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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

The Cognitive Effects of Machine Learning Aid in Domain-Specific and Domain-General Tasks.

With machine learning (ML) technologies rapidly expanding to new applications and domains, users are collaborating with artificial intelligence-assisted diagnostic tools to a larger and larger extent. But what impact does ML aid have on cognitive performance, especially when the ML output is not always accurate? Here, we examined the cognitive effects of the presence of simulated ML assistance—including both accurate and inaccurate output—on two tasks (a domain-specific nuclear safeguards task and domain-general visual search task). Patterns of performance varied across the two tasks for both the presence of ML aid as well as the category of ML feedback (e.g., false alarm). These results indicate that differences such as domain could influence users’ performance with ML aid, and suggest the need to test the effects of ML output (and associated errors) in the specific context of use, especially when the stimuli of interest are vague or ill-defined

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Structural Interconversion between Agglomerated Palladium Domains and Mononuclear Pd(II) Cations in Chabazite Zeolites

Palladium-exchanged zeolites are candidate materials for passive NO x adsorption in automotive exhaust aftertreatment, where mononuclear Pd cations behave as precursors to the purported NO x adsorption sites. Yet, the structures of zeolite lattice binding sites capable of stabilizing mononuclear Pd 2+ ions, and the mechanisms that interconvert agglomerated PdO and Pd domains into mononuclear Pd 2+ ions during Pd redispersion treatments, remain incompletely understood. In this work, we use a suite of spectroscopic methods and quantitative site titration techniques to characterize mononuclear and agglomerated Pd species on zeolites with varying material properties and treatment history. Aqueous-phase methods to introduce Pd onto NH 4 -form zeolites initially form mononuclear [Pd(NH 3 ) 4 ] 2+ complexes, but subsequent thermal treatments (573–723 K; air) lead to in situ formation of H 2 that first reduces Pd 2+ to metallic Pd domains, which are then oxidized by air to PdO domains. Progressive treatment of Pd-zeolites in air to higher temperatures (723–1023 K) converts larger fractions of agglomerated PdO to mononuclear Pd 2+ , as quantified by H 2 temperature programmed reduction, because higher temperature treatments facilitate Pd redispersion toward deeper locations within chabazite (CHA) crystallites, which is corroborated by complementary titrimetric and spectroscopic data. Pd-CHA zeolites synthesized with similar bulk Pd and framework Al content, but varying framework Al arrangement, provide evidence that six-membered rings (6-MR) hosting paired Al sites (Al–O–(Si–O) x –Al, x = 1, 2) stabilize Pd 2+ ions and that otherwise isolated Al sites can stabilize [PdOH] + species, identifiable by an IR OH stretch at 3660 cm –1 . These findings clarify the underlying chemical processes and gas environments that cause Pd agglomeration in zeolites and their subsequent redispersion to mononuclear Pd 2+ ions, which prefer binding at 6-MR paired Al sites in CHA, and indicate that higher temperature air treatments lead to more uniform Pd spatial distributions throughout zeolite crystallites.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Accelerating Multivariate Functional Approximation Computation with Domain Decomposition Techniques⋆

Modeling large datasets through Multivariate Functional Approximations (MFA) provide an elegant way to handle many visualization and scientific analysis workflows. The process necessitates scalable data partitioning methods to compute MFA representations efficiently without compromising the accuracy or continuity of the reconstructed solution. We propose a domain -decomposed method for computing the MFA with B -spline bases, which reduces the total work per task and uses a restricted Additive Schwarz (RAS) method to converge the control point data degrees -of -freedom along subdomain boundaries. We provide an in-depth analysis of the parallel approach with domain decomposition solvers, aiming to minimize local subdomain error residuals and recover high -order continuity at subdomain interfaces with appropriate choices of knot overlaps. The communication cost, determined by the overlap regions in the RAS implementation, is optimized to recover the numerical error profile of the single subdomain case. Our proposed method stands in contrast to previous methods, which typically only recover either C 0 or at best C 1 continuity for arbitrary B -spline degree expansions, or those that require post -processing to blend discontinuities in the reconstructed data. We demonstrate the effectiveness of our approach using analytical and real -world datasets in 1D, 2D, and 3D through both strong and weak scaling studies. The performance results indicate that the overall cost of computing the approximation is directly proportional to the underlying nearest -neighbor communication implementation, and is only weakly dependent on the overlap region size that determines the size of the messages. This finding underscores the efficiency and scalability of our proposed method, making it a promising solution for handling large datasets in scientific workflows.

additive Schwarz solvers↗
DOE OSTI2020

Carbohydrate‐binding domains facilitate efficient oligosaccharides synthesis by enhancing mutant catalytic domain transglycosylation activity

Abstract Chemoenzymatic approaches using carbohydrate‐active enzymes (CAZymes) offer a promising avenue for the synthesis of glycans like oligosaccharides. Here, we report a novel chemoenzymatic route for cellodextrins synthesis employed by chimeric CAZymes, akin to native glycosyltransferases, involving the unprecedented participation of a “non‐catalytic” lectin‐like domain or carbohydrate‐binding modules (CBMs) in the catalytic step for glycosidic bond synthesis using β‐cellobiosyl donor sugars as activated substrates. CBMs are often thought to play a passive substrate targeting role in enzymatic glycosylation reactions mostly via overcoming substrate diffusion limitations for tethered catalytic domains (CDs) but are not known to participate directly in any nucleophilic substitution mechanisms that impact the actual glycosyl transfer step. This study provides evidence for the direct participation of CBMs in the catalytic reaction step for β‐glucan glycosidic bonds synthesis enhancing activity for CBM‐based CAZyme chimeras by >140‐fold over CDs alone. Dynamic intradomain interactions that facilitate this poorly understood reaction mechanism were further revealed by small‐angle X‐ray scattering structural analysis along with detailed mutagenesis studies to shed light on our current limited understanding of similar transglycosylation‐type reaction mechanisms. In summary, our study provides a novel strategy for engineering similar CBM‐based CAZyme chimeras for the synthesis of bespoke oligosaccharides using simple activated sugar monomers.

Bandi, Chandra Kanth↗
DOE OSTI2021

KRAS interaction with RAF1 RAS-binding domain and cysteine-rich domain provides insights into RAS-mediated RAF activation

The first step of RAF activation involves binding to active RAS, resulting in the recruitment of RAF to the plasma membrane. To understand the molecular details of RAS-RAF interaction, we present crystal structures of wild-type and oncogenic mutants of KRAS complexed with the RAS-binding domain (RBD) and the membrane-interacting cysteine-rich domain (CRD) from the N-terminal regulatory region of RAF1. Our structures reveal that RBD and CRD interact with each other to form one structural entity in which both RBD and CRD interact extensively with KRAS. Mutations at the KRAS-CRD interface result in a significant reduction in RAF1 activation despite only a modest decrease in binding affinity. Combining our structures and published data, we provide a model of RAS-RAF complexation at the membrane, and molecular insights into RAS-RAF interaction during the process of RAS-mediated RAF activation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Polerovirus N-terminal readthrough domain structures reveal molecular strategies for mitigating virus transmission by aphids

Abstract Poleroviruses, enamoviruses, and luteoviruses are icosahedral, positive sense RNA viruses that cause economically important diseases in food and fiber crops. They are transmitted by phloem-feeding aphids in a circulative manner that involves the movement across and within insect tissues. The N-terminal portion of the viral readthrough domain ( N RTD) has been implicated as a key determinant of aphid transmission in each of these genera. Here, we report crystal structures of the N RTDs from the poleroviruses turnip yellow virus (TuYV) and potato leafroll virus (PLRV) at 1.53-Å and 2.22-Å resolution, respectively. These adopt a two-domain arrangement with a unique interdigitated topology and form highly conserved dimers that are stabilized by a C-terminal peptide that is critical for proper folding. We demonstrate that the PLRV N RTD can act as an inhibitor of virus transmission and identify N RTD mutant variants that are lethal to aphids. Sequence conservation argues that enamovirus and luteovirus N RTDs will follow the same structural blueprint, which affords a biological approach to block the spread of these agricultural pathogens in a generalizable manner.

Schiltz, Carl J. (ORCID:0000000332030784)↗
DOE OSTI2024

Imaging and structure analysis of ferroelectric domains, domain walls, and vortices by scanning electron diffraction

Direct electron detectors in scanning transmission electron microscopy give unprecedented possibilities for structure analysis at the nanoscale. In electronic and quantum materials, this new capability gives access to, for example, emergent chiral structures and symmetry-breaking distortions that underpin functional properties. Quantifying nanoscale structural features with statistical significance, however, is complicated by the subtleties of dynamic diffraction and coexisting contrast mechanisms, which often results in a low signal-to-noise ratio and the superposition of multiple signals that are challenging to deconvolute. Here we apply scanning electron diffraction to explore local polar distortions in the uniaxial ferroelectric Er(Mn,Ti)O 3 . Using a custom-designed convolutional autoencoder with bespoke regularization, we demonstrate that subtle variations in the scattering signatures of ferroelectric domains, domain walls, and vortex textures can readily be disentangled with statistical significance and separated from extrinsic contributions due to, e.g., variations in specimen thickness or bending. The work demonstrates a pathway to quantitatively measure symmetry-breaking distortions across large areas, mapping structural changes at interfaces and topological structures with nanoscale spatial resolution.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Spread spectrum time domain reflectometry (SSTDR) and frequency domain reflectometry (FDR) cable inspection using machine learning

Cables are initially qualified for nuclear power plant use for 40 years. As plants extend their operating license to 60 and 80 years, justification for continued cable use must shift to a condition-based approach since it is cost prohibitive to completely replace cables that are likely still capable of performing their design function. The Pacific Northwest National Laboratory (PNNL) Accelerated and Real Time Experimental Nodal Analysis (ARENA) cable motor test bed was used to test the response of a commercial spread spectrum time domain reflectometry (SSTDR) system, a laboratory instrument software-controlled SSTDR, and a vector network analyzer-based frequency domain reflectometry (FDR) system to various cable anomalies. The three instrument systems were able to interrogate cables over a range of frequency bandwidths that can be helpful for human data analysis. Data were subjected to supervised and unsupervised machine learning (ML) analyses to distinguish normal undamaged cable responses from anomalous cable responses. Both supervised and unsupervised ML approaches produced encouraging results with an undamaged/anomalous prediction accuracy from 0.69% to 0.87%. Recommendations for further development and field implementation include increased and more balanced sample sets particularly including more training data.

SSTDR, FDR, Reflectometry, Machine Learning, ARENA↗
DOE OSTI2022

Performance and characterization of the SPT-3G digital frequency-domain multiplexed readout system using an improved noise and crosstalk model

The third-generation South Pole Telescope camera (SPT-3G) improves upon its predecessor (SPTpol) by an order of magnitude increase in detectors on the focal plane. The technology used to read out and control these detectors, digital frequency-domain multiplexing (DfMUX), is conceptually the same as used for SPTpol, but extended to accommodate more detectors. A nearly 5× expansion in the readout operating bandwidth has enabled the use of this large focal plane, and SPT-3G performance meets the forecasting targets relevant to its science objectives. However, the electrical dynamics of the higher-bandwidth readout differ from predictions based on models of the SPTpol system due to the higher frequencies used and parasitic impedances associated with new cryogenic electronic architecture. To address this, we present an updated derivation for electrical crosstalk in higher-bandwidth DfMUX systems and identify two previously uncharacterized contributions to readout noise, which become dominant at high bias frequency. The updated crosstalk and noise models successfully describe the measured crosstalk and readout noise performance of SPT-3G. These results also suggest specific changes to warm electronics component values, wire-harness properties, and SQUID parameters, to improve the readout system for future experiments using DfMUX, such as the LiteBIRD space telescope.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Structure of the Receptor Binding Domain of EnvP(b)1, an Endogenous Retroviral Envelope Protein Expressed in Human Tissues

EnvP(b)1 is an endogenous retroviral envelope gene found in human and other primate genomes. We report EnvP(b)1 sequences in primate genomes consistent with an integration event between 40 and 71 million years ago. Using a highly specific polyclonal antiserum raised against the putative receptor binding domain (RBD) of human EnvP(b)1, we detected expression in human placenta, ovaries, and thymus. We found that EnvP(b)1 is proteolytically processed, and using cell-cell fusion assays in multiple primate cell lines, we demonstrated that extant EnvP(b)1 proteins from a variety of primate genomes are fusogenic. This work supports the idea that EnvP(b)1 is under purifying selection and its fusogenic activity has been maintained for over 40 million years. We determined the structure of the RBD of human EnvP(b)1, which defines structural similarities with extant leukemia viruses, despite little sequence conservation. This structure highlights a common scaffold from which novel receptor binding specificities likely evolved. The evolutionary plasticity of this domain may underlie the diversity of related Envs in circulating viruses.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Probing the structure and function of the protease domain of botulinum neurotoxins using single-domain antibodies

Botulinum neurotoxins (BoNTs) are among the deadliest of bacterial toxins. BoNT serotype A and B in particular pose the most serious threat to humans because of their high potency and persistence. To date, there is no effective treatment for late post-exposure therapy of botulism patients. Here, we aim to develop single-domain variable heavy-chain (VHH) antibodies targeting the protease domains (also known as the light chain, LC) of BoNT/A and BoNT/B as antidotes for post-intoxication treatments. Using a combination of X-ray crystallography and biochemical assays, we investigated the structures and inhibition mechanisms of a dozen unique VHHs that recognize four and three non-overlapping epitopes on the LC of BoNT/A and BoNT/B, respectively. We show that the VHHs that inhibit the LC activity occupy the extended substrate-recognition exosites or the cleavage pocket of LC/A or LC/B and thus block substrate binding. Notably, we identified several VHHs that recognize highly conserved epitopes across BoNT/A or BoNT/B subtypes, suggesting that these VHHs exhibit broad subtype efficacy. Further, we identify two novel conformations of the full-length LC/A, that could aid future development of inhibitors against BoNT/A. Our studies lay the foundation for structure-based engineering of protein- or peptide-based BoNT inhibitors with enhanced potencies and cross-subtypes properties.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Spread Spectrum Time Domain Reflectometry (SSTDR) and Frequency Domain Reflectometry (FDR) for Detection of Cable Anomalies Using Machine Learning

Cables are initially qualified for nuclear power plant use for 40 years. As plants extend their operating license to 60 and 80 years, continued use of these cables must shift to a performance-based approach since it is cost prohibitive to completely replace cables that are likely still capable of performing their design function. A variety of cable tests are available and are commonly applied during outages when the cables can be taken out of service. Frequency domain reflectometry (FDR) is one of these test methods that is being more broadly accepted and used because it not only detects anomalies along the cable with a low-voltage signal that does not stress the cable insulation, but the technique also locates the anomalies. This supports follow-up local inspection and local repair or partial replacement of a damaged cable segment. Currently, FDR testing is only applied to cables that are taken out of service since the test instrument would be damaged by operational voltages. A related technology that has found some acceptance in the aircraft and rail industry is spread spectrum time domain reflectometry (SSTDR). This technology has been implemented with a custom commercial instrument by LiveWire Innovation Inc. that is designed to operate on live cables up to 1000 volts. One of the main conclusions of a previous effort was that cable reflectometry plots can be difficult for humans to analyze due to baseline noise, low or noisy anomaly response peaks, or large responses from cable ends. Detection of cable anomalies for many of these frequencies and test conditions was challenging for manual analysis. This presented an ideal opportunity for ML analysis to distinguish undamaged cable indications from anomalous cable indications. This research discusses application of machine learning (ML) to reflectometry cable test methods. The goal was to assess feasibility to distinguish undamaged cable reflectometry responses from damaged or anomalous cable reflectometry responses. The assessment considered the 3 instruments, multiple frequency bandwidths from each instrument, multiple cable anomalies and test conditions, and both supervised and unsupervised ML approaches. Although approaches and analysis methods were not identical or directly comparable, both outputs were encouraging. The unsupervised prediction weighted accuracy was assessed by instrument and by frequency. It performed better at high frequencies with the highest prediction accuracy of 0.84 for the higher frequency FDR, 0.79 for the 48-MHz LiveWire SSTDR, and 0.77 for 300-MHz PNNL SSTDR. The initial weighted accuracy average across all frequencies for using supervised ML was 0.56 to 0.68. The supervised analysis was repeated with noisier training data removed resulting in weighted accuracies of 0.69 to 0.87. These weighted accuracies are not directly comparable due to differences in the supervised and unsupervised analysis details but do indicate an encouraging trend. Even with limited and unbalanced data, strong prediction accuracies seem encouraging for further work including more data under a wider range of conditions.

42 ENGINEERING↗
DOE OSTI2023

Spread Spectrum Time-Domain Reflectometry and Frequency Domain Reflectometry to Detect Shielded and Unshielded Cable Moisture Exposure

This work evaluates the feasibility to extend spread spectrum time-domain reflectometry (SSTDR) and frequency domain reflectometry (FDR) electrical cable testing to characterize whether an electrical cable is submerged in water or not and where it may be submerged. Using PNNL’s ARENA cable and motor test bed, shielded and non-shielded electrical cables were evaluated using SSTDR and FDR methods to detect and locate electrical cable exposure to water. Both SSTDR and FDR showed the presence of water with a non-shielded cable. Moisture was only detectable with the shielded cable if the insulation was damaged.

reflectometry cable test, cable moisture detection↗
DOE OSTI2023

Spread Spectrum Time Domain Reflectometry (SSTDR) and Frequency Domain Reflectometry (FDR) for Detection of Cable Anomalies Using Machine Learning

Cables are initially qualified for nuclear power plant use for 40 years. As plants extend their operating license to 60 and 80 years, continued use of these cables must shift to a performance-based approach since it is cost prohibitive to completely replace cables that are likely still capable of performing their design function. A variety of cable tests are available and are commonly applied during outages when the cables can be taken out of service. Frequency domain reflectometry (FDR) is one of these test methods that is being more broadly accepted and used because it not only detects anomalies along the cable with a low-voltage signal that does not stress the cable insulation, but the technique also locates the anomalies. This supports follow-up local inspection and local repair or partial replacement of a damaged cable segment. Currently, FDR testing is only applied to cables that are taken out of service since the test instrument would be damaged by operational voltages.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗