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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

DeepLearnMOR: a deep-learning framework for fluorescence image-based classification of organelle morphology

Abstract The proper biogenesis, morphogenesis, and dynamics of subcellular organelles are essential to their metabolic functions. Conventional techniques for identifying, classifying, and quantifying abnormalities in organelle morphology are largely manual and time-consuming, and require specific expertise. Deep learning has the potential to revolutionize image-based screens by greatly improving their scope, speed, and efficiency. Here, we used transfer learning and a convolutional neural network (CNN) to analyze over 47,000 confocal microscopy images from Arabidopsis wild-type and mutant plants with abnormal division of one of three essential energy organelles: chloroplasts, mitochondria, or peroxisomes. We have built a deep-learning framework, DeepLearnMOR (Deep Learning of the Morphology of Organelles), which can rapidly classify image categories and identify abnormalities in organelle morphology with over 97% accuracy. Feature visualization analysis identified important features used by the CNN to predict morphological abnormalities, and visual clues helped to better understand the decision-making process, thereby validating the reliability and interpretability of the neural network. This framework establishes a foundation for future larger-scale research with broader scopes and greater data set diversity and heterogeneity.

Plant Sciences↗
DOE OSTI2018

A Big Data Analytics Framework for HPC Log Data: Three Case Studies Using the Titan Supercomputer Log

Reliability, availability and serviceability (RAS) logs of high performance computing (HPC) resources, when closely investigated in spatial and temporal dimensions, can provide invaluable information regarding system status, performance, and resource utilization. These data are often generated from multiple logging systems and sensors that cover many components of the system. The analysis of these data for finding persistent temporal and spatial insights faces two main difficulties: the volume of RAS logs makes manual inspection difficult and the unstructured nature and unique properties of log data produced by each subsystem adds another dimension of difficulty in identifying implicit correlation among recorded events. To address these issues, we recently developed a multi-user Big Data analytics framework for HPC log data at Oak Ridge National Laboratory (ORNL). This paper introduces three in-progress data analytics projects that leverage this framework to assess system status, mine event patterns, and study correlations between user applications and system events. We describe the motivation of each project and detail their workflows using three years of log data collected from ORNL's Titan supercomputer.

Park, Byung↗
DOE OSTI2012

NetSim Steer: A Runtime Steering Framework for Network Simulators

This paper presents NetSim-Steer, a runtime steering framework for network simulators. With this framework, users can specify execution constraints for the network protocols and network models. In addition to this, users can implement steering rules to be executed when a constraint is violated. These rules allows users to alter the parameters of the protocols/models during the simulation so that they stay within the boundaries of the constraints.

Network simulation↗
DOE OSTI2026

Minimizing the Electromechanical Stresses in Poloidal Field Coils by Optimizing their Numbers and Locations using FREDA Framework

Poloidal field (PF) and central solenoid (CS) coils play a crucial role in sustaining the equilibrium and preserving the shape of highly confined tokamak plasmas. Ensuring that PF coil current and mechanical stress stay within superconducting and structural limitations is an important check in the design assessment. Minimizing the PF coil currents and mechanical stresses influences reliability, cost, and performance. A free-boundary MHD equilibrium code—FreeGS is employed within the fusion reactor design and assessment (FREDA) whole facility modeling (WFM) framework to construct the plasma equilibrium based on the configuration and currents in the PF coils. Here, we present the capability of the FreeGS code to minimize the currents, forces, and electromagnetic stresses on the PF coils by optimizing their number, sizes, structures, and locations while maintaining an MHD stable plasma configuration with a large confinement factor. The workflow is initialized with a configuration of plasma parameters and coils’ locations from the 0-D tokamak build systems code in the FREDA framework. Then, FreeGS is called to calculate the initial equilibrium at the minimum total current in PF coils. Thereafter, FreeGS’s internal optimizer minimizes the currents and hoop and central forces on the PF coils while maintaining the reference equilibrium. Finally, the input configuration is updated with the optimized parameters for equilibria over the ramp-up phase of a burning-plasma operation. FREDA’s whole facility optimization capability, which includes all magnetic field coil systems, blanket, vacuum vessel (VV), first wall, divertor, etc., is under development and out of the scope for this study.

Hassan, Ehab [ORNL] (ORCID:0000000181060301)↗
DOE OSTI2013

A framework to measure myocardial extracellular volume fraction using dual-phase low dose CT images

Purpose: Myocardial extracellular volume fraction (ECVF) is a surrogate imaging biomarker of diffuse myocardial fibrosis, a hallmark of pathologic ventricular remodeling. Low dose cardiac CT is emerging as a promising modality to detect diffuse interstitial myocardial fibrosis due to its fast acquisition and low radiation; however, the insufficient contrast in the low dose CT images poses great challenge to measure ECVF from the image. Methods: To deal with this difficulty, the authors present a complete ECVF measurement framework including a point-guided myocardial modeling, a deformable model-based myocardium segmentation, nonrigid registration of pre- and post-CT, and ECVF calculation. Results: The proposed method was evaluated on 20 patients by two observers. Compared to the manually delineated reference segmentations, the accuracy of our segmentation in terms of true positive volume fraction (TPVF), false positive volume fraction (FPVF), and average surface distance (ASD), were 92.18% ± 3.52%, 0.31% ± 0.10%, 0.69 ± 0.14 mm, respectively. The interobserver variability measured by concordance correlation coefficient regarding TPVF, FPVF, and ASD were 0.95, 0.90, 0.94, respectively, demonstrating excellent agreement. Bland-Altman method showed 95% limits of agreement between ECVF at CT and ECVF at MR. Conclusions: The proposed framework demonstrates its efficiency, accuracy, and noninvasiveness in ECVF measurement and dramatically advances the ECVF at cardiac CT toward its clinical use.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2023

Operation Optimization using Reinforcement Learning with Integrated Artificial Reasoning Framework

In large and complex systems, operational decision-making requires a systematic analysis with a vast amount of data from both process parameters and component status monitoring. In this paper, we present an integrated artificial reasoning approach for system state transition models that can help operational decision-making with explainable and traceable reasoning. The integrated artificial reasoning framework is a physics-based approach of defining the system structure in a Bayesian network, so we leveraged it in a Markov decision process (MDP) for finding optimal operational solutions. In our proposed framework, the MDP is implemented on a dynamic Bayesian network (DBN), which represents causalities in a system. The multilevel flow modeling was utilized in order to extract these causalities in a more efficient and objective manner. Since multilevel flow modeling is based on the fundamental energy and mass conservation laws, the target system is decomposed into several mass, energy, and information structures, which serve as the basis for a DBN. The MDP consists of the processes of finding a solution for the Bellman equation, which can be derived from the conditional probability equations of the constructed DBN. System operators can capture stochastic system dynamics as multiple subsystem state transitions based on their physical relations and uncertainties coming from the component degradation process or random failures. We analyzed a simplified example system to illustrate finding an optimal operational policy with this approach.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Tsdat: An Open-Source Data Standardization Framework for Marine Energy and Beyond

Many organizations are tasked with the collection and processing of large quantities of data from various measurement devices. Data reported from these sources are often not interoperable with datasets and software used by analysts and other organizations in the same domain, introducing barriers for collaboration on large-scale projects. This poses a particular problem for cross-device comparisons and machine learning applications, which rely on large quantities of data from multiple sources. To address these challenges, the open-source Time-Series Data Pipelines (Tsdat) Python framework was developed by Pacific Northwest National Laboratory, with strategic guidance and direction provided by the National Renewable Energy Laboratory and Sandia National Laboratories to facilitate collaboration and accelerate advancements in the marine energy domain through the development of an open-source ecosystem of tools. This paper will describe the Tsdat framework and the data standards within which it operates. A beta version of Tsdat has been released and is being used by several projects in marine energy, wind energy, and building energy systems.

big data↗
DOE OSTI2010

Metal Organic Framework Research: High Throughput Discovery of Robust Metal Organic Framework for CO2 Capture

IMPACCT Project: LBNL is developing a method for identifying the best metal organic frameworks for use in capturing CO2 from the flue gas of coal-fired power plants. Metal organic frameworks are porous, crystalline compounds that, based on their chemical structure, vary considerably in terms of their capacity to grab hold of passing CO2 molecules and their ability to withstand the harsh conditions found in the gas exhaust of coal-fired power plants. Owing primarily to their high tunability, metal organic frameworks can have an incredibly wide range of different chemical and physical properties, so identifying the best to use for CO2 capture and storage can be a difficult task. LBNL uses high-throughput instrumentation to analyze nearly 100 materials at a time, screening them for the characteristics that optimize their ability to selectively adsorb CO2 from coal exhaust. Their work will identify the most promising frameworks and accelerate their large-scale commercial development to benefit further research into reducing the cost of CO2 capture and storage.

ARPA-E↗
DOE OSTI2014

Methods for associating or dissociating guest materials with a metal organic framework, systems for associating or dissociating guest materials within a series of metal organic frameworks, thermal energy transfer assemblies, and methods for transferring thermal energy

Methods for releasing associated guest materials from a metal organic framework are provided. Methods for associating guest materials with a metal organic framework are also provided. Methods are provided for selectively associating or dissociating guest materials with a metal organic framework. Systems for associating or dissociating guest materials within a series of metal organic frameworks are provided. Thermal energy transfer assemblies are provided. Methods for transferring thermal energy are also provided.

42 ENGINEERING↗
DOE OSTI2016

Methods for associating or dissociating guest materials with a metal organic framework, systems for associating or dissociating guest materials within a series of metal organic frameworks, thermal energy transfer assemblies, and methods for transferring thermal energy

Methods for releasing associated guest materials from a metal organic framework are provided. Methods for associating guest materials with a metal organic framework are also provided. Methods are provided for selectively associating or dissociating guest materials with a metal organic framework. Systems for associating or dissociating guest materials within a series of metal organic frameworks are provided. Thermal energy transfer assemblies are provided. Methods for transferring thermal energy are also provided.

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

Highly C2/C1-Selective Covalent Organic Frameworks Substituted with Azo Groups

A series of covalent organic frameworks substituted with azo groups (AzoCOFs) have been synthesized via imine condensation. The obtained frameworks show crystallinity and high stability. More importantly, the AzoCOFs exhibit exceptionally high ideal adsorption solution theory (IAST) selectivity in adsorption of C 2 H 2 (35–2891) over CH 4 at 273 K and 1 bar, owing to the favorable interactions between azo groups and acetylene molecules. The dependence of the gas adsorption property on pore size and polarity of the frameworks was also studied. Here, the triethylene glycol substituted Tg-AzoCOF shows the highest C 2 H 2 /CH 4 selectivity (IAST selectivity of 2891), which represents the highest reported for all porous materials. The AzoCOFs also exhibit high IAST adsorption selectivity of C 2 H 4 /CH 4 (11–20), C 2 H 6 /CH 4 (15–22), and CO 2 /CH 4 (12–37), which is comparable with most porous materials, thus showing their great potential in gas separation applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Covalent-Organic Frameworks Composed of Rhenium Bipyridine and Metal Porphyrins: Designing Heterobimetallic Frameworks with Two Distinct Metal Sites

The incorporation of homogeneous catalysts for CO 2 reduction into extended frameworks has been a successful strategy for increasing catalyst lifetime and activity, but the effects of the linkers on catalysis are underexplored. In this work, a novel rhenium bipyridine complex was synthesized for the purpose of designing a covalent-organic framework (COF) with both metalloporphyrin and metal bipyridine moieties. Investigation of the rhenium complex as a homogeneous catalyst shows a faradaic efficiency of 81(8)% for the electrocatalytic conversion of CO 2 to CO upon the addition of methanol as the proton source. Treatment of the rhenium complex with tetra(4-aminophenyl)porphyrin under Schiff base conditions produces the desired COF, as indicated by powder X-ray diffraction (PXRD) studies. Metalation of the porphyrins was accomplished through postsynthetic modification with CoCl 2 and FeCl 3 metal precursors. The retention of the PXRD peaks and appearance of new Co and Fe peaks in the corresponding X-ray photoelectron spectroscopy spectra suggest the successful incorporation of a secondary metal site into the framework. Cyclic voltammetry measurements display increases in current densities when the atmosphere is changed from N 2 to CO 2 . Finally, controlled potential electrolyses show that the cobalt-postmetalated COF has the highest activity toward CO 2 reduction, reaching a faradaic efficiency of 18(2)%.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Magnetic ordering through itinerant ferromagnetism in a metal-organic framework

In this report, the materials that combine magnetic order with other desirable physical attributes could find transformative applications in spintronics, quantum sensing, low-density magnets and gas separations. Among potential multifunctional magnetic materials, metal-organic frameworks, in particular, bear structures that offer intrinsic porosity, vast chemical and structural programmability, and the tunability of electronic properties. Nevertheless, magnetic order within metal-organic frameworks has generally been limited to low temperatures, owing largely to challenges in creating a strong magnetic exchange. Here we employ the phenomenon of itinerant ferromagnetism to realize magnetic ordering at T C = 225 K in a mixed-valence chromium(II/III) triazolate compound, which represents the highest ferromagnetic ordering temperature yet observed in a metal-organic framework. The itinerant ferromagnetism proceeds through a double-exchange mechanism, which results in a barrierless charge transport below the Curie temperature and a large negative magnetoresistance of 23% at 5 K. These observations suggest applications for double-exchange-based coordination solids in the emergent fields of magnetoelectrics and spintronics.

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

Nanoconfinement of Molecular Magnesium Borohydride Captured in a Bipyridine-Functionalized Metal-Organic Framework

The lower limit of metal hydride nanoconfinement is demonstrated through the coordination of a molecular hydride species to binding sites inside the pores of a metal-organic framework (MOF). Magnesium borohydride, which has a high hydrogen capacity, is incorporated into the pores of UiO-67bpy (Zr6O4(OH)4(bpydc)6 with bpydc2- = 2,2'-bipyridine-5,5'- dicarboxylate) by solvent impregnation. The MOF retained its long-range order, and transmission electron microscopy and elemental mapping confirmed the retention of the crystal morphology and revealed a homogeneous distribution of the hydride within the MOF host. Notably, the B-, N-, and Mg-edge XAS data confirm the coordination of Mg(II) to the N atoms of the chelating bipyridine groups. In situ 11B MAS NMR studies helped elucidate the reaction mechanism and revealed that complete hydrogen release from Mg(BH4)2 occurs as low as 200 °C. Sieverts and thermogravimetric measurements indicate an increase in the rate of hydrogen release, with the onset of hydrogen desorption as low as 120 °C, which is approximately 150 °C lower than that of the bulk material. Furthermore, density functional theory calculations support the improved dehydrogenation properties and confirm the drastically lower activation energy for B-H bond dissociation.

Nanoconfinement, Metal Hydrides, Metal-Organic Fra↗
DOE OSTI2018

An Electron/Ion Dual‐Conductive Alloy Framework for High‐Rate and High‐Capacity Solid‐State Lithium‐Metal Batteries

Abstract The solid‐state Li battery is a promising energy‐storage system that is both safe and features a high energy density. A main obstacle to its application is the poor interface contact between the solid electrodes and the ceramic electrolyte. Surface treatment methods have been proposed to improve the interface of the ceramic electrolytes, but they are generally limited to low‐capacity or short‐term cycling. Herein, an electron/ion dual‐conductive solid framework is proposed by partially dealloying the Li–Mg alloy anode on a garnet‐type solid‐state electrolyte. The Li–Mg alloy framework serves as a solid electron/ion dual‐conductive Li host during cell cycling, in which the Li metal can cycle as a Li‐rich or Li‐deficient alloy anode, free from interface deterioration or volume collapse. Thus, the capacity, current density, and cycle life of the solid Li anode are improved. The cycle capability of this solid anode is demonstrated by cycling for 500 h at 1 mA cm −2 , followed by another 500 h at 2 mA cm −2 without short‐circuiting, realizing a record high cumulative capacity of 750 mA h cm −2 for garnet‐type all‐solid‐state Li batteries. This alloy framework with electron/ion dual‐conductive pathways creates the possibility to realize high‐energy solid‐state Li batteries with extended lifespans.

Yang, Chunpeng↗