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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Quantifying redox heterogeneity in single-crystalline LiCoO 2 cathode particles

Active cathode particles are fundamental architectural units for the composite electrode of Li-ion batteries. The microstructure of the particles has a profound impact on their behavior and, consequently, on the cell-level electrochemical performance. LiCoO 2 (LCO, a dominant cathode material) is often in the form of well-shaped particles, a few micrometres in size, with good crystallinity. In contrast to secondary particles (an agglomeration of many fine primary grains), which are the other common form of battery particles populated with structural and chemical defects, it is often anticipated that good particle crystallinity leads to superior mechanical robustness and suppressed charge heterogeneity. Yet, sub-particle level charge inhomogeneity in LCO particles has been widely reported in the literature, posing a frontier challenge in this field. Herein, this topic is revisited and it is demonstrated that X-ray absorption spectra on single-crystalline particles with highly anisotropic lattice structures are sensitive to the polarization configuration of the incident X-rays, causing some degree of ambiguity in analyzing the local spectroscopic fingerprint. To tackle this issue, a methodology is developed that extracts the white-line peak energy in the X-ray absorption near-edge structure spectra as a key data attribute for representing the local state of charge in the LCO crystal. This method demonstrates significantly improved accuracy and reveals the mesoscale chemical complexity in LCO particles with better fidelity. In addition to the implications on the importance of particle engineering for LCO cathodes, the method developed herein also has significant impact on spectro-microscopic studies of single-crystalline materials at synchrotron facilities, which is broadly applicable to a wide range of scientific disciplines well beyond battery research.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Automatic 3D image registration for nano-resolution chemical mapping using synchrotron spectro-tomography

Nano-resolution synchrotron X-ray spectro-tomography has been demonstrated as a powerful tool for probing the three-dimensional (3D) structural and chemical heterogeneity of a sample. By reconstructing a number of tomographic data sets recorded at different X-ray energy levels, the energy-dependent intensity variation in every given voxel fingerprints the corresponding local chemistry. The resolution and accuracy of this method, however, could be jeopardized by non-ideal experimental conditions, e.g. instability in the hardware system and/or in the sample itself. Herein is presented one such case, in which unanticipated sample deformation severely degrades the data quality. Here, to address this issue, an automatic 3D image registration method is implemented to evaluate and correct this effect. The method allows the redox heterogeneity in partially delithiated Li x Ta 0.3 Mn 0.4 O 2 battery cathode particles to be revealed with significantly improved fidelity.

3D image registration↗
DOE OSTI2022

ROI-Finder : machine learning to guide region-of-interest scanning for X-ray fluorescence microscopy

The microscopy research at the Bionanoprobe (currently at beamline 9-ID and later 2-ID after APS-U) of Argonne National Laboratory focuses on applying synchrotron X-ray fluorescence (XRF) techniques to obtain trace elemental mappings of cryogenic biological samples to gain insights about their role in critical biological activities. The elemental mappings and the morphological aspects of the biological samples, in this instance, the bacterium Escherichia coli ( E. Coli ), also serve as label-free biological fingerprints to identify E. coli cells that have been treated differently. The key limitations of achieving good identification performance are the extraction of cells from raw XRF measurements via binary conversion, definition of features, noise floor and proportion of cells treated differently in the measurement. Automating cell extraction from raw XRF measurements across different types of chemical treatment and the implementation of machine-learning models to distinguish cells from the background and their differing treatments are described. Principal components are calculated from domain knowledge specific features and clustered to distinguish healthy and poisoned cells from the background without manual annotation. The cells are ranked via fuzzy clustering to recommend regions of interest for automated experimentation. The effects of dwell time and the amount of data required on the usability of the software are also discussed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Fourfold alkyl wrapping of a copper(II) porphyrin thwarts macrocycle π–π stacking in a compact supramolecular package

Porphyrins are valuable constituents in optoelectronic, catalytic, and other applications, yet control of intermolecular π–π stacking is invariably essential to attain the desired properties. Superstructures built onto the porphyrin, often via meso -aryl groups, can afford facial encumbrance that suppresses π–π stacking, although some molecular designs have provided insufficient facial coverage and many have entailed cumbersome syntheses. In this study, a copper(II) porphyrin bearing four meso substituents, namely, {10,20-bis[2,6-bis(octyloxy)phenyl]-5,15-dibromoporphinato}copper(II), [Cu(C 64 H 82 Br 2 N 4 O 4 )], was prepared by metalation of the corresponding free-base porphyrin and was characterized by single-crystal X-ray diffraction. The crystal structure reveals a dihedral angle of 111.1 (2)° for the plane of the meso -aryl group relative to the plane of the porphyrin, with both aryl groups tilted in the same direction. Each of the four octyloxy groups exhibits a gauche conformation for the –OCH 2 CH 2 – unit but is extended with four or five anti (–CH 2 CH 2 –/H) conformations thereafter, causing each octyl group to span the dimension of the macrocycle. In a global frame of reference where the two Br atoms define the north/south poles and the two aryl groups are at antipodes on the equator, two octyl groups of one aryl unit project over the northern hemisphere (covering pyrroles A and B ), whereas those of the other aryl unit project over the southern hemisphere (covering pyrroles C and D ). Together, the four octyl groups ensheath the two faces of the porphyrin in a self-wrapped assembly. The closest approach of the Cu atom to an octyl methylene C atom (position 6) is 3.5817 (18) Å, the mean separations of neighboring porphyrin planes are 8.059 (4) and 4.693 (8) Å along the a and c axes, respectively, and the center-to-center distances between the Cu atoms of neighboring porphyrins are 10.2725 (4), 12.2540 (6), and 12.7472 (6) Å along the a , b , and c axes, respectively. The Hirshfeld surface analysis and two-dimensional (2D) fingerprint plots provide information concerning contact interactions in the supramolecular assembly of the solid crystal.

Chemistry↗
DOE OSTI2015

Characterization of melted fuel by neutron resonance spectroscopy

Neutrons can be used as a tool to study properties of materials and objects. An evolving activity in this field focusses on neutron induced reaction cross sections. The probability that a neutron interacts with nuclei strongly depends on the energy of the neutron. The cross sections reveal the presence of resonance structures, the energy and width of which are isotope specific. As such, these resonance structures can be used as fingerprints to determine the elemental and isotopic composition of materials and objects. They are the basis of two analytical methods which have been developed at Institute for Reference Materials and Measurements of the European Commission's Joint Research Centre (EC-JRC-IRMM): Neutron Resonance Capture Analysis (NRCA) and Neutron Resonance Transmission Analysis (NRTA). The first technique is based on the detection of gamma rays emitted during a neutron capture reaction in the sample being studied; the latter determines the fraction of neutrons transmitted through a sample positioned in a neutron beam. In the past both techniques have been applied to determine the composition of archaeological objects and to characterize nuclear reference materials. More recently a combination of NRTA and NRCA is being studied as a non-destructive method to determine the heavy metal content of particle-like debris of melted fuel that is formed in severe nuclear accidents such as the one which occurred at the Fukushima Daiichi nuclear power plant in Japan. This study is part of a collaboration between the Japan Atomic Energy Agency (JAEA) and ECJRC- IRMM and is a spin-off from the core activity of IRMM, i.e. the production of nuclear data for nuclear technology applications. This contribution focusses on a newly developed NRTA measurement station that has been set up recently at one of the flight paths of the neutron time-of-flight facility GELINA at the EC-JRC-IRMM. The basic principles of NRTA and first results of measurements at the new set up will be discussed. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Optimizing FPGA-based Accelerator Design for Large-Scale Molecular Similarity Search (Special Session Paper)

Molecular similarity search has been widely used in drug discovery to rapidly identify structurally similar compounds from large molecular databases. With the increasing size of chemical libraries, there is growing interest in the efficient ac- celeration of large-scale similarity search. Existing works mainly focus on CPU and GPU to accelerate the computation of Tatimoto coefficient in measuring the pairwise similarity between different molecular fingerprints. In this paper, we propose and optimize an FPGA-based accelerator design on exhaustive and approximate search algorithms. On exhaustive search using BitBound & fold- ing, we analyze the similarity cutoff and folding level relationship with search speedup and accuracy, and propose a scalable on- the-fly query engine on FPGAs to reduce the resource utilization and pipeline interval. We achieve a 450 million compounds-per- second processing throughput for a single query engine. On approximate search using hierarchical navigable small world (HNSW), a popular algorithm with high recall and query speed, we propose an FPGA-based graph traversal engine to utilize high throughput register array based priority queue and fine- grained distance calculation engine to increase the processing capability. Experimental results show that the proposed FPGA- based HNSW implementation achieves a 35× speedup than existing works on CPU. To the best of our knowledge, our FPGA- based implementation is the first attempt to accelerate molecular similarity search on FPGA and has the highest performance among existing approaches.

Peng, Hongwu↗
DOE OSTI2021

Digital data provenance for the power grid based on a Keyless Infrastructure Security Solution

In this work a data provenance system for grid-oriented applications is presented. The proposed Keyless Infrastructure Security Solution (KISS) provides mechanisms to store and maintain digital data fingerprints that can later be used to validate and assert data provenance using a time-based, hash tree mechanism. The developed solution has been designed to satisfy the stringent requirements of the modern power grid including execution time and storage necessities. Its applicability has been tested using a lab-scale, proof-of-concept deployment that secures an energy management system against the attack sequence observed on the 2016 Ukrainian power grid cyberattack. The results demonstrate a strong potential for enabling data provenance in a wide array of applications, including speed-sensitive applications such as those found in control room environments.

Sebastian Cardenas, David J.↗
DOE OSTI2024

Beyond the Bridge: Contention-Based Covert and Side Channel Attacks on Multi-GPU Interconnect

Recently, high-speed interconnects like NVLink have become a standard integration in modern multi-GPU systems, serving as a crucial bridge between CPUs and GPUs. This study highlights the vulnerability of multi-GPU systems to covert and side-channel attacks arising from congestion on these interconnects. An adversary, operating without special permissions, can extract private information about a victim's activities by monitoring NVLink congestion. Specifically, we leverage this insight to develop a covert channel attack across two GPUs, achieving a respectable bandwidth of 33 Kbps. Additionally, we introduce a side-channel attack that allows attackers to fingerprint applications on a remote GPU by probing the shared NVLink interconnect. We underscore the urgent nature of the threats posed by these attacks and advocate for heightened awareness within both industry and academia to implement multi-GPU interconnects with enhanced security measures.

Zhang, Yicheng↗
DOE OSTI2013

Tools for Understanding Identity

Identity attribution and enrichment is critical to many aspects of law-enforcement and intelligence gathering; this identity typically spans a number of domains in the natural-world such as biographic information (factual information – e.g. names, addresses), biometric information (e.g. fingerprints) and psychological information. In addition to these natural-world projections of identity, identity elements are projected in the cyber-world. Conversely, undesirable elements may use similar techniques to target individuals for spear-phishing attacks (or worse), and potential targets or their organizations may want to determine how to minimize the attack surface exposed. Our research has been exploring the construction of a mathematical model for identity that supports such holistic identities. The model captures the ways in which an identity is constructed through a combination of data elements (e.g. a username on a forum, an address, a telephone number). Some of these elements may allow new characteristics to be inferred, hence enriching the holistic view of the identity. An example use-case would be the inference of real names from usernames, the ‘path’ created by inferring new elements of identity is highlighted in the ‘critical information’ panel. Individual attribution exercises can be understood as paths through a number of elements. Intuitively the entire realizable ‘capability’ can be modeled as a directed graph, where the elements are nodes and the inferences are represented by links connecting one or more antecedents with a conclusion. The model can be operationalized with two levels of tool support described in this paper, the first is a working prototype, the second is expected to reach prototype by July 2013: Understanding the Model The tool allows a user to easily determine, given a particular set of inferences and attributes, which elements or inferences are of most value to an investigator (or an attacker). The tool is also able to take into account the difficulty of the inferences, allowing the user to consider different scenarios depending on the perceived resources of the attacker, or to prioritize lines of investigation. It also has a number of interesting visualizations that are designed to aid the user in understanding the model. The tool works by considering the inferences as a graph and runs various graph-theoretic algorithms, with some novel adaptations, in order to deduce various properties. Using the Model To help investigators exploit the model to perform identity attribution, we have developed the Identity Map visualization. For a user-provided set of known starting elements and a set of desired target elements for a given identity, the Identity Map generates investigative workflows as paths through the model. Each path consists of a series of elements and inferences between them that connect the input and output elements. Each path also has an associated confidence level that estimates the reliability of the resulting attribution. Identity Map can help investigators understand the possible ways to make an identification decision and guide them toward the data-collection or analysis steps required to reach that decision.

Creese, Sadie↗
DOE OSTI2015

Standoff Human Identification Using Body Shape

The ability to identify individuals is a key component of maintaining safety and security in public spaces and around critical infrastructure. Monitoring an open space is challenging because individuals must be identified and re-identified from a standoff distance nonintrusively, making methods like fingerprinting and even facial recognition impractical. We propose using body shape features as a means for identification from standoff sensing, either complementing other identifiers or as an alternative. An important challenge in monitoring open spaces is reconstructing identifying features when only a partial observation is available, because of the view-angle limitations and occlusion or subject pose changes. To address this challenge, we investigated the minimum number of features required for a high probability of correct identification, and we developed models for predicting a key body feature—height—from a limited set of observed features. We found that any set of nine randomly selected body measurements was sufficient to correctly identify an individual in a dataset of 4426 subjects. For predicting height, anthropometric measures were investigated for correlation with height. Their correlation coefficients and associated linear models were reported. These results—a sufficient number of features for identification and height prediction from a single feature—contribute to developing systems for standoff identification when views of a subject are limited.

Matzner, Shari↗
DOE OSTI2018

Exploiting Spatial Signatures of Power ENF Signal for Measurement Source Authentication

Electric Network Frequency (ENF) signals are the signatures of power systems that are either directly recorded from the power outlets or extracted from multimedia recordings near the electrical activities. Variations of ENF signals collected at different locations possess local environmental characteristics, which can be used as a potential fingerprint for authenticating measurements' source information. Within this paper is proposed a computational intelligence-based framework to recognize the source locations of power ENF signals within a distribution network in the US. To be more specific, a set of informative location-sensitive signatures from ENF measurements are initially extract with such measurements representative of local grid characteristics. Then these distinctive location-dependent signatures are further fed into a data mining algorithm yielding the “source-of-origin” of ENF measurements. Experimental results using ENF data at multiple intra-grid locations have validated the proposed methodology.

CUI, YI↗
DOE OSTI2022

Precoder Design for Physical-Layer Security and Authentication in Massive MIMO UAV Communications

Supporting reliable and seamless wireless connectivity for unmanned aerial vehicles (UAVs) has recently become a critical requirement to enable various different use cases of UAVs. Due to their widespread deployment footprint, cellular networks can support beyond visual line of sight (BVLOS) communications for UAVs. In this paper, we consider cellular connected UAVs (C-UAVs) that are served by massive multiple input-multiple-output (MIMO) links to extend coverage range, while also improving physical layer security and authentication. Here, we consider Rician channel and propose a novel linear precoder design for transmitting data and artificial noise (AN). We derive the closed-form expression of the ergodic secrecy rate of CUAVs for both conventional and proposed precoder designs. In addition, we obtain the optimal power splitting factor that divides the power between data and AN by asymptotic analysis. Then, we apply the proposed precoder design in the fingerprint embedding authentication framework, where the goal is to minimize the probability of detection of the authentication tag at an eavesdropper. In simulation results, we show the superiority of the proposed precoder in both secrecy rate and the authentication probability considering moderate and large number of antenna massive MIMO scenarios.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

Indoor Wireless Localization of Uncooperative Sources Using a Ray Tracing Model

Indoor geolocation of radio frequency (RF) trans- mitters is challenging due to site-specific multipath effects, especially when the sources are uncooperative. A source being uncooperative means that a-priori the transmit time, location, and power are unknown. It is proposed to use a site-specific ray tracing model to generate realistic indoor RF responses, perform geolocation using multiple methods, and compare their performance. This work will look at two types of geolocation algorithms: (1) time-difference of arrival (TDOA) and (2) re- ceived signal strength Indicator (RSSI) fingerprinting or pattern- matching-based methods. An indoor space will be simulated with a grid of fixed receivers and a grid of transmit locations using Remcom’s Wireless InSite. Using the output of the Wireless InSite simulation the response from any given transmit location can be generated and used to evaluate geolocation performance.

indoor source localization, Wireless InSite, re- c↗
DOE OSTI2014

Morphometric Comparison of Clavicle Outlines from 3D Bone Scans and 2D Chest Radiographs: A Short-listing Tool to Assist Radiographic Identification of Human Skeletons

This paper describes a computerized clavicle identification system, primarily designed to resolve the identities of unaccounted for US soldiers who fought in the Korean War. Elliptical Fourier analysis is used to quantify the clavicle outline shape from skeletons and postero-anterior antemortem chest radiographs to rank individuals in terms of metric distance. Similar to leading fingerprint identification systems, shortlists of the top matching candidates are extracted for subsequent human visual assessment. Two independent tests of the computerized system using 17 field-recovered skeletons and 409 chest radiographs demonstrate that true positive matches are captured within the top 5% of the sample 75% of the time. These results are outstanding given the eroded state of some field-recovered skeletons and the faintness of the 1950’s photoflurographs. These methods enhance the capability to resolve several hundred cold cases for which little circumstantial information exists and current DNA and dental record technologies cannot be applied.

computer assisted↗
DOE OSTI2021

Reduced ecosystem resilience quantifies fine-scale heterogeneity in tropical forest mortality responses to drought

Sensitivity of forest mortality to drought in carbon-dense tropical forests remains fraught with uncertainty, while extreme droughts are predicted to be more frequent and intense. Here, in this study, the potential of temporal autocorrelation of high-frequency variability in Landsat Enhanced Vegetation Index (EVI), an indicator of ecosystem resilience, to predict spatial and temporal variations of forest biomass mortality is evaluated against in situ census observations for 64 site-year combinations in Costa Rican tropical dry forests during the 2015 ENSO drought. Temporal autocorrelation, within the optimal moving window of 24 months, demonstrated robust predictive power for in situ mortality (leave-one- out cross-validation R 2 = 0.54), which allows for estimates of annual biomass mortality patterns at 30 m resolution. Subsequent spatial analysis showed substantial fine-scale heterogeneity of forest mortality patterns, largely driven by drought intensity and ecosystem properties related to plant water use such as forest deciduousness and topography. Highly deciduous forest patches demonstrated much lower mortality sensitivity to drought stress than less deciduous forest patches after elevation was controlled. Our results highlight the potential of high-resolution remote sensing to “fingerprint” forest mortality and the significant role of ecosystem heterogeneity in forest biomass resistance to drought.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

The compelling case for indentation as a functional exploratory and characterization tool

The utility of indentation testing for characterizing a wide range of mechanical properties of brittle materials is highlighted in light of recent articles questioning its validity, specifically in relation to the measurement of toughness. Contrary to assertion by some critics, indentation fracture theory is fundamentally founded in Griffith–Irwin fracture mechanics, based on model crack systems evolving within inhomogeneous but well-documented elastic and elastic–plastic contact stress fields. Notwithstanding some numerical uncertainty in associated stress intensity factor relations, the technique remains an unrivalled quick, convenient and economical means for comparative, site-specific toughness evaluation. Most importantly, indentation patterns are unique fingerprints of mechanical behavior and thereby afford a powerful functional tool for exploring the richness of material diversity. At the same time, it is cautioned that unconditional usage without due attention to the conformation of the indentation patterns can lead to overstated toughness values. Limitations of an alternative, more engineering approach to fracture evaluation, that of propagating a precrack through a “standard” machined specimen, are also outlined. Thus misconceptions in the critical literature concerning the fundamental nature of crack equilibrium and stability within contact and other inhomogeneous stress fields are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Utilization of PARAFAC ‐Modeled Excitation‐Emission Matrix ( EEM ) Fluorescence Spectroscopy to Identify Biogeochemical Processing of Dissolved Organic Matter in a Northern Peatland

Abstract In this study, we contrast the fluorescent properties of dissolved organic matter ( DOM ) in fens and bogs in a Northern Minnesota peatland using excitation emission matrix fluorescence spectroscopy with parallel factor analysis ( EEM ‐ PARAFAC ). EEM ‐ PARAFAC identified four humic‐like components and one protein‐like component and the dynamics of each were evaluated based on their distribution with depth as well as across sites differing in hydrology and major biological species. The PARAFAC ‐ EEM experiments were supported by dissolved organic carbon measurements ( DOC ), optical spectroscopy ( UV ‐Vis), and compositional characterization by ultrahigh resolution Fourier transform ion cyclotron resonance mass spectroscopy ( FT ‐ ICR MS ). The FT ‐ ICR MS data indicate that metabolism in peatlands reduces the molecular weights of individual components of DOM , and oxygen‐rich less aromatic molecules are selectively biodegraded. Our data suggest that different hydrologic and biological conditions within the larger peat ecosystem drive molecular changes in DOM , resulting in distinctly different chemical compositions and unique fluorescent fingerprints. PARAFAC modeling of EEM data coupled with ultrahigh resolution FT ‐ ICR MS has the potential to provide significant molecular‐based information on DOM composition that will support efforts to better understand the composition, sources, and diagenetic status of DOM from different terrestrial and aquatic systems.

Tfaily, Malak M.↗
DOE OSTI2018

Generating a high-confidence reference genome map of the Greater Duckweed by integration of cytogenomic, optical mapping, and Oxford Nanopore technologies

Duckweeds are the fastest growing angiosperms and have the potential to become a new generation of sustainable crops. Although a seed plant, Spirodela polyrhiza clones rarely flower and multiply mainly through vegetative propagation. Whole-genome sequencing using different approaches and clones yielded two reference maps. One for clone 9509, supported in its assembly by optical mapping of single DNA molecules, and one for clone 7498, supported by cytogenetic assignment of 96 fingerprinted bacterial artificial chromosomes (BACs) to its 20 chromosomes. However, these maps differ in the composition of several individual chromosome models. We validated both maps further to resolve these differences and addressed whether they could be due to chromosome rearrangements in different clones. For this purpose, we applied sequential multicolor fluorescence in situ hybridization (mcFISH) to seven S. polyrhiza clones, using 106 BACs that were mapped onto the 39 pseudomolecules for clone 7498. Furthermore we integrated high-depth Oxford Nanopore (ON) sequence data for clone 9509 to validate and revise the previously assembled chromosome models. We found no major structural rearrangements between these seven clones, identified seven chimeric pseudomolecules and Illumina assembly errors in the previous maps, respectively. A new S. polyrhiza genome map with high contiguity was produced with the ON sequence data and genome-wide synteny analysis supported the occurrence of two Whole Genome Duplication events during its evolution. This work generated a high confidence genome map for S. polyrhiza at the chromosome scale, and illustrates the complementarity of independent approaches to produce whole-genome assemblies in the absence of a genetic map.

59 BASIC BIOLOGICAL SCIENCES↗