temperatures. However, the development of carbon active materials with improved physicochemical and electrochemical properties is generally carried out via time-consuming and cost-ineffective experimental processes. In this regard, machine-learning technology provides a data-driven approach to examine previously reported research works to find the critical features for developing ideal carbon materials for supercapacitors. Here, we report the design of a machine-learning-derived activation strategy that uses sodium amide and cross-linked polymer precursors to synthesize highly porous carbons (i.e., with specific surface areas > 4000 m 2 /g). Tuning the pore size and oxygen content of the carbonaceous materials, we report a highly porous carbon-base electrode with 0.7 mg/cm 2 of electrode mass loading that exhibits a high specific capacitance of 610 F/g in 1 M H 2 SO 4 . This result approaches the specific capacitance of a porous carbon electrode predicted by the machine learning approach. We also investigate the charge storage mechanism and electrolyte transport properties via step potential electrochemical spectroscopy and quasielastic neutron scattering measurements.

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

Simulations in the era of exascale computing

Exascale computers — supercomputers that can perform 10 18 floating point operations per second — started coming online in 2022: in the United States, Frontier launched as the first public exascale supercomputer and Aurora is due to open soon; OceanLight and Tianhe-3 are operational in China; and JUPITER is due to launch in 2023 in Europe. Supercomputers offer unprecedented opportunities for modelling complex materials. In this Viewpoint, five researchers working on different types of materials discuss the most promising directions in computational materials science.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Materials for Chiral Light Control

Solution-processable semiconductors based on small molecules, polymers or halide perovskites combine sustainable manufacturing with exceptional optoelectronic properties that can be chemically tailored to achieve flexible and highly efficient optoelectronic and photonic devices. A new exciting research direction is the study of the influence of chirality on light-matter interactions in these soft materials and its exploitation for the simultaneous control of charge, spin and light. In this Viewpoint, researchers working on different types of chiral semiconductors discuss the most interesting directions in this rapidly expanding field.

chiral↗
DOE OSTI2021

Design new epoxy nanocomposite coatings based on metal vanadium oxy-phosphate M 0.5 VOPO 4 for anti-corrosion applications

Epoxy nanocomposite coatings are an essential way to protect petroleum storage tanks from corrosion. For this purpose, the new nanocomposite epoxy coatings (P-M/epoxy composites) have been successfully designed. The P-M/epoxy composites are based on the metal vanadium oxy-phosphate M 0.5 VOPO 4 (where M = Mg, Ni, and Zn). The function of P-M/epoxy composites as anti-corrosion coatings was explored using electrochemical and mechanical tests. Using electrochemical impedance spectroscopy (EIS), it has been noticed that the pore resistance and polarization resistance of the P-M/epoxy composites remain higher as compared to the neat epoxy. The P-M/epoxy composites have the greatest impact on the cathodic dis-bonded area and water absorption. Besides, P-M/epoxy composites exhibit a very high order of mechanical properties. Further, Mg 0.5 VOPO 4 has the greatest effect on the anti-corrosion properties of epoxy coating followed by Zn 0.5 VOPO 4 and Ni 0.5 VOPO 4 . All these properties lead to developing effective anti-corrosion coatings. Thus, the net result from this research work is highly promising and provides a potential for future works on the anti-corrosion coating.

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

Advances in metal–organic framework-based hydrogel materials: preparation, properties and applications

Although metal–organic frameworks (MOFs) with intriguing physiochemical properties have recently attracted increasing attention of researchers, MOFs have not adequately achieved various applications due to their instability and unsatisfactory processability. Hence, MOF-based composites as well as structurally novel MOFs have been established to solve this challenge. Recently, some efforts have been made for the development of MOF-based hydrogels. They exhibit excellent properties compared to initial MOFs in many ways (e.g., mechanical strength, absorption capacity and total pore volume). In this review, the up-to-date research progress of MOF-based hydrogels will be briefly summarized. Here, we mainly focus on expounding the classification of MOF-based hydrogels and their related synergistic effects. As to details, we will provide a conspectus of laconic and latest approaches for the synthesis of MOF-based hydrogels, focusing on composite systems, mechanism research, and stability. In addition, the applications of MOF-based hydrogels have been widely discussed, particularly in the environmental, energy and medical aspects. It is hoped that the detailed description of this review can help researchers working on MOF-based hydrogels to develop more novel composite materials and investigate their wider application.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Guest Editorial: Advanced Data-Analytics for Power System Operation, Control, and Enhanced Situational Awareness

Along with the smart grid development, modern power systems are entering a ‘data-intensive’ era. A vast volume of data from power grids is being collected through advanced sensing and communication technologies, such as smart metering data, phasor measurement data, as well as meteorological data (e.g., wind speed and solar irradiance) related to renewable power generation. Such data contains comprehensive information about the power system covering equipment's health status, power grid's static and dynamic characteristics, renewable power generation, customers’ electricity usage pattern, etc. Therefore, advanced data-analytics techniques are needed to convert such data to knowledge for practical applications. In line with the trend of widespread data-driven applications in power systems, this Special Issue aims to present state-of-the-art research works on advanced data-analytics for power system's operation, control, and situational awareness. There are in total twenty-six papers accepted for publication in this Special Issue through careful peer reviews and revisions. Under the overarching theme of data-driven applications in power systems, the selected papers are broadly categorised into five topics. The summary of every topic is given below. You are, however, strongly encouraged to read the full paper if interested.

Xu, Yan↗