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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

MEMOTE for standardized genome-scale metabolic model testing

Reconstructing metabolic reaction networks enables the development of testable hypotheses of an organism’s metabolism under different conditions. State-of-the-art genome-scale metabolic models (GEMs) can include thousands of metabolites and reactions that are assigned to subcellular locations. Gene–protein–reaction (GPR) rules and annotations using database information can add meta-information to GEMs. GEMs with metadata can be built using standard reconstruction protocols, and guidelines have been put in place for tracking provenance and enabling interoperability, but a standardized means of quality control for GEMs is lacking. Here we report a community effort to develop a test suite named MEMOTE (for metabolic model tests) to assess GEM quality.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Magnetic anisotropy and GGG substrate stray field in YIG films down to millikelvin temperatures

Abstract Quantum magnonics investigates the quantum-mechanical properties of magnons, such as quantum coherence or entanglement for solid-state quantum information technologies at the nanoscale. The most promising material for quantum magnonics is the ferrimagnetic yttrium iron garnet (YIG), which hosts magnons with the longest lifetimes. YIG films of the highest quality are grown on a paramagnetic gadolinium gallium garnet (GGG) substrate. The literature has reported that ferromagnetic resonance (FMR) frequencies of YIG/GGG decrease at temperatures below 50 K despite the increase in YIG magnetization. We investigated a 97 nm-thick YIG film grown on 500 μm-thick GGG substrate through a series of experiments conducted at temperatures as low as 30 mK, and using both analytical and numerical methods. Our findings suggest that the primary factor contributing to the FMR frequency shift is the stray magnetic field created by the partially magnetized GGG substrate. This stray field is antiparallel to the applied external field and is highly inhomogeneous, reaching up to 40 mT in the center of the sample. At temperatures below 500 mK, the GGG field exhibits a saturation that cannot be described by the standard Brillouin function for a paramagnet. Including the calculated GGG field in the analysis of the FMR frequency versus temperature dependence allowed the determination of the cubic and uniaxial anisotropies. We find that the total crystallographic anisotropy increases more than three times with the decrease in temperature down to 2 K. Our findings enable accurate predictions of the YIG/GGG magnetic systems behavior at low and ultralow millikelvin temperatures, crucial for developing quantum magnonic devices.

Serha, Rostyslav O.↗
DOE OSTI2021

Improve Learning from Crowds via Generative Augmentation

Crowdsourcing provides an efficient label collection schema for supervised machine learning. However, to control annotation cost, each instance in the crowdsourced data is typically annotated by a small number of annotators. This creates a sparsity issue and limits the quality of machine learning models trained on such data. In this paper, we study how to handle sparsity in crowdsourced data using data augmentation. Specifically, we propose to directly learn a classifier by augmenting the raw sparse annotations. We implement two principles of high-quality augmentation using Generative Adversarial Networks: 1) the generated annotations should follow the distribution of authentic ones, which is measured by a discriminator; 2) the generated annotations should have high mutual information with the ground-truth labels, which is measured by an auxiliary network. Extensive experiments and comparisons against an array of state-of-the-art learning from crowds methods on three real-world datasets proved the effectiveness of our data augmentation framework. It shows the potential of our algorithm for low-budget crowdsourcing in general.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2024

DAWN: Dashboard for Agricultural Water Use and Nutrient Management—A Predictive Decision Support System to Improve Crop Production in a Changing Climate

Abstract Climate change presents huge challenges to the already-complex decisions faced by U.S. agricultural producers, as seasonal weather patterns increasingly deviate from historical tendencies. Under USDA funding, a transdisciplinary team of researchers, extension experts, educators, and stakeholders is developing a climate decision support Dashboard for Agricultural Water use and Nutrient management (DAWN) to provide Corn Belt farmers with better predictive information. DAWN’s goal is to provide credible, usable information to support decisions by creating infrastructure to make subseasonal-to-seasonal forecasts accessible. DAWN uses an integrated approach to 1) engage stakeholders to coproduce a decision support and information delivery system; 2) build a coupled modeling system to represent and transfer holistic systems knowledge into effective tools; 3) produce reliable forecasts to help stakeholders optimize crop productivity and environmental quality; and 4) integrate research and extension into experiential, transdisciplinary education. This article presents DAWN’s framework for integrating climate–agriculture research, extension, and education to bridge science and service. We also present key challenges to the creation and delivery of decision support, specifically in infrastructure development, coproduction and trust building with stakeholders, product design, effective communication, and moving tools toward use.

Meteorology & Atmospheric Sciences↗
DOE OSTI2021

An adaptable technique for comparative image assessment: Application to crosswell electromagnetic survey design for fluid monitoring

Reservoir integrity stewardship accompanying carbon capture and sequestration considers fluid extraction and reinjection as a risk-mitigating method against overpressuring that could lead to caprock damage and ensuing [Formula: see text] leakage. Crosswell electromagnetics offers a technically viable monitoring method with the spatial volume coverage necessary for reservoir-encompassing pressure management. However, a certain logistic dilemma for deep gas sequestration into saline and thus electrically conductive aquifers is that crosswell magnetic-field measurements underperform in the imaging of more resistive plume bodies, further exacerbated when vertical arrays intersect, as opposed to surround, plumes. Furthermore, comparative synthetic-data plume imaging of such scenarios rates the information content of magnetic-field versus electric-field 3D crosswell layouts for reservoir and infrastructure conditions of a representative pilot site in a coastal area in Florida. The image quality of the resulting plume replications can be ranked numerically through a newly proposed semblance qualifier, appraising the model goodness of fit to a given reference. In contrast to common least-squares measures for goodness of fit, the semblance formulation uses classifying logistic function types, thus enabling a better distinction of predefined anomaly features.

58 GEOSCIENCES↗
DOE OSTI2022

Towards optimal gas cooling with minimal aero-optical distortion for a laser amplifier head

Next-generation lasers combining high-peak-power, ultrashort pulses with high repetition rates have the potential to efficiently deliver the high-average-power outputs required by many emerging technologies and areas of research. This work introduces a three-stage workflow consisting of low- and high-fidelity fluid simulations, in addition to aero-optical analyses. The final goal is to optimize gas cooling within a laser amplifier head while maintaining minimal aero-optical distortions. Low-fidelity RANS simulations are used to obtain mean flow solutions and transition locations. High-fidelity LES simulations, informed by their RANS counterparts, provide solutions containing density fluctuations, which are then passed on to the aero-optical analysis. The aero-optical analysis provides insight into the optical quality of the laser beam passing through the flow found in the LES results.

42 ENGINEERING↗
DOE OSTI2022

Fabrication of Advanced Nanocarbon-Metal Composites for Improved Energy Efficiency

We fabricated nanocarbon metal composites (NCMC) of Al alloys with a process called “electrocharging assisted process” (EAP). This method consists of the application of a high current to a mixture of liquid metal and carbon particles. We investigated aluminum alloys (6061 and 1350) and used activated carbon and graphite powder as the source of carbon. The high current induces the formation of carbon chains and ribbons in the liquid metal. Upon solidification of the metal an epitaxial relation between the carbon nanostructures and the metal lattice is produced. The purpose of the project was to find the parameters during the reaction that would give rise to a high density of nanoribbons extending throughout the metal such that the electrical conductivity and the mechanical strength of the composite increased and that the method could be extended to large scale manufacturing. For this purpose, we designed two reactors for the incorporation of nanocarbon ribbons in aluminum metal. The first reactor was designed to have more control of the region with the high current density. However, there were problems with getting good mixing of the carbon in small volumes. A second reactor was designed with a stirrer that allowed for better mixing of the carbon by the introduction of argon gas through the shaft of the stirrer. NCMC were fabricated with a series of parameters to understand the role of current, time of applied current, type and shape of the cathode electrode and stirring speed of the mixture. We analyzed the composites by Raman scattering to gain information on the crystallite size of the nanocarbon, XRD to obtain the crystal structure of the composite, SEM and TEM to characterize the grain size of the aluminum grains and the quality of the crystal structure. We also measured the electrical conductivity and mechanical properties of selected samples. The nanocomposites showed increase in crystallite size of the nanocarbon with a linear dependence of the crystallite size on the duration of the applied current. There is a minimum current density necessary for the crystallite size to increase compared to the ~ 10 nm size of the activated carbon source used in the fabrication. The electrical conductivity of the nanocomposites increased with crystallite size of the nanocarbon and with the concentration of converted carbon. The maximum increase in electrical conductivity was 5.7% above the baseline for samples with ~ 4 wt % nanocarbon with crystallite size larger than 30 nm. These samples presented a hardness ~ 8% higher than the baseline samples with no carbon.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Novel frequency tunable systems for superconducting cavities (Abbreviated Report)

Ultra-low loss microwave resonant cavities are the backbone of quantum information science (QIS) and axion/dark matter detection (ADMX), but one of the challenges in developing 3D cavity systems has been finding a tuning mechanism that does not drastically reduce the cavity quality factor (Q) but still provides a large operating bandwidth. To alleviate this limitation, we proposed to fabricate a high-Q, 3D microwave cavity with an integrated hybrid mechanical/electrical tuning scheme to achieve both coarse and rapid fine tuning. We implemented two tuning schemes: one using a shift in kinetic inductance and one utilizing mechanical motion. We found that the kinetic inductance method did not yield any tunability in the cavity mode, but the mechanical adjustment successfully moved the cavity resonance. The quality factors obtained were lower than originally proposed, but there is potential to improve the design on further iterations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Sampling and Analysis Plan for LSL2 Underground Storage Tank Evaluation of PFAS in Soil: Protection of Groundwater

This SAP gathers all pertinent information relevant to the sampling and analysis of soil at the removal site for a former 10,000-gallon UST and reference sites in the vicinity of the excavation site. Data Quality Objectives establishes the process and steps for the acquisition of data. Data Flow Diagram establishes the decisions and next steps. Quality Assurance Project Plan establishes the quality requirements for data collection, including planning, implementation, and assessment of sampling, field measurements, and laboratory analysis. The work is being completed for DOE-SC Pacific Northwest Site Office.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Count Every Trip: Finding the Uncertainty in Energy Estimates Made from Inferred Travel Modes

To properly inform transport policy and infrastructure changes, transportation related metrics need both measured values and uncertainties of those values. Travel monitoring smartphone apps can record people's travel behavior, but trip data quality is limited by sensor errors, user labeling rates and the accuracy of inference algorithms used for travel diary creation. We discuss the use of phone app recorded travel diary data to estimate energy consumption, and propose the use of propagation of variance to find error bars for such estimates. We define energy consumption for one trip as trip length times the energy intensity per distance unit of the travel mode used. We characterize trip length errors with relative error and inferred trip mode errors with confusion matrix columns. The resulting variances of each measurement are then propagated to the final calculated energy consumption. We tested our uncertainty methods on a dataset that used phone app data combined with prompted recall, consisting of 92,234 labeled trips for over 500,000 miles. Accounting for uncertainty using expected energy intensities and variance propagation gives a dataset-wide aggregate energy consumption percent error of about 9%, within one standard deviation from the truth. Future work could involve applying similar methods to other travel diary based metrics.

ADVANCED PROPULSION SYSTEMS,MATHEMATICS AND COMPUT↗
DOE OSTI2023

Count Every Trip: Finding the Uncertainty in Energy Estimates Made from Inferred Travel Modes

To properly inform transport policy and infrastructure changes, transportation related metrics need both measured values and uncertainties of those values. Travel monitoring smartphone apps can record people's travel behavior, but trip data quality is limited by sensor errors, user labeling rates and the accuracy of inference algorithms used for travel diary creation. We discuss the use of phone app recorded travel diary data to estimate energy consumption, and propose the use of propagation of variance to find error bars for such estimates. We define energy consumption for one trip as trip length times the energy intensity per distance unit of the travel mode used. We characterize trip length errors with relative error and inferred trip mode errors with confusion matrix columns. The resulting variances of each measurement are then propagated to the final calculated energy consumption. We tested our uncertainty methods on a dataset that used phone app data combined with prompted recall, consisting of 92,234 labeled trips for over 500,000 miles. Accounting for uncertainty using expected energy intensities and variance propagation gives a dataset-wide aggregate energy consumption percent error of about 9%, within one standard deviation from the truth. Future work could involve applying similar methods to other travel diary based metrics.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Estimating Travel Energy Consumption Uncertainty Based on Inferred Travel Mode and Sensed Travel Length

To properly inform transport policy and infrastructure changes, transportation related metrics need both measured values and uncertainties of those values. Travel monitoring smartphone apps can record people's travel behavior, but trip data quality is limited by sensor errors, user labeling rates and the accuracy of inference algorithms used for travel diary creation. We discuss the use of phone app recorded travel diary data to estimate energy consumption, and propose the use of propagation of variance to find error bars for such estimates. We define energy consumption for one trip as trip length times the energy intensity per distance unit of the travel mode used. We characterize trip length errors with relative error and inferred trip mode errors with confusion matrix columns. The resulting variances of each measurement are then propagated to the final calculated energy consumption. We tested our uncertainty methods on a dataset that used phone app data combined with prompted recall, consisting of 92,234 labeled trips for over 500,000 miles. Accounting for uncertainty using expected energy intensities and variance propagation gives a dataset-wide aggregate energy consumption percent error of about 8%, within one standard deviation from the truth. Future work could involve applying similar methods to other travel diary based metrics.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗
DOE OSTI2021

Occupant-Centric key performance indicators to inform building design and operations

Building performance indicators are widely used to guide building design and track and benchmark operational performance. Traditional building performance indicators mostly focus on the energy efficiency perspective. As occupants are the primary building service recipients in residential and most commercial buildings, their comfort and wellbeing are crucial. As such, this study first identified significant attributes of occupant-centric key performance indicators (KPIs) and analyzed the diverse factors that should be considered in formulating an occupant-centric KPI. Then a suite of occupant-centric KPIs were synthesized from the review and enhancement of existing occupant-related performance metrics. The proposed occupant KPIs represent the occupant lens on three integrative aspects of building performance: resource use (including energy and water), indoor environmental quality, and human–building interactions. A simulation-based case study was conducted to demonstrate how occupant-centric KPIs can be used to quantify the impacts of building operation changes from the occupants’ point of view. Highlights: Occupant-centric metrics are currently ad hoc and limited, yet crucial to inform building design and operations. Literature was reviewed to reveal the state-of-the-art and gaps of occupant-centric metrics. A suite of occupant-centric key performance indicators (KPIs) covering five groups of building services were synthesized. Proposed occupant KPIs represent three aspects of performance: resource use and demand, occupant comfort and health, and human–building interactions. A case study using whole building simulation was conducted to demonstrate the use of occupant-centric KPIs in evaluating building operations during a power outage.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Analysis of DWPF Sludge Batch 6 (Macrobatch 7): Pour Stream Glass Samples

The Defense Waste Processing Facility (DWPF) began processing Sludge Batch 6 (SB6), also referred to as Macrobatch 7 (MB7), in June 2010. SB6 is a blend of the heel of Tank 40 from Sludge Batch 5 (SB5), H-Canyon Np transfers and SB6 that was transferred to Tank 40 from Tank 51.1 SB6 was processed using Frit 418. Sludge is received into the DWPF Chemical Processing Cell (CPC) and is processed through the Sludge Receipt and Adjustment Tank (SRAT) and Slurry Mix Evaporator Tank (SME). The treated sludge slurry is then transferred to the Melter Feed Tank (MFT) and fed to the melter. During processing of each sludge batch, the DWPF is required to take at least one glass sample to meet the objectives of the Glass Product Control Program (GPCP) and to complete the necessary Production Records so that the final glass product may be disposed of at a Federal Repository. The DWPF requested various analyses of radioactive glass samples obtained from the melter pour stream during processing of SB6 as well as reduction/oxidation (REDOX) analysis of MFT samples to determine the impact of Argon bubbling. Sample analysis followed the Task Technical and Quality Assurance Plan (TTQAP) and an Analytical Study Plan (ASP). Four Pour Stream (PS) glass samples and two MFT slurry samples were delivered to the Savannah River National Laboratory (SRNL) from the DWPF. Table 1-1 lists the sample information for each pour stream glass sample. SB6 PS3 (S03472) was selected as the official pour stream sample for SB6 and full analysis was requested. This report details the visual observations of the as-received SB6 PS No.3 glass sample as well as results for the chemical composition, Product Consistency Test (PCT), radionuclide content, noble metals, and glass density. REDOX results will be provided for all four pour stream samples and vitrified samples of MFT-558 and MFT-568A. Where appropriate, data from other pour stream samples will be provided.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Grazer-induced changes in molecular signatures of cyanobacteria

Algal biomass production is an emerging renewable source of fuels, nutrients, manufacturing materials, and pharmaceuticals. Industrial-scale production is predominantly performed in open raceway ponds that are inexpensive to build, operate, and maintain compared to closed bioreactors. However, these open pond systems suffer from increased opportunities for biological contamination from predators, pathogens, and competitors, which result in reduced biomass quality and yields and often the complete destruction of the crop over a short period of time. Early detection of contaminants is a necessary step of integrated pest management for triggering and informing interventions to prevent crop losses. To develop a sensitive method of detection utilizing mass spectrometry (MS), we used three methods – imaging mass spectrometry (imaging MS), liquid chromatography MS/MS (LC-MS/MS) combined with molecular networking, and gas chromatography MS/MS (GC–MS/MS) – to observe and identify molecular signatures from a model predator-prey system of the heterolobosean amoeba HGG1 preying on the filamentous cyanobacterium Anabaena sp. PCC 7120. Imaging MS enabled the association of molecules with the crop, the predator, or the activity of protozoan grazing, while LC-MS/MS-based molecular networking identified a subset of the grazing-specific signals as the chlorophyll breakdown products pyropheophytin, pheophorbide A, and pyropheophorbide. Application of MS techniques to other amoebacyanobacterial predator-prey pairs allowed categorization of grazing signatures as universal or specific to the species of prey, predator, or the prey-predator pairing, indicating that MS-based techniques can distinguish crops from competitors and potentially identify predators. Finally, GCMS/MS was shown to be capable of monitoring novel volatile organic compounds (VOCs), including those predicted to be released through chlorophyll breakdown, in the headspace over algal cultures under predation. Furthermore, these results demonstrate that the combination of multiple MS technologies creates a predictive framework to identify and catalog relevant molecular signatures for informing crop protection strategies.

09 BIOMASS FUELS↗
DOE OSTI2025

Strain-tunable microwave-resonance technique for quantum materials

By integrating a dielectric microwave resonator with a piezoelectric-based strain device, we develop an in situ strain-tunable microwave spectroscopy technique that enables contactless measurements of material properties under strain. To demonstrate the capability of this device, we measure the strain-dependent microwave surface impedance of the representative iron-based superconductor Ba⁢Fe 2 (As 1−𝑥 ⁢P 𝑥 ) 2 at the slightly overdoped composition. We successfully control and observe the suppression of superconductivity under both compressive and tensile anisotropic lattice distortions along the tetragonal [110] T direction, as manifested by changes in the quality factor and resonance frequency shifts of microwave resonance. Furthermore, strain-induced changes in microwave surface resistivity, an extension of conventional DC-limit transport elastoresistivity to the microwave regime, provide information on electronic anisotropy equivalent to that of DC elastoresistivity, while offering a contactless alternative. Furthermore, our strain-tunable cavity therefore serves as a powerful, contactless probe of fundamental material properties under strain and may also potentially facilitate the design of hybrid quantum systems with strain-engineered quantum degrees of freedom.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

36 Hz integral linewidth laser based on a photonic integrated 4.0 m coil resonator

Laser stabilization sits at the heart of many precision scientific experiments and applications, including quantum information science, metrology, and atomic timekeeping. Many of these systems narrow the laser linewidth and stabilize the carrier by use of Pound–Drever–Hall (PDH) locking to a table-scale, ultrahigh quality factor (Q), vacuum spaced Fabry–Perot reference cavity. Integrating these cavities to bring characteristics of PDH stabilization to the chip scale is critical to reducing their size, cost, and weight, and enabling a wide range of portable and system-on-chip applications. We report a significant advance in integrated laser linewidth narrowing, stabilization, and noise reduction by use of a photonic integrated 4.0 m long coil resonator to stabilize a semiconductor laser. We achieve a 36 Hz 1 / π <#comment/> -integral linewidth, Allan deviation of 1.8 × <#comment/> 10 − <#comment/> 13 at 10 ms measurement time, and a 2.3 kHz/s drift—to the best of our knowledge, the lowest integral linewidth and highest stability demonstrated for an integrated waveguide reference cavity. This performance represents over an order of magnitude improvement in integral linewidth and frequency noise over previous integrated waveguide PDH stabilized reference cavities and bulk-optic and integrated injection locked approaches, and over two orders of magnitude improvement in frequency and phase noise than integrated injection locked approaches. Two different wavelength coil designs are demonstrated, stabilizing lasers at 1550 nm and 1319 nm. The resonator is bus-coupled to a 4.0 m long coil, with a 49 MHz free spectral range, mode volume of 1.0 × <#comment/> 10 10 µ <#comment/> m 3 , and 142 million intrinsic Q , fabricated in a CMOS compatible, ultralow loss silicon nitride waveguide platform. Our measurements and simulations show that the thermorefractive noise floor for this particular cavity is reached for frequencies down to 20 Hz in an ambient environment with simple passive vibration isolation and without vacuum or thermal isolation. The thermorefractive noise limited performance is estimated to yield an 8 Hz 1 / π <#comment/> -integral linewidth and Allan deviation of 5 × <#comment/> 10 − <#comment/> 14 at 10 ms, opening a stability regime that heretofore has been available only in fundamentally non-integrated systems. These results demonstrate the potential to bring the characteristics of laboratory-scale stabilized lasers to the integrated, wafer-scale compatible chip scale, and are of interest for a number of applications in quantum technologies and atomic, molecular, and optical physics, and with further developments below 10 Hz linewidth, can be highly relevant to ultralow noise microwave generation.

Liu, Kaikai (ORCID:0000000213609646)↗