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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Intrinsic exchange bias from interfacial reconstruction in an epitaxial Ni x Co y Fe 3– x – y O 4 (111)/α-Al 2 O 3 (0001) thin film family

Intrinsic exchange bias is known as the unidirectional exchange anisotropy that emerges in a nominally single-component ferro-(ferri-)magnetic system. In this work, with magnetic and structural characterizations, we demonstrate that intrinsic exchange bias is a general phenomenon in (Ni, Co, Fe)-based spinel oxide films deposited on α-Al 2 O 3 (0001) substrates, due to the emergence of a rock-salt interfacial layer consisting of antiferromagnetic CoO from interfacial reconstruction. We show that in Ni x Co y Fe 3–x–y O 4 (111)/α-Al 2 O 3 (0001) films, intrinsic exchange bias and interfacial reconstruction have consistent dependences on Co concentration y, while the Ni and Fe concentration appears to be less important. This work establishes a family of intrinsic exchange bias materials with great tunability by stoichiometry and highlights the strategy of interface engineering in controlling material functionalities.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

High Efficient THz Emission From Unbiased and Biased Semiconductor Nanowires Fabricated Using Electron Beam Lithography

Besides having perfect control on structural features, such as vertical alignment and uniform distribution by fabricating the wires via e-beam lithography and etching process, we also investigated the THz emission from these fabricated nanowires when they are applied DC bias voltage. To be able to apply a voltage bias, an interdigitated gold (Au) electrode was patterned on the high-quality InGaAs epilayer grown on InP substrate bymolecular beam epitaxy. Afterwards, perfect vertically aligned and uniformly distributed nanowires were fabricated in between the electrodes of this interdigitated pattern so that we could apply voltage bias to improve the THz emission. As a result, we achieved enhancement in the emitted THz radiation by ~four times, about 12 dB increase in power ratio at 0.25 THz with a DC biased electric field compared with unbiased NWs.

Biased emission↗
DOE OSTI2023

Effects of error, chimera, bias, and GC content on the accuracy of amplicon sequencing

ABSTRACT Targeted amplicon sequencing is widely used in microbial ecology studies. However, sequencing artifacts and amplification biases are of great concern. To identify sources of these artifacts, a systematic analysis was performed using mock communities comprised of 16S rRNA genes from 33 bacterial strains. Our results indicated that while sequencing errors were generally isolated to low-abundance operational taxonomic units, chimeric sequences were a major source of artifacts. Singleton and doubleton sequences were primarily chimeras. Formation of chimeric sequences was significantly correlated with the GC content of the targeted sequences. Low-GC-content mock community members exhibited lower rates of chimeric sequence formation. GC content also had a large impact on sequence recovery. The quantitative capacity was notably limited, with substantial recovery variations and weak correlation between anticipated and observed strain abundances. The mock community strains with higher GC content had higher recovery rates than strains with lower GC content. Amplification bias was also observed due to the differences in primer affinity. A two-step PCR strategy reduced the number of chimeric sequences by half. In addition, comparative analyses based on the mock communities showed that several widely used sequence processing pipelines/methods, including DADA2, Deblur, UCLUST, UNOISE, and UPARSE, had different advantages and disadvantages in artifact removal and rare species detection. These results are important for improving sequencing quality and reliability and developing new algorithms to process targeted amplicon sequences. IMPORTANCE Amplicon sequencing of targeted genes is the predominant approach to estimate the membership and structure of microbial communities. However, accurate reconstruction of community composition is difficult due to sequencing errors, and other methodological biases and effective approaches to overcome these challenges are essential. Using a mock community of 33 phylogenetically diverse strains, this study evaluated the effect of GC content on sequencing results and tested different approaches to improve overall sequencing accuracy while characterizing the pros and cons of popular amplicon sequence data processing approaches. The sequencing results from this study can serve as a benchmarking data set for future algorithmic improvements. Furthermore, the new insights on sequencing error, chimera formation, and GC bias from this study will help enhance the quality of amplicon sequencing studies and support the development of new data analysis approaches.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2006

Real-time Sub-cm Differential Orbit Determination of two Low-Earth Orbiters with GPS Bias Fixing

An effective technique for real-time differential orbit determination with GPS bias fixing is formulated. With this technique, only real-time GPS orbits and clocks are needed (available from the NASA Global Differential GPS System with 10-20 cm accuracy). The onboard, realtime orbital states of user satellites (few meters in accuracy) are used for orbit initialization and integration. An extended Kalman filter is constructed for the estimation of the differential orbit between the two satellites as well as a reference orbit, together with their associating dynamics parameters. Due to close proximity of the two satellites and of similar body shapes, the differential dynamics are highly common and can be tightly constrained which, in turn, strengthens the orbit estimation. Without explicit differencing of GPS data, double-differenced phase biases are formed by a transformation matrix. Integer-valued fixing of these biases are then performed which greatly strengthens the orbit estimation. A 9-day demonstration between GRACE orbits with baselines of approx.200 km indicates that approx.80% of the double-differenced phase biases can successfully be fixed and the differential orbit can be determined to approx.7 mm as compared to the results of onboard K-band ranging.

global positioning system (GPS)↗
NASA NTRS2021

Social Bias in AI and its Implications

Previous studies have documented many different types of biases that exist in artificial intelligence (AI) and machine learning (ML) systems. We reviewed the literature on AI and ML bias with a focus on social implications and found that bias in AI and ML can potentially have harmful social impacts on individuals and/or groups of people. By affecting people differently according to characteristics such as race, gender, or sexual orientation, AI and ML systems may lead to harm by exacerbating social inequities. We recount examples of issues that have occurred in systems that use technology that might be used at NASA and elsewhere so that similar issues might be identified and mitigated in future systems. We also provide interested parties with a gateway into existing work on social bias in AI and ML systems.

artificial intelligence (AI)↗
NASA NTRS2022

Regression Bias in using Solar Wind Measurements

Simultaneous solar wind measurements from the solar wind monitors, WIND and ACE, differ due to the spatial and temporal structure of the solar wind. Correlation studies that use these measurements as input may infer an incorrect correlation due to uncertainties arising from this spatial and temporal structure, especially at extreme and rare solar wind values. In particular, regression analysis will lead to a regression function whose slope is biased towards the mean value of the measurement parameter. This article demonstrates this regression bias by comparing simultaneous ACE and WIND solar wind measurements. A non-linear regression analysis between them leads to a perception of underestimation of extreme values of one measurement on average over the other. Using numerical experiments, we show that popular regression analysis techniques such as linear least-squares, orthogonal least-squares, and non-linear regression are not immune to this bias. Hence while using solar wind parameters as an independent variable in a correlation or regression analysis, random uncertainty in the independent variable can create unintended biases in the response of the dependent variable. More generally, the regression to the mean effect can impact both event-based, statistical studies of magnetospheric response to solar wind forcing.

magnetosphere↗
NASA NTRSDate not supplied

Coronal FIP Bias: From Full-Sun X-Ray Spectroscopy to Imaging Spectroscopy

The First Ionization Potential (FIP) bias, whereby the abundances of the low FIP elements in different coronal structures vary from their photospheric values and may also vary with time, has been known for a long time, but still poorly understood. X-ray spectroscopic observations of the Sun are very crucial to study the spatio-temporal variation, and to understand the physical mechanisms giving rise to the FIP bias. Recent X-ray spectroscopic observations of the Sun in disk-integrated mode by Solar X-ray Monitor (XSM) onboard Chandrayaan-2 enhanced our knowledge of the temporal variation of FIP bias during solar flares and in hot AR cores. Here we will summarize the results from these recent studies. Also we will discuss the importance of spatially resolved spectroscopic observation to understand the FIP bias. In this context we will explore the role of upcoming X-ray imaging spectrographs.

solar corona↗
DOE OSTI2016

Collaborative Project: Understanding Climate Model Biases in Tropical Atlantic and Their Impact on Simulations of Extreme Climate Events

Recent studies have revealed that among all the tropical oceans, the tropical Atlantic has experienced the most pronounced warming trend over the 20th century. Many extreme climate events affecting the U.S., such as hurricanes, severe precipitation and drought events, are influenced by conditions in the Gulf of Mexico and the Atlantic Ocean. It is therefore imperative to have accurate simulations of the climatic mean and variability in the Atlantic region to be able to make credible projections of future climate change affecting the U.S. and other countries adjoining the Atlantic Ocean. Unfortunately, almost all global climate models exhibit large biases in their simulations of tropical Atlantic climate. The atmospheric convection simulation errors in the Amazon region and the associated errors in the trade wind simulations are hypothesized to be a leading cause of the tropical Atlantic biases in climate models. As global climate models have resolutions that are too coarse to resolve some of the atmospheric and oceanic processes responsible for the model biases, we propose to use a high-resolution coupled regional climate model (CRCM) framework to address the tropical bias issue. We propose to combine the expertise in tropical coupled atmosphere-ocean modeling at Texas A&M University (TAMU) and the coupled land-atmosphere modeling expertise at Pacific Northwest National Laboratory (PNNL) to develop a comprehensive CRCM for the Atlantic sector within a general and flexible modeling framework. The atmospheric component of the CRCM will be the NCAR WRF model and the oceanic component will be the Rutgers/UCLA ROMS. For the land component, we will use CLM modified at PNNL to include more detailed representations of vegetation and soil hydrology processes. The combined TAMU-PNNL CRCM model will be used to simulate the Atlantic climate, and the associated land-atmosphere-ocean interactions at a horizontal resolution of 9 km or finer. A particular focus of the model development effort will be to optimize the performance of WRF and ROMS over several thousand of cores by focusing on both the parallel communication libraries and the I/O interfaces, in order to achieve the sustained throughput needed to perform simulations on such fine resolution grids. The CRCM model will be developed within the framework of the Coupler (CPL7) software that is part of the NCAR Community Earth System Model (CESM). Through efforts at PNNL and within the community, WRF and CLM have already been coupled via CPL7. Using the flux coupler approach for the whole CRCM model will allow us to flexibly couple WRF, ROMS, and CLM with each model running on its own grid at different resolutions. In addition, this framework will allow us to easily port parameterizations between CESM and the CRCM, and potentially allow partial coupling between the CESM and the CRCM. TAMU and PNNL will contribute cooperatively to this research endeavor. The TAMU team led by Chang and Saravanan has considerable experience in studying atmosphere-ocean interactions within tropical Atlantic sector and will focus on modeling issues that relate to coupling WRF and ROMS. The PNNL team led by Leung has extensive expertise in atmosphere-land interaction and will be responsible for improving the land surface parameterization. Both teams will jointly work on integrating WRF-ROMS and WRF-CLM to couple WRF, ROMS, and CLM through CPL7. Montuoro of the TAMU Supercomputing Center will be responsible for improving the MPI and Parallel IO interfaces of the CRCM. Both teams will contribute to the design and execution of the proposed numerical experiments and jointly perform analysis of the numerical experiments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Biases in southern hemisphere climate trends induced by coarsely specifying the temporal resolution of stratospheric ozone

Abstract Global climate models that do not include interactive middle atmosphere chemistry, such as most of those contributing to the Coupled Model Intercomparison Project Phase 5, typically specify stratospheric ozone using monthly mean, zonal mean values and linearly interpolate to the time resolution of the model. We show that this method leads to significant biases in the simulated climate of the southern hemisphere (SH) over the late twentieth century. Previous studies have attributed similar biases in simulated SH climate change to the effect of the spatial smoothing of the specified ozone, i.e., to using zonal mean concentrations. We here show that the bias in climate trends due to undersampling of the rapid temporal changes in ozone during the seasonal evolution of the Antarctic ozone hole is considerable and reaches all the way into the troposphere. Our results suggest that the bias can be substantially reduced by specifying daily ozone concentrations.

Neely, III, R. R.↗
DOE OSTI2015

RACORO continental boundary layer cloud investigations. 3. Separation of parameterization biases in single-column model CAM5 simulations of shallow cumulus

Climatically important low-level clouds are commonly misrepresented in climate models. The FAst-physics System TEstbed and Research (FASTER) project has constructed case studies from the Atmospheric Radiation Measurement (ARM) Climate Research Facility's Southern Great Plain site during the RACORO aircraft campaign to facilitate research on model representation of boundary-layer clouds. This paper focuses on using the single-column Community Atmosphere Model version 5 (SCAM5) simulations of a multi-day continental shallow cumulus case to identify specific parameterization causes of low-cloud biases. Consistent model biases among the simulations driven by a set of alternative forcings suggest that uncertainty in the forcing plays only a relatively minor role. In-depth analysis reveals that the model's shallow cumulus convection scheme tends to significantly under-produce clouds during the times when shallow cumuli exist in the observations, while the deep convective and stratiform cloud schemes significantly over-produce low-level clouds throughout the day. The links between model biases and the underlying assumptions of the shallow cumulus scheme are further diagnosed with the aid of large-eddy simulations and aircraft measurements, and by suppressing the triggering of the deep convection scheme. It is found that the weak boundary layer turbulence simulated is directly responsible for the weak cumulus activity and the simulated boundary layer stratiform clouds. Increased vertical and temporal resolutions are shown to lead to stronger boundary layer turbulence and reduction of low-cloud biases.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Ion Energy and Angular Distribution in Biased Inductively Coupled Ar/O 2 Discharges by Using a Hybrid Model

In this work, a global bulk plasma model coupled bi‐directionally with a Monte‐Carlo/fluid sheath model was developed for electronegative inductive discharges, to explore the ion energy function (IEDF) and angular distributions function (IADF) bombarding an rf‐biased electrode. At low bias voltage, the IEDF of shows a single energy peak that transforms into a bimodal distribution with increasing bias voltage. The IEDFs of and are always bimodal. The ion energy peak separation width largely depends on the ion masses. The IADFs are affected by the bias voltage, pressures and coil powers. The results at different coil powers indicate the importance of considering the collisions induced by atoms, especially in a a molecular gas.

Wen, De‐Qi↗
DOE OSTI2019

Mitigating Implicit Bias as a Leader

Bias. It’s a word that makes most of us squirm. Bias implies to us that we are “bad people” and are being accused of deliberately discriminating against others. Yet, if you ask a social scientist, you will find that it doesn't mean that at all; implicit bias is a neurologically based, energy-saving short cut. Our brains apply mental models to make thousands of quick decisions every day: which brand of milk to buy at the store or when to turn the wheel to avoid a traffic accident. Lastly, we form our implicit biases subconsciously over time, influenced by our upbringing, societal norms, and life experiences.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2016

Substrate bias induced synthesis of flowered-like bunched carbon nanotube directly on bulk nickel

Highlights: • Flowered-like bunched MWCNTs have been synthesized by MW PECVD technique. • Effect of substrate bias on the properties of MWCNT has been studied. • Minimum E{sub T} = 1.9 V/μm with β = 4770 has been obtained in the film deposited at −350 V. - Abstract: This paper reports the effect of substrate bias on the multiwalled carbon nanotube (MWCNT) deposited on nickel foil by microwave plasma enhanced chemical vapor deposition technique. The MWCNTs have been characterized by the scanning electron microscopy (SEM), high resolution transmission electron microscopy (HRTEM), Raman spectroscopy, field emission and current–voltage characteristic of the heterojunction diode. The SEM images exhibit unique hierarchical flowered-like bunched and conformally coated MWCNTs. Substrate bias induced ion bombardment helps in the enhancement of hydrocarbon dissociation and is responsible for flowered-like MWCNTs growth. The HRTEM micrographs show the base growth mechanism for MWCNTs. The value of turn on field for emission decreases from 5.5 to 1.9 V/μm and field enhancement factor increases from 927 to 4770, respectively, with the increase of substrate bias. The diode ideality factor of CNT/ n-Si heterojunction is evaluated as 2.4 and the on/off current ratio is found to be 7 at ±2 V, respectively.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Theoretical and experimental demonstration of the relationship between microstructure and the DC-bias-superposition characteristic of ferrite materials

Highlights: • We proved how to improve DC-bias-superposition characteristic of ferrites. • We confirmed the correctness of the theoretical result by experiment. • This research provides a good guide for developing more stable ferrites. - Abstract: DC-bias superposition is important for ferrite materials used in power components. However, methods of improving this characteristic of ferrites have not yet been clearly established. In this study, we theoretically prove that a ferrite with high intrinsic permeability composition and thick grain-boundary microstructure provides better DC-bias superposition than a ferrite with low intrinsic-permeability composition and thin grain-boundary microstructure given the same permeability. We then validate the theoretical results by experiments. Results can guide the development of ferrite materials while considering permeability and stability for the improvement of DC-bias superposition.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Bias-dependent displacement damage effects in a silicon avalanche photodiode

Radiation effects studies on a commercial beveled-edge avalanche photodiode (APD) showed that applying reverse bias to the device during irradiation enhanced the severity of apparent damage. Proton microbeam irradiations were made using a proton beam energy of 2 MeV and fluence ranging from 2.0 × 10 10 to 5.1 × 10 12 cm -2 . Charge collection measurements using the ion beam induced charge (IBIC) technique showed that relative losses increased by up to an order of magnitude when the reverse bias applied during irradiation increased from 50 to 1500 V. The presence of reverse bias also led to equivalent losses in charge collection that would only be seen in irradiations with an order of magnitude higher fluence in unbiased APDs. The results demonstrate that bias-enhanced irradiation damage is insufficiently understood and must be accounted for in characterizations of radiation effects.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Machine learning-based bias-corrected future projections of ozone concentrations from a chemistry-climate model

Reliable projection of future near-surface ozone is crucial for air quality management and health risk assessment. However, potential biases in spatial distribution, magnitude and trends in ozone concentrations simulated by global chemistry-climate models limit their applicability in regional-scale evaluations. In this study, LightGBM, a machine learning (ML) algorithm is applied to correct biases in CESM2-simulated ozone concentrations over China, the United States and Europe and calibrate future ozone projections under two diverse Shared Socioeconomic Pathways (SSP1-2.6 and SSP5-8.5) scenarios from 2020 to 2060. The ML-based correction significantly improves the spatial distribution and reduces the model bias by 40%–60%. It also reverses the potentially incorrect trend of ozone change under SSP1-2.6 in eastern China. When applying ML-based bias correction to CESM2 future projections, warm season mean ozone concentrations decrease across China, the United States, and Europe by –13.5, –17.9, and –13.7 µg/m³, respectively, between 2020 and 2060 in SSP1-2.6, while they increase by 9.4, 2.0, and 5.2 µg/m³ in SSP5-8.5. Decomposition analysis show that changes in anthropogenic emissions dominate future ozone changes in both scenarios, while strong climate penalty from ozone changes occurs in polluted eastern China and climate benefit is found in western China, the United States and Europe under SSP5-8.5. These findings demonstrate the value of combining ML with chemistry-climate models to produce more accurate air quality projections, thereby informing more effective and region-specific environmental protection strategies.

Chemistry Model↗
DOE OSTI2015

Implications of room temperature oxidation on crystal structure and exchange bias effect in Co/CoO nanoparticles

In this study, we describe how the exchange bias effect in Co/CoO nanoparticles depends on the size focusing and temperature treatment of precursor Co nanoparticles before oxidation at ambient conditions. By appealing to magnetization, microscopy, neutron and synchrotron x-ray measurements we found that as-synthesized Co nanoparticles readily oxidize in air only after 20 days. The highest exchange bias field of 814 Oe is observed at T = 2K. When the same nanoparticles are centrifuged and annealed at 70 °C in vacuum prior to oxidation, the exchange bias field is increased to 2570 Oe. Annealing of Co nanoparticles in vacuum improves their crystallinity and prevents complete oxidation, so that Co-core/CoO-shell structure is preserved even after 120 days. The crystal structure of CoO shell in both samples is different from its bulk counterpart. Implications of such distorted CoO shells on exchange bias are discussed. Coating of Co nanoparticles with amorphous silica shell makes them resistant to oxidation, but ultimately modifies the crystal structure of both Co core and SiO 2 shell.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2019

The Summertime Precipitation Bias in E3SM Atmosphere Model Version 1 over the Central United States

This study analyzes the summertime precipitation bias over the Central United States and its relationship to the simulated large-scale environment and the convection scheme in the Energy Exascale Earth System Model Atmosphere Model version 1. This relationship is mainly examined in a set of short-term hindcasts initialized with realistic large-scale conditions for the summer of 2011. Besides the uniform 1° model resolution, we adopt Regionally Refined Meshes to increase the model resolution to 0.25°over the contiguous United States. Additional five-year Atmospheric Model Intercomparison Project simulations are conducted to confirm that the results from the hindcasts are consistent with the climate runs. We find that the summertime dry precipitation bias over the Great Plains and the wet bias over the Rockies cannot be reduced simultaneously by changing resolution or tuning parameters. As for the diurnal cycle, Energy Exascale Earth System Model Atmosphere Model version 1 captures the general diurnal variation of the large-scale moisture transport and the large-scale upward motion over the Central United States. However, the diurnal cycle of precipitation over the Great Plains is out of phase with the diurnal variation of the large-scale environment because the convective precipitation dominates the total precipitation and its diurnal cycle, and it does not directly respond to the local moisture convergence and the large-scale upward motion. These results reemphasize the importance of improving the coupling of the convection to the large-scale environment in reducing the summer precipitation bias over the Central United States in climate models with the resolution of ~0.25°.

54 ENVIRONMENTAL SCIENCES↗