Search NASA⌕ Search

SEARCH · Search NASA

Results for “measurement quality”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 253 records · Page 14

High-Quality Factor Microwave Resonators using Rhenium

Coplanar waveguide resonators are a perfect tool to evaluate the losses induced by defects and interfaces in superconducting devices. Even if niobium is the most used superconductor for resonators and qubits, its native oxide at the metal-air (MA) interface limits the device results. Tantalum has recently significantly improved qubit performances due to a thinner and less disordered oxide layer compared to Nb. To further improve the MA interface, we used rhenium, a superconducting material with 1.7 K critical temperature resistant to oxidation: it forms an oxide layer thinner than 1 nm. In this study, we will present a thorough investigation of rhenium CPW resonator measurements with internal quality factors at the single photon level exceeding 2 million. The devices have been fabricated on a sapphire substrate while the processing parameters have been varying and optimized. The measurements have been performed as a function of power and temperature to disentangle different sources of losses, such as two-level systems (TLS) and quasi-particles. A peculiar TLS temperature dependence has been measured and analyzed. In this work, we also vary the participation ratio of the devices to extract the losses introduced by the involved interfaces with higher fidelity and precision. We carried on a deep material characterization effort to link the results to the differences in the fabrication steps, and we will present material characterization measurements performed via AFM, ToF-SIMS, XPS, and TEM.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Microbiome response in an urban river system is dominated by seasonality over wastewater treatment upgrades

Background: Microorganisms such as coliform-forming bacteria are commonly used to assess freshwater quality for drinking and recreational use. However, such organisms do not exist in isolation; they exist within the context of dynamic, interactive microbial communities which vary through space and time. Elucidating spatiotemporal microbial dynamics is imperative for discriminating robust community changes from ephemeral ecological trends, and for improving our overall understanding of the relationship between microbial communities and ecosystem health. We conducted a seven-year (2013–2019) microbial time-series investigation in the Chicago Area Waterways (CAWS): an urban river system which, in 2016, experienced substantial upgrades to disinfection processes at two wastewater reclamation plants (WRPs) that discharge into the CAWS and improved stormwater capture, to improve river water quality and reduce flooding. Using culture-independent and culture-dependent approaches, we compared CAWS microbial ecology before and after the intervention. Results: Examinations of time-resolved beta distances between WRP-adjacent sites showed that community similarity measures were often consistent with the spatial orientation of site locations to one another and to the WRP outfalls. Fecal coliform results suggested that upgrades reduced coliform-associated bacteria in the effluent and the downstream river community. However, examinations of whole community changes through time suggest that the upgrades did little to affect overall riverine community dynamics, which instead were overwhelmingly driven by yearly patterns consistent with seasonality. Conclusions: This study presents a systematic effort to combine 16S rRNA gene amplicon sequencing with traditional culture-based methods to evaluate the influence of treatment innovations and systems upgrades on the microbiome of the Chicago Area Waterway System, representing the longest and most comprehensive characterization of the microbiome of an urban waterway yet attempted. We found that the systems upgrades were successful in improving specific water quality measures immediately downstream of wastewater outflows. Additionally, we found that the implementation of the water quality improvement measures to the river system did not disrupt the overall dynamics of the downstream microbial community, which remained heavily influenced by seasonal trends. Such results emphasize the dynamic nature of microbiomes in open environmental systems such as the CAWS, but also suggest that the seasonal oscillations remain consistent even when perturbed.

16S rRNA gene sequencing↗

Robust Event Classification Using Imperfect Real-world PMU Data

Here, this paper studies robust event classification using imperfect real-world phasor measurement unit (PMU) data. By analyzing the real-world PMU data, we find it is challenging to directly use this dataset for event classifiers due to the low data quality observed in PMU measurements and event logs. To address these challenges, we develop a novel machine learning framework for training robust event classifiers, which consists of three main steps: data preprocessing, fine-grained event data extraction, and feature engineering. Specifically, the data preprocessing step addresses the data quality issues of PMU measurements (e.g., bad data and missing data); in the fine-grained event data extraction step, a model-free event detection method is developed to accurately localize the events from the inaccurate event timestamps in the event logs; and the feature engineering step constructs the event features based on the patterns of different event types, in order to improve the performance and the interpretability of the event classifiers. Based on the proposed framework, we develop a workflow for event classification using the real-world PMU data streaming into the system in real time. Using the proposed framework, robust event classifiers can be efficiently trained based on many off-the-shelf lightweight machine learning models. Numerical experiments using the real-world dataset from the Western Interconnection of the U.S power transmission grid show that the event classifiers trained under the proposed framework can achieve high classification accuracy while being robust against low-quality data.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Chitosan Coating Incorporated with Carvacrol Improves Postharvest Guava (Psidium guajava) Quality

Guava (Psidium guajava L.) is an important economic crop grown widely in tropical and subtropical regions. Guava exhibits fast ripening and senescence as a climacteric fruit, causing a short shelf life and quality deterioration. Chitosan–essential oil nanoemulsions can be an edible coating used to improve postharvest quality attributes. In this study, chitosan was mixed with carvacrol to generate a nano-emulsoid solution containing 0.1 and 0.2% (v/v) carvacrol, using a sonic dismembrator. Guava fruit were coated with the above emulsion and postharvest quality parameters were measured during storage at 20 ± 1 °C and RH = 80 ± 5% for 8 days. The result illustrated that the particle size of the chitosan–carvacrol emulsions was nanoscale, and their high stability was demonstrated by the zeta potential and polydispersity index. Chitosan coating (2%, w/v, 310–375 kDa) containing 0.2% (v/v) carvacrol maintained postharvest quality compared to chitosan alone, with higher firmness, soluble solid content, total acid, and total phenol content, and lower weight loss and pericarp browning. The collective data were further verified by principal component analysis. A chitosan coating containing carvacrol can reduce postharvest losses. It can be applied as an effective strategy to improve postharvest fruit quality.

Agriculture↗

A Comprehensive Open-Source R Software For Statistical Metrology Calculations: From Uncertainty Evaluation To Risk Analysis

Whether calibrating equipment or inspecting products on the factory floor, metrology requires many complicated statistical calculations to achieve a full understanding and evaluation of measurement uncertainty and quality. In order to assist its workforce in performing these calculations in a consistent and rigorous way, the Primary Standards Lab at Sandia National Laboratories (SNL) has developed a free and open-source software package for computing various metrology calculations from uncertainty propagation to risk analysis. In addition to propagating uncertainty through a measurement model using the well-known Guide to Expression of Uncertainty in Measurement or Monte Carlo approaches, evaluating the individual Type A and Type B uncertainty components that go into the measurement model often requires other statistical methods such as analysis of variance or determining uncertainty in a fitted curve. Once the uncertainty in a measurement has been calculated, it is usually evaluated from a risk perspective to ensure the measurement is suitable for making a particular conformance decision. Finally, SNL’s software can perform all these calculations in a single application via an easy-to-use graphical interface, where the different functions are integrated so the results of one calculation can be used as inputs to another calculation.

97 MATHEMATICS AND COMPUTING↗

High- Q Microwave Dielectric Resonator for Axion Dark-Matter Haloscopes

The frequency band 1–15 GHz provides exciting prospects for resonant axion haloscopes as indicated by cosmological and astrophysical arguments. Among the challenges currently addressed to reach the required sensitivity, the development of high-quality factor cavities that tolerate multitesla fields plays a central role. We report a three-dimensional resonator based on a right-circular copper cavity with hollow cylinders that confine higher-order modes around the cylinder axis. Its effective volume at 10.3 GHz is 3.4 × 10 − 2 l, and under an 8-T field we measure an internal quality factor of more than nine million. A fine-tuning system limited to approximately 1 -MHz range is tested, useful for understanding the conditions required to run a haloscope with a cavity exceeding the axion quality factor. The cavity parameters we report demonstrate the potential of this unique resonator to probe galactic dark-matter axion at scan rates exceeding 2 MHz/day when the cavity is readout by a quantum-limited receiver.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Kinetic model-based group contribution method for derived cetane number prediction of oxygenated fuel components and blends

A four-step autoignition model was used to derive an expression for the ignition delay (ID) measured in ignition quality testers (IQT) with the derived cetane number (DCN) determined from this ID using the ASTM D6890 standard correlation. The model predicts DCN for individual compounds and blends as a function of each compound's global initiation and net chain branching rate constants. Expressions for these values were determined assuming they could be related to the functional groups present in each compound. Measurement data for 125 compounds and 94 binary and ternary blends (including oxygenates: alcohols, aldehydes, esters, ethers, and ketones), from literature and from measurements performed in our lab, were used to obtain the dependence of the measured ignition delay on each functional group. The new kinetic model-based group contribution method was able to predict the ignition delay of both pure compounds and blends, with an average DCN error of 4.4 (19%) and 2.8 (11%), respectively. Here, the blend model was also used to develop an ID mixing rule by incorporating existing IQT ignition delay data for each compound. Use of the mixing rule gave an average DCN error of 3.6 (16%) for blends. Both the blend model and mixing rule were found to be superior compared to standard linear by volume fraction or mole fraction mixing rules commonly used to estimate the DCN of mixtures.

42 ENGINEERING↗

Increasing the power of weak lensing data with multipole-based intrinsic alignment estimators

ABSTRACT It has long been known that galaxy shapes align coherently with the large-scale density field. Characterizing this effect is essential to interpreting measurements of weak gravitational lensing, the deflection of light from distant galaxies by matter overdensities along the line of sight, as it also produces coherent galaxy alignments that we wish to interpret in terms of a cosmological model. Existing direct measurements of intrinsic alignments using galaxy samples with high-quality shape and redshift measurements typically use well-understood but sub-optimal projected estimators, which do not make good use of the information in the data when comparing those estimators to theoretical models. We demonstrate a more optimal estimator, based on a multipole expansion of the correlation functions or power spectra, for direct measurements of galaxy intrinsic alignments. We show that even using the lowest order multipole alone increases the significance of inferred model parameters using simulated and real data, without any additional modelling complexity. We apply this estimator to measurements of parameters of the non-linear alignment model using data from the Sloan Digital Sky survey, demonstrating consistent results with a factor of ∼2 greater precision in parameter fits to intrinsic alignments models. This result is functionally equivalent to quadrupling the survey area, but without the attendant costs – thereby demonstrating the value in using this new estimator in current and future intrinsic alignments measurements using spectroscopic galaxy samples.

Astronomy & Astrophysics↗

Loss tangent fluctuations due to two-level systems in superconducting microwave resonators

Superconducting microwave resonators are critical to quantum computing and sensing technologies. Additionally, they are common proxies for superconducting qubits when determining the effects of performance-limiting loss mechanisms such as from two-level systems (TLSs). The extraction of these loss mechanisms is often performed by measuring the internal quality factor Qi as a function of power or temperature. In this work, we investigate large temporal fluctuations of Qi at low powers over periods of 12–16 h (relative standard deviation σQi/Qi=13%). These fluctuations are ubiquitous across multiple resonators, chips, and cooldowns. We are able to attribute these fluctuations to variations in the TLS loss tangent due to two main indicators. First, measured fluctuations decrease as power and temperature increase. Second, for interleaved measurements, we observe correlations between low- and medium-power Qi fluctuations and an absence of correlations with high-power fluctuations. Agreement with the TLS loss tangent mean is obtained by performing measurements over a time span of a few hours. We hypothesize that, in addition to decoherence, due to coupling to individual near-resonant TLS, superconducting qubits are affected by these observed TLS loss tangent fluctuations.

Vallières, André [Northwestern U.; Fermilab] (ORCI↗

CROCUS Air Quality Data at Chicago State University Prairie Site

The Air Quality Transmitter (AQT) (Vaisala AQT530) instrument provides observations on meteorological conditions, including particulate matter (PM2.5, PM10), gas species concentrations (Nitric Oxide (NO), Nitrogen Dioxide (NO2), Ozone (O3)), and environment temperature and moisture. These measurements are critical for understanding air quality. These measurements are useful for understanding changes in aerosol properties, air quality research, and comparing to model experiments especially in urban environments.This dataset is from the Department of Energy Office of Science funded project, Community Research on Urban and Climate Science (CROCUS) (https://crocus-urban.org/). Datasets are stored in the netCDF data format, and we we encourage users to make use the associated toolkits available from Unidata (https://www.unidata.ucar.edu/software/netcdf/), Project Pythia (https://foundations.projectpythia.org/core/data-formats/netcdf-cf.html), and our “Instrument Cookbooks” (https://crocus-urban.github.io/instrument-cookbooks) for more information on how to process the metadata-rich datasets.

54 ENVIRONMENTAL SCIENCES↗

Mitigating Electrochemical Impedance Spectroscopy Artifacts in PEMWE Reference Electrode Measurements

This study investigates strategies to improve the quality of electrochemical impedance spectroscopy (EIS) measurements using reference electrodes (RE) in proton exchange membrane water electrolyzers (PEMWE). We demonstrate that adding a low impedance wire in parallel to the RE significantly enhances signal accuracy, especially at high frequencies. Additionally, we identify electrical pad heaters as a source of measurement noise. EIS measurements fulfilling Kramers–Kronig validity criteria were only achieved in their absence. These insights advance the diagnostic capabilities of REs in water electrolyzers and support more reliable, spatially resolved analysis of electrochemical losses within the cell.

08 HYDROGEN↗

Comparative Analysis of TRGBs (CATs) from Unsupervised, Multi-halo-field Measurements: Contrast is Key

The tip of the red giant branch (TRGB) is an apparent discontinuity of the luminosity function (LF) due to the end of the red giant evolutionary phase and is used to measure distances in the local universe. In practice, tip localization via edge detection response (EDR) relies on several methods applied on a case-by-case basis. It is hard to evaluate how individual choices affect a distance estimation using only a single host field while also avoiding confirmation bias. To devise a standardized approach, we compare unsupervised, algorithmic analyses of the TRGB in multiple halo fields per galaxy. We first optimize methods for the lowest field-to-field dispersion, including spatial filtering, smoothing, and weighting of LF, color band selection, and tip selection based on the number of likely RGB stars and the ratio of stars below versus above the tip (R). We find R, which we call the tip contrast, to be the most important indicator of the quality of EDR measurements; higher R selection can decrease field-to-field dispersion. Further, since R is found to correlate with the age or metallicity of the stellar population based on theoretical modeling, it might result in a displacement of the detected tip magnitude. We find a tip-contrast relation with a slope of -0.023 ± 0.0046 mag/ratio, an ~5σ result that can be used to correct these variations in the detections. When using TRGB to establish a distance ladder, consistent TRGB standardization using tip-contrast relation across rungs is vital to make robust cosmological measurements.

79 ASTRONOMY AND ASTROPHYSICS↗

CROCUS Air Quality Data at Northeastern Illinois University Rooftop

This dataset is from the Department of Energy Office of Science funded project, Community Research on Urban and Climate Science (CROCUS) (https://crocus-urban.org/). The AQT (Vaisala AQT530) instrument provides observations on meteorological conditions, including particulate matter (PM2.5, PM10), gas species concentrations (NO, NO2, O3, CO), and environment temperature and moisture. These measurements are critical for understanding air quality. These measurements are useful for understanding changes in aerosol properties, air quality research, and comparing to model experiments especially in urban environments.Datasets are stored in the netCDF data format, and we we encourage users to make use the associated toolkits available from Unidata (https://www.unidata.ucar.edu/software/netcdf/), Project Pythia (https://foundations.projectpythia.org/core/data-formats/netcdf-cf.html), and our “Instrument Cookbooks” (https://crocus-urban.github.io/instrument-cookbooks) for more information on how to process the metadata-rich datasets.

54 ENVIRONMENTAL SCIENCES↗

Modeling dust mineralogical composition: sensitivity to soil mineralogy atlases and their expected climate impacts

Soil dust aerosols are a key component of the climate system, as they interact with short- and long-wave radiation, alter cloud formation processes, affect atmospheric chemistry and play a role in biogeochemical cycles by providing nutrient inputs such as iron and phosphorus. The influence of dust on these processes depends on its physicochemical properties, which, far from being homogeneous, are shaped by its regionally varying mineral composition. The relative amount of minerals in dust depends on the source region and shows a large geographical variability. However, many state-of-the-art Earth system models (ESMs), upon which climate analyses and projections rely, still consider dust mineralogy to be invariant. The explicit representation of minerals in ESMs is more hindered by our limited knowledge of the global soil composition along with the resulting size-resolved airborne mineralogy than by computational constraints. In this work we introduce an explicit mineralogy representation within the state-of-the-art Multiscale Online Nonhydrostatic AtmospheRe CHemistry (MONARCH) model. We review and compare two existing soil mineralogy datasets, which remain a source of uncertainty for dust mineralogy modeling and provide an evaluation of multiannual simulations against available mineralogy observations. Soil mineralogy datasets are based on measurements performed after wet sieving, which breaks the aggregates found in the parent soil. Our model predicts the emitted particle size distribution (PSD) in terms of its constituent minerals based on brittle fragmentation theory (BFT), which reconstructs the emitted mineral aggregates destroyed by wet sieving. Our simulations broadly reproduce the most abundant mineral fractions independently of the soil composition data used. Feldspars and calcite are highly sensitive to the soil mineralogy map, mainly due to the different assumptions made in each soil dataset to extrapolate a handful of soil measurements to arid and semi-arid regions worldwide. For the least abundant or more difficult-to-determine minerals, such as iron oxides, uncertainties in soil mineralogy yield differences in annual mean aerosol mass fractions of up to ~ 100 %. Although BFT restores coarse aggregates including phyllosilicates that usually break during soil analysis, we still identify an overestimation of coarse quartz mass fractions (above 2 µm in diameter). In a dedicated experiment, we estimate the fraction of dust with undetermined composition as given by a soil map, which makes up ~ 10 % of the emitted dust mass at the global scale and can be regionally larger. Changes in the underlying soil mineralogy impact our estimates of climate-relevant variables, particularly affecting the regional variability of the single-scattering albedo at solar wavelengths or the total iron deposited over oceans. All in all, this assessment represents a baseline for future model experiments including new mineralogical maps constrained by high-quality spaceborne hyperspectral measurements, such as those arising from the NASA Earth Surface Mineral Dust Source Investigation (EMIT) mission.

54 ENVIRONMENTAL SCIENCES↗

Using electron channeling contrast imaging to inform and improve the growth of high-efficiency GaAs solar cells on nanopatterned GaAs substrates

Patterned substrates provide opportunities for reducing the cost of high-efficiency III-V devices by incorporating mechanically weak layers beneficial for substrate reuse (e.g. by spalling). In this work, the functionality of electron channeling contrast imaging (ECCI) as a tool to efficiently understand and mitigate defect formation is exemplified by developing a process in which high-quality III-V material can be grown on nanopatterned GaAs substrates. Reactive ion etching used in the patterning process was found to damage the GaAs substrate surface, leading to the formation of stacking faults in the epitaxial material as observed by ECCI. Etching the patterned substrates in a 1 NH4OH: 1 H2O2: 50 DI H2O solution for 10 s prior to growth removed the substrate surface damage and stacking faults were no longer present. Growth of solar cell device structures initially produced samples with many macroscale flaws creating shunts in the devices, which complicated the assessment of material quality by device measurements. However, ECCI revealed that the epitaxial material surrounding macroscale flaws was free from any crystallographic defects such as stacking faults and threading dislocations. With this knowledge, we focused on refining the patterning process to eliminate the macroscale flaws. Solar cells were then grown on the improved nanopatterned substrates and exhibited device structures with defect densities less than 5 x 105 cm -2 and average conversion efficiency of 24.8%, nearly identical to devices grown on unpatterned epi-ready substrates (25.0%).

14 SOLAR ENERGY↗

Extreme Antiscaling Performance of Slippery Omniphobic Covalently Attached Liquids

Scale formation presents an enormous cost to the global economy. Classical nucleation theory dictates that to reduce the heterogeneous nucleation of scale, the surface should have low surface energy and be as smooth as possible. Past approaches have focused on lowering surface energy via the use of hydrophobic coatings and have created atomically smooth interfaces to eliminate nucleation sites, or both, via the infusion of low-surface-energy lubricants into rough superhydrophobic substrates. Although lubricant-based surfaces are promising candidates for antiscaling, lubricant drainage inhibits their utilization. Here, we develop methodologies to deposit slippery omniphobic covalently attached liquids (SOCAL) on arbitrary substrates. Similar to lubricant-based surfaces, SOCAL has ultralow roughness and surface energy, enabling low nucleation rates and eliminating the need to replenish the lubricant. To enable SOCAL coating on metals, we investigated the surface chemistry required to ensure high-quality functionalization as measured by ultralow contact angle hysteresis (<3°). Using a multilayer deposition approach, we first electrophoretically deposit (EPD) silicon dioxide (SiO 2 ) as an intermediate layer between the metallic substrate and SOCAL. The necessity of EPD SiO 2 is to smooth (<10 nm roughness) as well as to enable the proper surface chemistry for SOCAL bonding. To characterize antiscaling performance, we utilized calcium sulfate (CaSO 4 ) scale tests, showing a 20× reduction in scale deposition rate than untreated metallic substrates. Descaling tests revealed that SOCAL dramatically decreases scale adhesion, resulting in rapid removal of scale buildup. Furthermore, our work not only demonstrates a robust methodology for depositing antiscaling SOCAL coatings on metals but also develops design guidelines for the creation of antifouling coatings for alternate applications such as biofouling and high-temperature coking.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗