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At least 1,207 records · Page 67

All sources NASA NTRS DOE OSTI

DOE OSTI2019

Novel Ordered Rocksalt-Type Lithium-Rich Li 2 Ru 1–x Ni x O 3-δ (0.3 ≤ x ≤ 0.5) Cathode Material with Tunable Anionic Redox Potential

In this work, a series of ordered rocksalt (OR) type Li-rich Li 2 Ru 1–x Ni x O 3-δ (LRN x O, 0.3 ≤ x ≤ 0.5) are successfully synthesized and investigated for the first time. X-ray diffraction and neutron powder diffraction patterns exhibit an obvious phase transition from layered to an OR structure as the Ni content gradually increases from x = 0 to x = 0.5, which leads to different electrochemical behaviors. In the case of OR-LRN 0.4 O, an ~350 mV decrease of the oxygen oxidation potential compared with Li 2 RuO 3 (LRO) is observed from around 4.2 to 3.85 V, which is confirmed by both X-ray photelectron O 1s spectra and dQ/dV results. Additionally, the role of Ni substitution on the oxygen redox reaction is studied by first-principles calculations, and it is concluded that the formation of the OR structure caused by Ni substitution is the main reason for lowering the oxygen oxidation potential. In addition, the average discharge voltage of OR-LRN 0.4 O is also enhanced compared with LRO. This work provides a novel innovative strategy to modulate and control the oxygen anion redox reaction for high-energy-density Li-rich materials, which shed light on the fundamental understanding and optimizing of the anion redox process in Li-rich materials.

25 ENERGY STORAGE↗

DOE OSTI2020

Electronic structure calculations of twisted multi-layer graphene superlattices

Quantum confinement endows two-dimensional (2D) layered materials with exceptional physics and novel properties compared to their bulk counterparts. Although certain two- and few-layer configurations of graphene have been realized and studied, a systematic investigation of the properties of arbitrarily layered graphene assemblies is still lacking. We introduce theoretical concepts and methods for the processing of materials information, and as a case study, apply them to investigate the electronic structure of multi-layer graphene-based assemblies in a high-throughput fashion. We provide a critical discussion of patterns and trends in tight binding band structures and we identify specific layered assemblies using low-dispersion electronic bands as indicators of potentially interesting physics like strongly correlated behavior. A combination of data-driven models for visualization and prediction is used to intelligently explore the materials space. This work more generally aims to increase confidence in the combined use of physics-based and data-driven modeling for the systematic refinement of knowledge about 2D layered materials, with implications for the development of novel quantum devices.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Stability of the peroxide group in BaO 2 under high pressure

Alkaline earth metal peroxides are typical examples of ionic compounds containing polyanions. We herein report a stable BaO 2 phase at high pressure up to 130 GPa found via a first-principles computational structure searches and high-pressure experimental investigations. The identified monoclinic structure (space group C2/m) can be derived by sublattice distortions of Ba atoms and peroxide groups associated with the phonon mode softening of the lower-pressure Cmmm structure. Contrary to the previous expectation of polymerization of the peroxide group at elevated pressure, the new phase retains the peroxide group and interestingly exhibits an insulating behavior demonstrating an increase of the band gap under compression. Our synchrotron XRD measurements could not distinguish between Cmmm and C2/m BaO 2 definitively because the difference in XRD patterns is very subtle. However, our data do not show any sign of polymerization transition up to 120 GPa. Raman spectra of the O-O peroxide vibration show a small anomaly in frequency at 110 GPa, which is qualitatively similar to that predicted theoretically due to the Cmmm to C2/m phase transition thus supporting the predicted transformation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2024

Nanoscale structural correlations in a model cuprate superconductor

Understanding the extent and role of inhomogeneity is a pivotal challenge in the physics of cuprate superconductors. While it is known that structural and electronic inhomogeneity is prevalent in the cuprates, it has proven difficult to disentangle compound-specific features from universally relevant effects. Here, in this study, we combine advanced neutron and x-ray diffuse scattering with numerical modeling to obtain insight into bulk structural correlations in HgBa 2 ⁢ CuO 4+δ . This cuprate exhibits a high optimal transition temperature of nearly 100 K, pristine charge-transport behavior, and a simple average crystal structure without long-range structural instabilities, and is therefore uniquely suited for investigations of intrinsic inhomogeneity. We uncover diffuse reciprocal-space patterns that correspond to prominent nanoscale correlations of atomic displacements perpendicular to the CuO 2 planes. The real-space nature of the correlations is revealed through three-dimensional pair distribution function analysis and complementary numerical refinement. We find that relative displacements of ionic and CuO 2 layers play a crucial role, and that the structural inhomogeneity is not directly caused by the presence of conventional point defects. The observed correlations are therefore intrinsic to HgBa 2 ⁢ CuO 4+δ , and thus likely important for the physics of cuprates more broadly. It is possible that the structural correlations are closely related to the unusual superconducting fluctuations and Mott-localization in these complex oxides. As advances in scattering techniques yield increasingly comprehensive data, the experimental and analysis tools developed here for large volumes of diffuse scattering data can be expected to aid future investigations of a wide range of materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2024

Custom Accessors: Enabling Scalable Data Ingestion, (Re-)Organization, and Analysis on Distributed Systems

The emerging class of high velocity and high volume data analytic workflows comprise interwoven data ingestion, organization, and processing stages, with ingestion and organization steps often contributing comparable or even higher computational costs than actual processing steps. Since complex workflows consist of a variety of phases that view and use data differently, being able to construct efficient, scalable, distributed data structures (arrays, vectors, sets, maps, and multi-maps) is essential and requires custom methods to extend and shrink containers, analyze and position data, and, maintain globallyconsistent meta-data. In this paper, we propose a novel datastructure access paradigm based on the concept of Accessors. At a high level, accessors are customizable callable objects that can modify the behavior of insert, read, update, and delete operations for distributed containers while preserving atomicity guarantees. Accessors provide a very clean and natural way to implement a variety of programming patterns, e.g., conditional insertion/deletion and cascading computations, which would be otherwise hard (or even impossible) to express in parallel and distributed settings without using locks. We demonstrate the practicality and usefulness of our approach with two representative use cases and study the performance of these applications on a distributed High-Performance Computing system. Our analysis highlights that our proposed abstraction allows for an effective overlapping and concurrent execution of different workflow steps (e.g., data ingestion and analysis), which in a conventional analytics pipeline would execute sequentially, contributing cumulatively to the overall latency.

Castellana, Vito G. [BATTELLE (PACIFIC NW LAB)] (O↗

DOE OSTI2019

Resistance and Resilience of Sulfidogenic Communities in the Face of the Specific Inhibitor Perchlorate

Hydrogen sulfide is a toxic and corrosive gas, produced by the activity of sulfate-reducing microorganisms (SRM). Owing to the environmental, economic and human-health consequences of sulfide, there is interest in developing specific inhibitors of SRM. Recent studies have identified perchlorate as a promising emerging inhibitor. The aim of this work is to quantitatively dissect the inhibitory dynamics of perchlorate. Sulfidogenic mixed continuous-flow systems were treated with perchlorate. SRM number, sulfide production and community structure were monitored pre-, during and post-treatment. The data generated was compared to a simple mathematical model, where SRM growth slows as a result of inhibition. The experimental data supports the interpretation that perchlorate largely acts to suppress SRM growth rates, rendering planktonic SRM increasingly susceptible to wash-out. Surface-attachment was identified as an important parameter preventing SRM wash-out and thus governing inhibitory dynamics. Our study confirmed the lesser depletion of surface-attached SRM as compared to planktonic SRM during perchlorate treatment. Indirect effects of perchlorate (bio-competitive exclusion of SRM by dissimilatory perchlorate-reducing bacteria, DPRB) were also assayed by amending reactors with DPRB. Indeed, low concentrations of perchlorate coupled with DRPB amendment can drive sulfide concentrations to zero. Further, inhibition in a complex community was compared to that in a pure culture, highlighting similarities and differences between the two scenarios. Finally, we quantified susceptibility to perchlorate across SRM in various culture conditions, showing that prediction of complex behavior in continuous systems from batch results is possible. This study thus provides an overview of the sensitivity of sulfidogenic communities to perchlorate, as well as mechanisms underlying these patterns.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1986

The climate of Mars

The composition of the primitive Martian atmosphere and its development into the present environment are described. The primitive atmosphere consisted of water vapor, carbon dioxide, and nitrogen released from rocks; the greenhouse effect which maintained the surface temperature above the frost point of water is examined. Volcanic activity reduced the greenhouse effect and along with CO2 removal from the atmosphere caused a lowering of the planet temperature. The global circulation patterns on earth and Mars are compared; the similarities in the circulation patterns and Mars' seasonal variations are studied. The carbon dioxide and water cycles on Mars are analyzed; the carbon dioxide cycle determines seasonal variations in surface pressure and the behavior of the water cycle. The behavior of the atmospheric dust and the relationship between the seasonal dust cycle and Hadley circulation are investigated. The periodic variations in the three orbital parameters of Mars, which affect the climate by changing the seasonal and latitudinal distribution of incoming solar energy are discussed

Haberle, R. M.↗

NASA NTRS1990

Evidence for chaotic fault interactions in the seismicity of the San Andreas fault and Nankai trough

The dynamical behavior introduced by fault interactions is examined here using a simple spring-loaded, slider-block model with velocity-weakening friction. The model consists of two slider blocks coupled to each other and to a constant-velocity driver by elastic springs. For an asymmetric system in which the frictional forces on the two blocks are not equal, the solutions exhibit chaotic behavior. The system's behavior over a range of parameter values seems to be generally analogous to that of weakly coupled segments of an active fault. Similarities between the model simulations and observed patterns of seismicity on the south central San Andreas fault in California and in the Nankai trough along the coast of southwestern Japan.

Huang, Jie↗

NASA NTRS2003

Bioconvection in Cultures of the Calcifying Unicellular Alga Pleurochrysis Carterae

The unicellular, marine, calcifying alga P leurochiysis carterae--a model to study cell morphogenesis, cell polarity, calcification, gravitaxis, reproduction and development-- has extremely flexible culture requirements. Support studies for a flight experiment addressing cell motility suggested that cell density (cells/ml) affects cell movement in P. carterae cultures through the gradual establishment of bioconvection as the culture grows. To assess the effect of cell density on direction of the movement, without the effects of aging of the culture, swimming behavior was analyzed in aliquots from a series of dilutions obtained from a stock culture. Results showed that at low concentrations cells swim randomly. As the concentration increases, upswimming patterns overtake random swimming. Gradually, up and down movement patterns prevail, representative of bioconvection. This oriented swimming of P. carterae occurs in a wide range of concentrations, adding to the list of flexible requirements, in this case, cell concentration, to be used for spaceflight studies addressing cell motility and bioconvection in a unicellular model of biologically directed mineralization.

Montufar-Solis, Dina↗

NASA NTRS1989

Communication indices of crew coordination

The relationship between communication patterns and performance in 10 two-person flightcrews is explored with the aim of identifying speech variations which differentiate low- and high-error full mission simulator flights. Verbal data, transcribed from the videotaped performances, are treated as interactive sequences of speech events in which statements spoken by one crewmember are considered within the context of the other crewmember's prior and subsequent speech. Specific speech patterns characterized each crew, but the overriding findings included: a) marked homogeneity of patterns characterizing low-error crews, interpreted as the adoption of a standard form of communicating, and b) heterogeneity of patterns characterizing high-error crews, interpreted as the relative absence of a conventionalized form. Because conventions are regularities which confirm the expectations of those involved, predictability of crewmember behavior should be greater when standard conventions are followed. We conclude that such a practice can facilitate the coordination process and enhance crew performance.

Aerospace Medicine↗

NASA NTRS2016

Study of Material Densification of In718 in the Higher Throughput Parameter Regime

Selective Laser Melting (SLM) is a powder bed fusion additive manufacturing process used increasingly in the aerospace industry to reduce the cost, weight, and fabrication time for complex propulsion components. Previous optimization studies for SLM using the Concept Laser M1 and M2 machines at NASA Marshall Space Flight Center have centered on machine default parameters. The objective of this project is to characterize how heat treatment affects density and porosity from a microscopic point of view. This is performs using higher throughput parameters (a previously unexplored region of the manufacturing operating envelope for this application) on material consolidation. Density blocks were analyzed to explore the relationship between build parameters (laser power, scan speed, and hatch spacing) and material consolidation (assessed in terms of density and porosity). The study also considers the impact of post-processing, specifically hot isostatic pressing and heat treatment, as well as deposition pattern on material consolidation in the higher energy parameter regime. Metallurgical evaluation of specimens will also be presented. This work will contribute to creating a knowledge base (understanding material behavior in all ranges of the AM equipment operating envelope) that is critical to transitioning AM from the custom low rate production sphere it currently occupies to the world of mass high rate production, where parts are fabricated at a rapid rate with confidence that they will meet or exceed all stringent functional requirements for spaceflight hardware. These studies will also provide important data on the sensitivity of material consolidation to process parameters that will inform the design and development of future flight articles using SLM.

Cordner, Samuel↗

NASA NTRS2022

First Observations of Mesospheric OH Emission Profiles from OMPS/LP

The hydroxyl radical (OH) is one of the most reactive trace species and plays several important roles in the photochemical equilibrium and energy balance in the mesosphere. Global observations of OH from satellite instruments have a role to play in the study of OH and water vapor variations. This study describes an advanced algorithm to detect mesospheric OH emission profiles from the Suomi NPP satellite Ozone Mapping and Profiler Suite Limb Profiler (OMPS/LP). A triplet technique has been adapted to the OMPS/LP radiance measurements for determining OH emission signatures and OH index (OHI) from the OH A2Σ+-X2Π 0-0 band near the 308.8-nm wavelength. The derived mesospheric profiles provide an overall picture of the vertical distribution of OHI between 55 and 84 km and seasonal and latitudinal variability of the strength and height of the OHI. The observed annual cycle is correlated with the water vapor cycle and anticorrelated with the mesospheric temperature cycle. The data show that the relationships persist during the period of April 2012–December 2020. The seasonal behavior of OHI may be associated with variations in solar illumination or mesospheric water vapor abundance. The influence of solar illumination is dominant in the midlatitudes, while the OHI pattern is dominated by water vapor photolysis and other influences in the tropics.

Observations of Mesospheric OH Emission↗

NASA NTRS2004

The effects of heavy particle irradiation on exploration and response to environmental change

Free radicals produced by exposure to heavy particles have been found to produce motor and cognitive behavioral toxicity effects in rats similar to those found during aging. The present research was designed to investigate the effects of exposure to 56Fe particles on the ability of male Sprague-Dawley rats to detect novel arrangements in a given environment. Using a test of spatial memory previously demonstrated to be sensitive to aging, open field activity and reaction to spatial and non-spatial changes were measured in a group that received a dose of 1.5 Gy (n=10) of 56Fe heavy particle radiation or in non-radiated controls (n=10). Animals irradiated with 1.5 Gy of 56Fe particles exhibited some age-like effects in rats tested, even though they were, for the most part, subtle. Animals took longer to enter, visited less and spent significantly less time in the middle and the center portions of the open field, independently of total frequency and duration of activity of both groups. Likewise, irradiated subjects spend significantly more time exploring novel objects placed in the open field than did controls. However, irradiated subjects did not vary from controls in their exploration patterns when objects in the open field were spatially rearranged. Thus, irradiation with a dose of 1.5 Gy of 56Fe high-energy particle radiation elicited age-like effects in general open field exploratory behavior, but did not elicit age-like effects during the spatial and non-spatial rearrangement tasks. Published by Elsevier Ltd on behalf of COSPAR.

NASA Program Biomedical Research and Countermeasur↗

DOE OSTI2014

Ergodicity reflected in macroscopic and microscopic field-dependent behavior of BNT-based relaxors

The effect of heterovalent B-site doping on ergodicity of relaxor ferroelectrics is studied using (1 − y)(0.81Bi{sub 1/2}Na{sub 1/2}TiO{sub 3}-0.19Bi{sub 1/2}K{sub 1/2}TiO{sub 3})-yBiZn{sub 1/2}Ti{sub 1/2}O{sub 3} (BNT-BKT-BZT) with y = (0.02;0.03;0.04) as a model system. Both the large- and small-signal parameters are studied as a function of electric field. The crystal structure is assessed by means of neutron diffraction in the initial state and after exposure to a high electric field. In order to measure ferroelastic domain textures, diffraction patterns of the poled samples are collected as a function of sample rotation angle. Piezoresponse force microscopy (PFM) is employed to probe the microstructure for polar regions at a nanoscopic scale. For low electric fields E < 2 kV·mm{sup −1}, large- and small-signal constitutive behavior do not change with composition. At high electric fields, however, drastic differences are observed due to a field-induced phase transition into a long-range ordered state. It is hypothesized that increasing BZT content decreases the degree of non-ergodicity; thus, the formation of long-range order is impeded. It is suggested that frozen and dynamic polar nano regions exist to a different degree, depending on the BZT content. This image is supported by PFM measurements. Moreover, PFM measurements suggest that the relaxation mechanism after removal of the bias field is influenced by surface charges.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2021

Hybrid Analytics Solution to Improve Coal Power Plant Operations

This project focused on developing advanced methods for thermal performance monitoring of a coal-fueled power plant. The specific goal was to develop and demonstrate a new thermal performance monitoring approach using a hybrid model that integrates a physics-based heat balance model with a machine learning-based pattern recognition model. The hybrid model enables increased accuracy and scope of the thermal analysis and an improved ability to monitor and detect changes in plant operation. This new approach takes full advantage of the individual model capabilities and creates an important new set of capabilities not previously possible using the two types of models separately. Using the heat balance model, a rich set of derived parameters (virtual sensors) are calculated from the measured plant operating data at each time point. The combined measured and derived data values are used by machine learning algorithms to create pattern recognition models over the range of normal unit operation. To create the monitoring models, historical data from normal operation of the plant is first processed by the heat balance model to compute the derived parameter data. The result is a greatly expanded set of normal operating data that can be used as input to create the pattern recognition model. Once the models are calibrated for normal operation, the hybrid model is suitable for use in continuous online monitoring. During online monitoring, new plant operating data is processed first by the heat balance model and then by the pattern recognition model. Results from the pattern recognition model quantify the deviation of each measured or derived parameter from its expected value in normal operation. The hybrid models can detect abnormal changes in plant operating data with very high accuracy and sensitivity. When abnormal behavior is detected, alerts are generated automatically for evaluation by the plant monitoring staff. The new hybrid solution product was developed and verified in the performance of the project. The hybrid solution was tested first in a simulation environment that mimicked the plant data systems and infrastructure used by U.S. power generating plants and utilities. The hybrid solution was then deployed for real-time, online monitoring of an operating coal-fueled power plant at a field test site. Field testing demonstrated that all hybrid solution development objectives were accomplished. The project work was based on combining the capabilities of two existing software products to create the new hybrid solution product. One of these was the existing MapEx® heat balance product and the other was the existing SureSense® advanced pattern recognition product. Each of these separate products was assessed to be at a Technology Readiness Level (TRL) of 9 at the start of the effort. The hybrid solution product was assessed to be at a TRL of 2 at the start of the project based on early feasibility work by the project team. At completion of the field testing performed in the project, the hybrid solution product was assessed to be at a TRL of 7. The project team expects that the hybrid solution product will be deployed commercially and will achieve a TRL of 9 within one year after completion of the project.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2025

Statistical relationships across epigenomes using large-scale hierarchical clustering

Recent advances in genomics and sequencing platforms have revolutionized our ability to create immense data sets, particularly for studying epigenetic regulation of gene expression. However, the avalanche of epigenomic data is difficult to parse for biological interpretation given nonlinear complex patterns and relationships. This attractive challenge in epigenomic data lends itself to machine learning for discerning infectivity and susceptibility. In this study, we explore over 3000 epigenomes of uninfected individuals and provide a framework to characterize the relationships among epigenetic modifiers, their modifiers, genetic loci, and specific immune cell types across all chromosomes using hierarchical clustering. Hierarchical clustering of epigenomic data revealed consistent epigenetic patterns across chromosomes, demonstrating that variation due to epigenetic modifiers is greater than variation between cell types. Gene Ontology and KEGG pathway analyses indicated significant enrichment of genes involved in chromatin remodeling, mRNA splicing, immune responses, and the regulation of microRNAs and snoRNAs. Epigenetic modifiers frequently formed biologically relevant clusters, including the cohesin complex, RNA Polymerase II transcription factors, and PRC2 complex members. These clustering behaviors remained consistent across all chromosomes, supported by entropy analysis and high Adjusted Rand Index scores, indicating robust cross-chromosomal similarity. Co-occurrence analysis further revealed specific sets of modifiers that consistently appeared together within clusters, reflecting shared biological functions and interactions. Validation using another dataset confirmed the reproducibility of these clustering patterns and modifier co-occurrence relationships, underscoring the reliability and generalizability of the methodology.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

MAPredict: Static Analysis Driven Memory Access Prediction Framework for Modern CPUs

Application memory access patterns are crucial in deciding how much traffic is served by the cache and forwarded to the dynamic random-access memory (DRAM). However, predicting such memory traffic is difficult because of the interplay of prefetchers, compilers, parallel execution, and innovations in manufacturer-specific micro-architectures. This research introduced MAPredict, a static analysis-driven framework that addresses these challenges to predict last-level cache (LLC)-DRAM traffic. By exploring and analyzing the behavior of modern Intel processors, MAPredict formulates cache-aware analytical models. MAPredict invokes these models to predict LLC-DRAM traffic by combining the application model, machine model, and user-provided hints to capture dynamic information. MAPredict successfully predicts LLC-DRAM traffic for different regular access patterns and provides the means to combine static and empirical observations for irregular access patterns. Evaluating 130 workloads from six applications on recent Intel micro-architectures, MAPredict yielded an average accuracy of 99% for streaming, 91% for strided, and 92% for stencil patterns. By coupling static and empirical methods, up to 97% average accuracy was obtained for random access patterns on different micro-architectures.

Monil, M. A. H.↗

DOE OSTI2015

TU-CD-BRB-05: Radiation Damage Signature of White Matter Fiber Bundles Using Diffusion Tensor Imaging (DTI)

Purpose: To develop an automated and scalable approach and identify temporal, spatial and dosimetric patterns of radiation damage of white matter (WM) fibers following partial brain irradiation. Methods: An automated and scalable approach was developed to extract DTI features of 22 major WM fibers from 33 patients with low-grade/benign tumors treated by radiation therapy (RT). DTI scans of the patients were performed pre-RT, 3- and 6-week during RT, and 1, 6 and 18 months after RT. The automated tractography analysis was applied to 198 datasets as: (1) intra-subject registration of longitudinal DTI, (2) spatial normalization of individual-patient DTI to the Johns Hopkins WM Atlas, (3) automatic fiber tracking regulated by the WM Atlas, and (4) segmentation of WM into 22 major tract profiles. Longitudinal percentage changes in fractional anisotropy (FA), and mean, axial and radial diffusivity (MD/AD/RD) of each tract from pre-RT were quantified and correlated to 95%, 90% and 80% percentiles of doses and mean doses received by the tract. Heatmaps were used to identify clusters of significant correlation and reveal temporal, spatial and dosimetric signatures of WM damage. A multivariate linear regression was further carried out to determine influence of clinical factors. Results: Of 22 tracts, AD/MD changes in 12 tracts had significant correlation with doses, especially at 6 and 18 months post-RT, indicating progressive radiation damage after RT. Most interestingly, the DTI-index changes in the elongated tracts were associated with received maximum doses, suggesting a serial-structure behavior; while short association fibers were affected by mean doses, indicating a parallel-structure response. Conclusion: Using an automated DTI-tractography analysis of whole brain WM fibers, we reveal complex radiation damage patterns of WM fibers. Damage in WM fibers that play an important role in the neural network could be associated with late neurocognitive function declines after brain irradiation. NIH NS064973.

60 APPLIED LIFE SCIENCES↗